CINXE.COM

<!DOCTYPE html> <html lang="en" xmlns:fb="http://www.facebook.com/2008/fbml" class="wf-loading"> <head prefix="og: https://ogp.me/ns# fb: https://ogp.me/ns/fb# academia: https://ogp.me/ns/fb/academia#"> <meta charset="utf-8"> <meta name=viewport content="width=device-width, initial-scale=1"> <meta rel="search" type="application/opensearchdescription+xml" href="/open_search.xml" title="Academia.edu"> <title>RUDIGER VONDERHEYDT | Johns Hopkins University - Academia.edu</title>  <link href="//a.academia-assets.com/images/favicons/favicon-production.ico" rel="shortcut icon" type="image/vnd.microsoft.icon"> <link rel="apple-touch-icon" sizes="57x57" href="//a.academia-assets.com/images/favicons/apple-touch-icon-57x57.png"> <link rel="apple-touch-icon" sizes="60x60" href="//a.academia-assets.com/images/favicons/apple-touch-icon-60x60.png"> <link rel="apple-touch-icon" sizes="72x72" href="//a.academia-assets.com/images/favicons/apple-touch-icon-72x72.png"> <link rel="apple-touch-icon" sizes="76x76" href="//a.academia-assets.com/images/favicons/apple-touch-icon-76x76.png"> <link rel="apple-touch-icon" sizes="114x114" href="//a.academia-assets.com/images/favicons/apple-touch-icon-114x114.png"> <link rel="apple-touch-icon" sizes="120x120" href="//a.academia-assets.com/images/favicons/apple-touch-icon-120x120.png"> <link rel="apple-touch-icon" sizes="144x144" href="//a.academia-assets.com/images/favicons/apple-touch-icon-144x144.png"> <link rel="apple-touch-icon" sizes="152x152" href="//a.academia-assets.com/images/favicons/apple-touch-icon-152x152.png"> <link rel="apple-touch-icon" sizes="180x180" href="//a.academia-assets.com/images/favicons/apple-touch-icon-180x180.png"> <link rel="icon" type="image/png" href="//a.academia-assets.com/images/favicons/favicon-32x32.png" sizes="32x32"> <link rel="icon" type="image/png" href="//a.academia-assets.com/images/favicons/favicon-194x194.png" sizes="194x194"> <link rel="icon" type="image/png" href="//a.academia-assets.com/images/favicons/favicon-96x96.png" sizes="96x96"> <link rel="icon" type="image/png" href="//a.academia-assets.com/images/favicons/android-chrome-192x192.png" sizes="192x192"> <link rel="icon" type="image/png" href="//a.academia-assets.com/images/favicons/favicon-16x16.png" sizes="16x16"> <link rel="manifest" href="//a.academia-assets.com/images/favicons/manifest.json"> <meta name="msapplication-TileColor" content="#2b5797"> <meta name="msapplication-TileImage" content="//a.academia-assets.com/images/favicons/mstile-144x144.png"> <meta name="theme-color" content="#ffffff"> <script> window.performance && window.performance.measure && window.performance.measure("Time To First Byte", "requestStart", "responseStart"); </script> <script> (function() { if (!window.URLSearchParams || !window.history || !window.history.replaceState) { return; } var searchParams = new URLSearchParams(window.location.search); var paramsToDelete = [ 'fs', 'sm', 'swp', 'iid', 'nbs', 'rcc', // related content category 'rcpos', // related content carousel position 'rcpg', // related carousel page 'rchid', // related content hit id 'f_ri', // research interest id, for SEO tracking 'f_fri', // featured research interest, for SEO tracking (param key without value) 'f_rid', // from research interest directory for SEO tracking 'f_loswp', // from research interest pills on LOSWP sidebar for SEO tracking 'rhid', // referrring hit id ]; if (paramsToDelete.every((key) => searchParams.get(key) === null)) { return; } paramsToDelete.forEach((key) => { searchParams.delete(key); }); var cleanUrl = new URL(window.location.href); cleanUrl.search = searchParams.toString(); history.replaceState({}, document.title, cleanUrl); })(); </script> <script async src="https://www.googletagmanager.com/gtag/js?id=G-5VKX33P2DS"></script> <script> window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'G-5VKX33P2DS', { cookie_domain: 'academia.edu', send_page_view: false, }); gtag('event', 'page_view', { 'controller': "profiles/works", 'action': "summary", 'controller_action': 'profiles/works#summary', 'logged_in': 'false', 'edge': 'unknown', // Send nil if there is no A/B test bucket, in case some records get logged // with missing data - that way we can distinguish between the two cases. // ab_test_bucket should be of the form <ab_test_name>:<bucket> 'ab_test_bucket': null, }) </script> <script type="text/javascript"> window.sendUserTiming = function(timingName) { if (!(window.performance && window.performance.measure)) return; var entries = window.performance.getEntriesByName(timingName, "measure"); if (entries.length !== 1) return; var timingValue = Math.round(entries[0].duration); gtag('event', 'timing_complete', { name: timingName, value: timingValue, event_category: 'User-centric', }); }; window.sendUserTiming("Time To First Byte"); </script> <meta name="csrf-param" content="authenticity_token" /> <meta name="csrf-token" content="4QkyRMrphVk9hEAGNf2Yg5hJRUBYRtjNJ6X+tJwM9KCMxdur1QDeUX+Fu+OuPdwCSpBRKBZ0zReOoG9LQna1zw==" /> <link rel="stylesheet" media="all" href="//a.academia-assets.com/assets/wow-77f7b87cb1583fc59aa8f94756ebfe913345937eb932042b4077563bebb5fb4b.css" /><link rel="stylesheet" media="all" href="//a.academia-assets.com/assets/social/home-9e8218e1301001388038e3fc3427ed00d079a4760ff7745d1ec1b2d59103170a.css" /><link rel="stylesheet" media="all" href="//a.academia-assets.com/assets/design_system/heading-b2b823dd904da60a48fd1bfa1defd840610c2ff414d3f39ed3af46277ab8df3b.css" /><link rel="stylesheet" media="all" href="//a.academia-assets.com/assets/design_system/button-3cea6e0ad4715ed965c49bfb15dedfc632787b32ff6d8c3a474182b231146ab7.css" /><link crossorigin="" href="https://fonts.gstatic.com/" rel="preconnect" /><link href="https://fonts.googleapis.com/css2?family=DM+Sans:ital,opsz,wght@0,9..40,100..1000;1,9..40,100..1000&family=Gupter:wght@400;500;700&family=IBM+Plex+Mono:wght@300;400&family=Material+Symbols+Outlined:opsz,wght,FILL,GRAD@20,400,0,0&display=swap" rel="stylesheet" /><link rel="stylesheet" media="all" href="//a.academia-assets.com/assets/design_system/common-10fa40af19d25203774df2d4a03b9b5771b45109c2304968038e88a81d1215c5.css" /> <meta name="author" content="rudiger vonderheydt" /> <meta name="description" content="RUDIGER VONDERHEYDT, Johns Hopkins University: 6 Followers, 123 Research papers. Research interests: Special Theory Of Relativity, Natural Environment, and…" /> <meta name="google-site-verification" content="bKJMBZA7E43xhDOopFZkssMMkBRjvYERV-NaN4R6mrs" /> <script> var $controller_name = 'works'; var $action_name = "summary"; var $rails_env = 'production'; var $app_rev = '92477ec68c09d28ae4730a4143c926f074776319'; var $domain = 'academia.edu'; var $app_host = "academia.edu"; var $asset_host = "academia-assets.com"; var $start_time = new Date().getTime(); var $recaptcha_key = "6LdxlRMTAAAAADnu_zyLhLg0YF9uACwz78shpjJB"; var $recaptcha_invisible_key = "6Lf3KHUUAAAAACggoMpmGJdQDtiyrjVlvGJ6BbAj"; var $disableClientRecordHit = false; </script> <script> window.Aedu = { hit_data: null }; window.Aedu.SiteStats = {"premium_universities_count":15276,"monthly_visitors":"113 million","monthly_visitor_count":113784677,"monthly_visitor_count_in_millions":113,"user_count":277518545,"paper_count":55203019,"paper_count_in_millions":55,"page_count":432000000,"page_count_in_millions":432,"pdf_count":16500000,"pdf_count_in_millions":16}; window.Aedu.serverRenderTime = new Date(1732781678000); window.Aedu.timeDifference = new Date().getTime() - 1732781678000; window.Aedu.isUsingCssV1 = false; window.Aedu.enableLocalization = true; window.Aedu.activateFullstory = false; window.Aedu.serviceAvailability = { status: {"attention_db":"on","bibliography_db":"on","contacts_db":"on","email_db":"on","indexability_db":"on","mentions_db":"on","news_db":"on","notifications_db":"on","offsite_mentions_db":"on","redshift":"on","redshift_exports_db":"on","related_works_db":"on","ring_db":"on","user_tests_db":"on"}, serviceEnabled: function(service) { return this.status[service] === "on"; }, readEnabled: function(service) { return this.serviceEnabled(service) || this.status[service] === "read_only"; }, }; window.Aedu.viewApmTrace = function() { // Check if x-apm-trace-id meta tag is set, and open the trace in APM // in a new window if it is. var apmTraceId = document.head.querySelector('meta[name="x-apm-trace-id"]'); if (apmTraceId) { var traceId = apmTraceId.content; // Use trace ID to construct URL, an example URL looks like: // https://app.datadoghq.com/apm/traces?query=trace_id%31298410148923562634 var apmUrl = 'https://app.datadoghq.com/apm/traces?query=trace_id%3A' + traceId; window.open(apmUrl, '_blank'); } }; </script>  <link href="https://fonts.googleapis.com/css?family=Roboto:100,100i,300,300i,400,400i,500,500i,700,700i,900,900i" rel="stylesheet"> <link href="//maxcdn.bootstrapcdn.com/font-awesome/4.3.0/css/font-awesome.min.css" rel="stylesheet"> <link rel="stylesheet" media="all" href="//a.academia-assets.com/assets/libraries-a9675dcb01ec4ef6aa807ba772c7a5a00c1820d3ff661c1038a20f80d06bb4e4.css" /> <link rel="stylesheet" media="all" href="//a.academia-assets.com/assets/academia-bdb9e8c097f01e611f2fc5e2f1a9dc599beede975e2ae5629983543a1726e947.css" /> <link rel="stylesheet" media="all" href="//a.academia-assets.com/assets/design_system_legacy-056a9113b9a0f5343d013b29ee1929d5a18be35fdcdceb616600b4db8bd20054.css" /> <script src="//a.academia-assets.com/assets/webpack_bundles/runtime-bundle-005434038af4252ca37c527588411a3d6a0eabb5f727fac83f8bbe7fd88d93bb.js"></script> <script src="//a.academia-assets.com/assets/webpack_bundles/webpack_libraries_and_infrequently_changed.wjs-bundle-bae13f9b51961d5f1e06008e39e31d0138cb31332e8c2e874c6d6a250ec2bb14.js"></script> <script src="//a.academia-assets.com/assets/webpack_bundles/core_webpack.wjs-bundle-19a25d160d01bde427443d06cd6b810c4c92c6026e7cb31519e06313eb24ed90.js"></script> <script src="//a.academia-assets.com/assets/webpack_bundles/sentry.wjs-bundle-5fe03fddca915c8ba0f7edbe64c194308e8ce5abaed7bffe1255ff37549c4808.js"></script> <script> jade = window.jade || {}; jade.helpers = window.$h; jade._ = window._; </script>  <script id="tag-manager-head-root">(function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start': new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0], j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src= 'https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f); })(window,document,'script','dataLayer_old','GTM-5G9JF7Z');</script>  <script> window.gptadslots = []; window.googletag = window.googletag || {}; window.googletag.cmd = window.googletag.cmd || []; </script> <script type="text/javascript"> // TODO(jacob): This should be defined, may be rare load order problem. // Checking if null is just a quick fix, will default to en if unset. // Better fix is to run this immedietely after I18n is set. if (window.I18n != null) { I18n.defaultLocale = "en"; I18n.locale = "en"; I18n.fallbacks = true; } </script> <link rel="canonical" href="https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT" /> </head>   <body class='c-profiles/works a-summary logged_out'>  <div id="fb-root"></div><script>window.fbAsyncInit = function() { FB.init({ appId: "2369844204", version: "v8.0", status: true, cookie: true, xfbml: true }); // Additional initialization code. if (window.InitFacebook) { // facebook.ts already loaded, set it up. window.InitFacebook(); } else { // Set a flag for facebook.ts to find when it loads. window.academiaAuthReadyFacebook = true; } };</script><script>window.fbAsyncLoad = function() { // Protection against double calling of this function if (window.FB) { return; } (function(d, s, id){ var js, fjs = d.getElementsByTagName(s)[0]; if (d.getElementById(id)) {return;} js = d.createElement(s); js.id = id; js.src = "//connect.facebook.net/en_US/sdk.js"; fjs.parentNode.insertBefore(js, fjs); }(document, 'script', 'facebook-jssdk')); } if (!window.defer_facebook) { // Autoload if not deferred window.fbAsyncLoad(); } else { // Defer loading by 5 seconds setTimeout(function() { window.fbAsyncLoad(); }, 5000); }</script> <div id="google-root"></div><script>window.loadGoogle = function() { if (window.InitGoogle) { // google.ts already loaded, set it up. window.InitGoogle("331998490334-rsn3chp12mbkiqhl6e7lu2q0mlbu0f1b"); } else { // Set a flag for google.ts to use when it loads. window.GoogleClientID = "331998490334-rsn3chp12mbkiqhl6e7lu2q0mlbu0f1b"; } };</script><script>window.googleAsyncLoad = function() { // Protection against double calling of this function (function(d) { var js; var id = 'google-jssdk'; var ref = d.getElementsByTagName('script')[0]; if (d.getElementById(id)) { return; } js = d.createElement('script'); js.id = id; js.async = true; js.onload = loadGoogle; js.src = "https://accounts.google.com/gsi/client" ref.parentNode.insertBefore(js, ref); }(document)); } if (!window.defer_google) { // Autoload if not deferred window.googleAsyncLoad(); } else { // Defer loading by 5 seconds setTimeout(function() { window.googleAsyncLoad(); }, 5000); }</script> <div id="tag-manager-body-root">  <noscript><iframe src="https://www.googletagmanager.com/ns.html?id=GTM-5G9JF7Z" height="0" width="0" style="display:none;visibility:hidden"></iframe></noscript>   <script> window.addEventListener('load', function() { if (document.querySelector('input[name="commit"]')) { document.querySelector('input[name="commit"]').addEventListener('click', function() { gtag('event', 'click', { event_category: 'button', event_label: 'Log In' }) }) } }); </script> </div> <script>var _comscore = _comscore || []; _comscore.push({ c1: "2", c2: "26766707" }); (function() { var s = document.createElement("script"), el = document.getElementsByTagName("script")[0]; s.async = true; s.src = (document.location.protocol == "https:" ? "https://sb" : "http://b") + ".scorecardresearch.com/beacon.js"; el.parentNode.insertBefore(s, el); })();</script><img src="https://sb.scorecardresearch.com/p?c1=2&c2=26766707&cv=2.0&cj=1" style="position: absolute; visibility: hidden" /> <div id='react-modal'></div> <div class='DesignSystem'> <a class='u-showOnFocus' href='#site'> Skip to main content </a> </div> <div id="upgrade_ie_banner" style="display: none;"><p>Academia.edu no longer supports Internet Explorer.</p><p>To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to <a href="https://www.academia.edu/upgrade-browser">upgrade your browser</a>.</p></div><script>// Show this banner for all versions of IE if (!!window.MSInputMethodContext || /(MSIE)/.test(navigator.userAgent)) { document.getElementById('upgrade_ie_banner').style.display = 'block'; }</script> <div class="DesignSystem bootstrap ShrinkableNav"><div class="navbar navbar-default main-header"><div class="container-wrapper" id="main-header-container"><div class="container"><div class="navbar-header"><div class="nav-left-wrapper u-mt0x"><div class="nav-logo"><a data-main-header-link-target="logo_home" href="https://www.academia.edu/"><img class="visible-xs-inline-block" style="height: 24px;" alt="Academia.edu" src="//a.academia-assets.com/images/academia-logo-redesign-2015-A.svg" width="24" height="24" /><img width="145.2" height="18" class="hidden-xs" style="height: 24px;" alt="Academia.edu" src="//a.academia-assets.com/images/academia-logo-redesign-2015.svg" /></a></div><div class="nav-search"><div class="SiteSearch-wrapper select2-no-default-pills"><form class="js-SiteSearch-form DesignSystem" action="https://www.academia.edu/search" accept-charset="UTF-8" method="get"><input name="utf8" type="hidden" value="✓" autocomplete="off" /><i class="SiteSearch-icon fa fa-search u-fw700 u-positionAbsolute u-tcGrayDark"></i><input class="js-SiteSearch-form-input SiteSearch-form-input form-control" data-main-header-click-target="search_input" name="q" placeholder="Search" type="text" value="" /></form></div></div></div><div class="nav-right-wrapper pull-right"><ul class="NavLinks js-main-nav list-unstyled"><li class="NavLinks-link"><a class="js-header-login-url Button Button--inverseGray Button--sm u-mb4x" id="nav_log_in" rel="nofollow" href="https://www.academia.edu/login">Log In</a></li><li class="NavLinks-link u-p0x"><a class="Button Button--inverseGray Button--sm u-mb4x" rel="nofollow" href="https://www.academia.edu/signup">Sign Up</a></li></ul><button class="hidden-lg hidden-md hidden-sm u-ml4x navbar-toggle collapsed" data-target=".js-mobile-header-links" data-toggle="collapse" type="button"><span class="icon-bar"></span><span class="icon-bar"></span><span class="icon-bar"></span></button></div></div><div class="collapse navbar-collapse js-mobile-header-links"><ul class="nav navbar-nav"><li class="u-borderColorGrayLight u-borderBottom1"><a rel="nofollow" href="https://www.academia.edu/login">Log In</a></li><li class="u-borderColorGrayLight u-borderBottom1"><a rel="nofollow" href="https://www.academia.edu/signup">Sign Up</a></li><li class="u-borderColorGrayLight u-borderBottom1 js-mobile-nav-expand-trigger"><a href="#">more&nbsp<span class="caret"></span></a></li><li><ul class="js-mobile-nav-expand-section nav navbar-nav u-m0x collapse"><li class="u-borderColorGrayLight u-borderBottom1"><a rel="false" href="https://www.academia.edu/about">About</a></li><li class="u-borderColorGrayLight u-borderBottom1"><a rel="nofollow" href="https://www.academia.edu/press">Press</a></li><li class="u-borderColorGrayLight u-borderBottom1"><a rel="nofollow" href="https://medium.com/@academia">Blog</a></li><li class="u-borderColorGrayLight u-borderBottom1"><a rel="false" href="https://www.academia.edu/documents">Papers</a></li><li class="u-borderColorGrayLight u-borderBottom1"><a rel="nofollow" href="https://www.academia.edu/terms">Terms</a></li><li class="u-borderColorGrayLight u-borderBottom1"><a rel="nofollow" href="https://www.academia.edu/privacy">Privacy</a></li><li class="u-borderColorGrayLight u-borderBottom1"><a rel="nofollow" href="https://www.academia.edu/copyright">Copyright</a></li><li class="u-borderColorGrayLight u-borderBottom1"><a rel="nofollow" href="https://www.academia.edu/hiring"><i class="fa fa-briefcase"></i> We're Hiring!</a></li><li class="u-borderColorGrayLight u-borderBottom1"><a rel="nofollow" href="https://support.academia.edu/"><i class="fa fa-question-circle"></i> Help Center</a></li><li class="js-mobile-nav-collapse-trigger u-borderColorGrayLight u-borderBottom1 dropup" style="display:none"><a href="#">less&nbsp<span class="caret"></span></a></li></ul></li></ul></div></div></div><script>(function(){ var $moreLink = $(".js-mobile-nav-expand-trigger"); var $lessLink = $(".js-mobile-nav-collapse-trigger"); var $section = $('.js-mobile-nav-expand-section'); $moreLink.click(function(ev){ ev.preventDefault(); $moreLink.hide(); $lessLink.show(); $section.collapse('show'); }); $lessLink.click(function(ev){ ev.preventDefault(); $moreLink.show(); $lessLink.hide(); $section.collapse('hide'); }); })() if ($a.is_logged_in() || false) { new Aedu.NavigationController({ el: '.js-main-nav', showHighlightedNotification: false }); } else { $(".js-header-login-url").attr("href", $a.loginUrlWithRedirect()); } Aedu.autocompleteSearch = new AutocompleteSearch({el: '.js-SiteSearch-form'});</script></div></div> <div id='site' class='fixed'> <div id="content" class="clearfix"> <script>document.addEventListener('DOMContentLoaded', function(){ var $dismissible = $(".dismissible_banner"); $dismissible.click(function(ev) { $dismissible.hide(); }); });</script> <script src="//a.academia-assets.com/assets/webpack_bundles/profile.wjs-bundle-e032f1d55548c2f2dee4eac9fe52f38beaf13471f2298bb2ea82725ae930b83c.js" defer="defer"></script><script>Aedu.rankings = { showPaperRankingsLink: false } $viewedUser = Aedu.User.set_viewed( {"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT","photo":"/images/s65_no_pic.png","has_photo":false,"department":{"id":63566,"name":"Neuroscience","url":"https://johnshopkins.academia.edu/Departments/Neuroscience/Documents","university":{"id":64,"name":"Johns Hopkins University","url":"https://johnshopkins.academia.edu/"}},"position":"Emeritus","position_id":6,"is_analytics_public":false,"interests":[{"id":40051,"name":"Special Theory Of Relativity","url":"https://www.academia.edu/Documents/in/Special_Theory_Of_Relativity"},{"id":340277,"name":"Natural Environment","url":"https://www.academia.edu/Documents/in/Natural_Environment"},{"id":158205,"name":"Tuna Longline Fisheries","url":"https://www.academia.edu/Documents/in/Tuna_Longline_Fisheries"},{"id":1130559,"name":"Electric Field","url":"https://www.academia.edu/Documents/in/Electric_Field"},{"id":30959,"name":"Climate modeling","url":"https://www.academia.edu/Documents/in/Climate_modeling"},{"id":161,"name":"Neuroscience","url":"https://www.academia.edu/Documents/in/Neuroscience"}]} ); if ($a.is_logged_in() && $viewedUser.is_current_user()) { $('body').addClass('profile-viewed-by-owner'); } $socialProfiles = [{"id":45555815,"link":"https://profiles.google.com/109352452537318246797","name":"Google","link_domain":"profiles.google.com","icon":"//www.google.com/s2/u/0/favicons?domain=profiles.google.com"}]</script><div id="js-react-on-rails-context" style="display:none" data-rails-context="{"inMailer":false,"i18nLocale":"en","i18nDefaultLocale":"en","href":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT","location":"/RUDIGERVONDERHEYDT","scheme":"https","host":"johnshopkins.academia.edu","port":null,"pathname":"/RUDIGERVONDERHEYDT","search":null,"httpAcceptLanguage":null,"serverSide":false}"></div> <div class="js-react-on-rails-component" style="display:none" data-component-name="ProfileCheckPaperUpdate" data-props="{}" data-trace="false" data-dom-id="ProfileCheckPaperUpdate-react-component-7a871fa0-e7b0-464e-b704-7a9c5d34ae74"></div> <div id="ProfileCheckPaperUpdate-react-component-7a871fa0-e7b0-464e-b704-7a9c5d34ae74"></div> <div class="DesignSystem"><div class="onsite-ping" id="onsite-ping"></div></div><div class="profile-user-info DesignSystem"><div class="social-profile-container"><div class="left-panel-container"><div class="user-info-component-wrapper"><div class="user-summary-cta-container"><div class="user-summary-container"><div class="social-profile-avatar-container"><img class="profile-avatar u-positionAbsolute" border="0" alt="" src="//a.academia-assets.com/images/s200_no_pic.png" /></div><div class="title-container"><h1 class="ds2-5-heading-sans-serif-sm">RUDIGER VONDERHEYDT</h1><div class="affiliations-container fake-truncate js-profile-affiliations"><div><a class="u-tcGrayDarker" href="https://johnshopkins.academia.edu/">Johns Hopkins University</a>, <a class="u-tcGrayDarker" href="https://johnshopkins.academia.edu/Departments/Neuroscience/Documents">Neuroscience</a>, <span class="u-tcGrayDarker">Emeritus</span></div></div></div></div><div class="sidebar-cta-container"><button class="ds2-5-button hidden profile-cta-button grow js-profile-follow-button" data-broccoli-component="user-info.follow-button" data-click-track="profile-user-info-follow-button" data-follow-user-fname="RUDIGER" data-follow-user-id="99283352" data-follow-user-source="profile_button" data-has-google="false"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">add</span>Follow</button><button class="ds2-5-button hidden profile-cta-button grow js-profile-unfollow-button" data-broccoli-component="user-info.unfollow-button" data-click-track="profile-user-info-unfollow-button" data-unfollow-user-id="99283352"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">done</span>Following</button></div></div><div class="user-stats-container"><a><div class="stat-container js-profile-followers"><p class="label">Followers</p><p class="data">6</p></div></a><a><div class="stat-container js-profile-followees" data-broccoli-component="user-info.followees-count" data-click-track="profile-expand-user-info-following"><p class="label">Following</p><p class="data">0</p></div></a><a href="/RUDIGERVONDERHEYDT/mentions"><div class="stat-container"><p class="label">Mentions</p><p class="data">1</p></div></a><span><div class="stat-container"><p class="label"><span class="js-profile-total-view-text">Public Views</span></p><p class="data"><span class="js-profile-view-count"></span></p></div></span></div><div class="ri-section"><div class="ri-section-header"><span>Interests</span><a class="ri-more-link js-profile-ri-list-card" data-click-track="profile-user-info-primary-research-interest" data-has-card-for-ri-list="99283352">View All (6)</a></div><div class="ri-tags-container"><a data-click-track="profile-user-info-expand-research-interests" data-has-card-for-ri-list="99283352" href="https://www.academia.edu/Documents/in/Special_Theory_Of_Relativity"><div id="js-react-on-rails-context" style="display:none" data-rails-context="{"inMailer":false,"i18nLocale":"en","i18nDefaultLocale":"en","href":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT","location":"/RUDIGERVONDERHEYDT","scheme":"https","host":"johnshopkins.academia.edu","port":null,"pathname":"/RUDIGERVONDERHEYDT","search":null,"httpAcceptLanguage":null,"serverSide":false}"></div> <div class="js-react-on-rails-component" style="display:none" data-component-name="Pill" data-props="{"color":"gray","children":["Special Theory Of Relativity"]}" data-trace="false" data-dom-id="Pill-react-component-5ecd030b-27dc-4faa-9db7-5ffac20fc14a"></div> <div id="Pill-react-component-5ecd030b-27dc-4faa-9db7-5ffac20fc14a"></div> </a><a data-click-track="profile-user-info-expand-research-interests" data-has-card-for-ri-list="99283352" href="https://www.academia.edu/Documents/in/Natural_Environment"><div class="js-react-on-rails-component" style="display:none" data-component-name="Pill" data-props="{"color":"gray","children":["Natural Environment"]}" data-trace="false" data-dom-id="Pill-react-component-9d2bb60d-47e8-4c2b-9e61-4ccf9a0f137b"></div> <div id="Pill-react-component-9d2bb60d-47e8-4c2b-9e61-4ccf9a0f137b"></div> </a><a data-click-track="profile-user-info-expand-research-interests" data-has-card-for-ri-list="99283352" href="https://www.academia.edu/Documents/in/Tuna_Longline_Fisheries"><div class="js-react-on-rails-component" style="display:none" data-component-name="Pill" data-props="{"color":"gray","children":["Tuna Longline Fisheries"]}" data-trace="false" data-dom-id="Pill-react-component-401f1ba3-73a5-484f-a8fb-e9ce3f59512a"></div> <div id="Pill-react-component-401f1ba3-73a5-484f-a8fb-e9ce3f59512a"></div> </a><a data-click-track="profile-user-info-expand-research-interests" data-has-card-for-ri-list="99283352" href="https://www.academia.edu/Documents/in/Electric_Field"><div class="js-react-on-rails-component" style="display:none" data-component-name="Pill" data-props="{"color":"gray","children":["Electric Field"]}" data-trace="false" data-dom-id="Pill-react-component-6e69e588-413d-4fa5-84cb-aaee053c2e27"></div> <div id="Pill-react-component-6e69e588-413d-4fa5-84cb-aaee053c2e27"></div> </a><a data-click-track="profile-user-info-expand-research-interests" data-has-card-for-ri-list="99283352" href="https://www.academia.edu/Documents/in/Climate_modeling"><div class="js-react-on-rails-component" style="display:none" data-component-name="Pill" data-props="{"color":"gray","children":["Climate modeling"]}" data-trace="false" data-dom-id="Pill-react-component-555c5f20-0313-4c0a-a118-473fca8cc4a3"></div> <div id="Pill-react-component-555c5f20-0313-4c0a-a118-473fca8cc4a3"></div> </a></div></div><div class="external-links-container"><ul class="profile-links new-profile js-UserInfo-social"><li class="profile-profiles js-social-profiles-container"><i class="fa fa-spin fa-spinner"></i></li></ul></div></div></div><div class="right-panel-container"><div class="user-content-wrapper"><div class="uploads-container" id="social-redesign-work-container"><div class="upload-header"><h2 class="ds2-5-heading-sans-serif-xs">Uploads</h2></div><div class="documents-container backbone-social-profile-documents" style="width: 100%;"><div class="u-taCenter"></div><div class="profile--tab_content_container js-tab-pane tab-pane active" id="all"><div class="profile--tab_heading_container js-section-heading" data-section="Papers" id="Papers"><h3 class="profile--tab_heading_container">Papers by RUDIGER VONDERHEYDT</h3></div><div class="js-work-strip profile--work_container" data-work-id="109893024"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/109893024/Visual_cortical_processing_From_image_to_object_representation"><img alt="Research paper thumbnail of Visual cortical processing-From image to object representation" class="work-thumbnail" src="https://attachments.academia-assets.com/107879736/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/109893024/Visual_cortical_processing_From_image_to_object_representation">Visual cortical processing-From image to object representation</a></div><div class="wp-workCard_item"><span>Frontiers in Computer Science</span><span>, 2023</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Image understanding is often conceived as a hierarchical process with many levels, where complexi...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Image understanding is often conceived as a hierarchical process with many levels, where complexity and invariance of object representation gradually increase with level in the hierarchy. In contrast, neurophysiological studies have shown that figure-ground organization and border ownership coding, which imply understanding of the object structure of an image, occur at levels as low as V1 and V2 of the visual cortex. This cannot be the result of back-projections from object recognition centers because border-ownership signals appear well-before shape selective responses emerge in inferotemporal cortex. Ultra-fast border-ownership signals have been found not only for simple figure displays, but also for complex natural scenes. In this paper I review neurophysiological evidence for the hypothesis that the brain uses dedicated grouping mechanisms early on to link elementary features to larger entities we might call "proto-objects", a process that is pre-attentive and does not rely on object recognition. The proto-object structures enable the system to individuate objects and provide permanence, to track moving objects and cope with the displacements caused by eye movements, and to select one object out of many and scrutinize the selected object. I sketch a novel experimental paradigm for identifying grouping circuits, describe a first application targeting area V4, which yielded negative results, and suggest targets for future applications of this paradigm.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="956ef6c89d0110b6f9b0f1fc25c4d2f9" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":107879736,"asset_id":109893024,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/107879736/download_file?st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="109893024"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="109893024"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 109893024; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=109893024]").text(description); $(".js-view-count[data-work-id=109893024]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 109893024; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='109893024']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 109893024, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "956ef6c89d0110b6f9b0f1fc25c4d2f9" } } $('.js-work-strip[data-work-id=109893024]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":109893024,"title":"Visual cortical processing-From image to object representation","translated_title":"","metadata":{"doi":"10.3389/fcomp.2023.1136987","abstract":"Image understanding is often conceived as a hierarchical process with many levels, where complexity and invariance of object representation gradually increase with level in the hierarchy. In contrast, neurophysiological studies have shown that figure-ground organization and border ownership coding, which imply understanding of the object structure of an image, occur at levels as low as V1 and V2 of the visual cortex. This cannot be the result of back-projections from object recognition centers because border-ownership signals appear well-before shape selective responses emerge in inferotemporal cortex. Ultra-fast border-ownership signals have been found not only for simple figure displays, but also for complex natural scenes. In this paper I review neurophysiological evidence for the hypothesis that the brain uses dedicated grouping mechanisms early on to link elementary features to larger entities we might call \"proto-objects\", a process that is pre-attentive and does not rely on object recognition. The proto-object structures enable the system to individuate objects and provide permanence, to track moving objects and cope with the displacements caused by eye movements, and to select one object out of many and scrutinize the selected object. I sketch a novel experimental paradigm for identifying grouping circuits, describe a first application targeting area V4, which yielded negative results, and suggest targets for future applications of this paradigm.","publication_date":{"day":null,"month":null,"year":2023,"errors":{}},"publication_name":"Frontiers in Computer Science"},"translated_abstract":"Image understanding is often conceived as a hierarchical process with many levels, where complexity and invariance of object representation gradually increase with level in the hierarchy. In contrast, neurophysiological studies have shown that figure-ground organization and border ownership coding, which imply understanding of the object structure of an image, occur at levels as low as V1 and V2 of the visual cortex. This cannot be the result of back-projections from object recognition centers because border-ownership signals appear well-before shape selective responses emerge in inferotemporal cortex. Ultra-fast border-ownership signals have been found not only for simple figure displays, but also for complex natural scenes. In this paper I review neurophysiological evidence for the hypothesis that the brain uses dedicated grouping mechanisms early on to link elementary features to larger entities we might call \"proto-objects\", a process that is pre-attentive and does not rely on object recognition. The proto-object structures enable the system to individuate objects and provide permanence, to track moving objects and cope with the displacements caused by eye movements, and to select one object out of many and scrutinize the selected object. I sketch a novel experimental paradigm for identifying grouping circuits, describe a first application targeting area V4, which yielded negative results, and suggest targets for future applications of this paradigm.","internal_url":"https://www.academia.edu/109893024/Visual_cortical_processing_From_image_to_object_representation","translated_internal_url":"","created_at":"2023-11-26T16:01:57.163-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[{"id":40593739,"work_id":109893024,"tagging_user_id":99283352,"tagged_user_id":32407145,"co_author_invite_id":null,"email":"m***s@u.arizona.edu","affiliation":"The University of Arizona","display_order":1,"name":"Mary Peterson","title":"Visual cortical processing-From image to object representation"},{"id":40593740,"work_id":109893024,"tagging_user_id":99283352,"tagged_user_id":null,"co_author_invite_id":141508,"email":"g***t@berkeley.edu","display_order":2,"name":"Jack Gallant","title":"Visual cortical processing-From image to object representation"},{"id":40593741,"work_id":109893024,"tagging_user_id":99283352,"tagged_user_id":101974527,"co_author_invite_id":null,"email":"n***o@gmail.com","affiliation":"Radboud University Nijmegen","display_order":3,"name":"Naoki Kogo","title":"Visual cortical processing-From image to object representation"},{"id":40593742,"work_id":109893024,"tagging_user_id":99283352,"tagged_user_id":null,"co_author_invite_id":596605,"email":"v***t@jhu.edu","display_order":4,"name":"Rüdiger Von Der Heydt","title":"Visual cortical processing-From image to object representation"}],"downloadable_attachments":[{"id":107879736,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/107879736/thumbnails/1.jpg","file_name":"vonderHeydt_2023_From_image_to_object_representation.pdf","download_url":"https://www.academia.edu/attachments/107879736/download_file?st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Visual_cortical_processing_From_image_to.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/107879736/vonderHeydt_2023_From_image_to_object_representation-libre.pdf?1701045059=\u0026response-content-disposition=attachment%3B+filename%3DVisual_cortical_processing_From_image_to.pdf\u0026Expires=1732785277\u0026Signature=SzQeBDA2cVu~N3gmvr6PX7g2JSmN624K~3FdB4XeWAqIvjcoP75Q5JImrwNDohpXl7VyVqVKt0e0gQLXZckbljD~JQueDFh-Ga8ssf2jc82oD2izAXv0siJKCmUzaFHSD7yIQw9-qEtomICYnqposO4~cInLh69Q-Jhnt8KDKn053pWvLUJh6SqwKZFWQcZObl4BR0XuYFINanqHpCsYiNA8GNarFLEUix0Q-EqbhEDUjp2br4Noh6wk1NSojUwZaO6I-jEehPSZMuo8H9y2d9j4PdT7EaULWEgdOlPXV6qQdVp~lM1dTh7-NTsO3xmzUURxd5~iJHd3zkJA7dmskQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Visual_cortical_processing_From_image_to_object_representation","translated_slug":"","page_count":18,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[{"id":107879736,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/107879736/thumbnails/1.jpg","file_name":"vonderHeydt_2023_From_image_to_object_representation.pdf","download_url":"https://www.academia.edu/attachments/107879736/download_file?st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Visual_cortical_processing_From_image_to.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/107879736/vonderHeydt_2023_From_image_to_object_representation-libre.pdf?1701045059=\u0026response-content-disposition=attachment%3B+filename%3DVisual_cortical_processing_From_image_to.pdf\u0026Expires=1732785277\u0026Signature=SzQeBDA2cVu~N3gmvr6PX7g2JSmN624K~3FdB4XeWAqIvjcoP75Q5JImrwNDohpXl7VyVqVKt0e0gQLXZckbljD~JQueDFh-Ga8ssf2jc82oD2izAXv0siJKCmUzaFHSD7yIQw9-qEtomICYnqposO4~cInLh69Q-Jhnt8KDKn053pWvLUJh6SqwKZFWQcZObl4BR0XuYFINanqHpCsYiNA8GNarFLEUix0Q-EqbhEDUjp2br4Noh6wk1NSojUwZaO6I-jEehPSZMuo8H9y2d9j4PdT7EaULWEgdOlPXV6qQdVp~lM1dTh7-NTsO3xmzUURxd5~iJHd3zkJA7dmskQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":161,"name":"Neuroscience","url":"https://www.academia.edu/Documents/in/Neuroscience"},{"id":59692,"name":"Vision","url":"https://www.academia.edu/Documents/in/Vision"},{"id":118256,"name":"Object Perception","url":"https://www.academia.edu/Documents/in/Object_Perception"},{"id":242845,"name":"Object Permanence","url":"https://www.academia.edu/Documents/in/Object_Permanence"},{"id":700621,"name":"Visual Short Term Memory","url":"https://www.academia.edu/Documents/in/Visual_Short_Term_Memory"},{"id":1181061,"name":"Neural Signal","url":"https://www.academia.edu/Documents/in/Neural_Signal"},{"id":1851775,"name":"Perceptual organization","url":"https://www.academia.edu/Documents/in/Perceptual_organization"},{"id":2707350,"name":"Brain Mechanisms","url":"https://www.academia.edu/Documents/in/Brain_Mechanisms"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="75763340"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/75763340/Searching_for_object_pointers_in_the_visual_cortex"><img alt="Research paper thumbnail of Searching for object pointers in the visual cortex" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/75763340/Searching_for_object_pointers_in_the_visual_cortex">Searching for object pointers in the visual cortex</a></div><div class="wp-workCard_item"><span>Journal of Neurophysiology</span><span>, 2020</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The way we perceive objects as permanent contrasts with the short-lived responses of visual corti...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The way we perceive objects as permanent contrasts with the short-lived responses of visual cortical neurons. A theory postulates pointers that give objects continuity, predicting a class of neurons that respond not only to visual objects but also when an occluded object moves into their receptive field. Here, we tested this theory with a novel paradigm in which a monkey freely scans an array of objects while some of them are transiently occluded.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75763340"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75763340"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75763340; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75763340]").text(description); $(".js-view-count[data-work-id=75763340]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75763340; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75763340']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 75763340, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=75763340]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75763340,"title":"Searching for object pointers in the visual cortex","translated_title":"","metadata":{"abstract":"The way we perceive objects as permanent contrasts with the short-lived responses of visual cortical neurons. A theory postulates pointers that give objects continuity, predicting a class of neurons that respond not only to visual objects but also when an occluded object moves into their receptive field. Here, we tested this theory with a novel paradigm in which a monkey freely scans an array of objects while some of them are transiently occluded.","publisher":"American Physiological Society","publication_date":{"day":null,"month":null,"year":2020,"errors":{}},"publication_name":"Journal of Neurophysiology"},"translated_abstract":"The way we perceive objects as permanent contrasts with the short-lived responses of visual cortical neurons. A theory postulates pointers that give objects continuity, predicting a class of neurons that respond not only to visual objects but also when an occluded object moves into their receptive field. Here, we tested this theory with a novel paradigm in which a monkey freely scans an array of objects while some of them are transiently occluded.","internal_url":"https://www.academia.edu/75763340/Searching_for_object_pointers_in_the_visual_cortex","translated_internal_url":"","created_at":"2022-04-07T17:07:00.449-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Searching_for_object_pointers_in_the_visual_cortex","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[],"research_interests":[{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science"},{"id":465,"name":"Artificial Intelligence","url":"https://www.academia.edu/Documents/in/Artificial_Intelligence"},{"id":22272,"name":"Neurophysiology","url":"https://www.academia.edu/Documents/in/Neurophysiology"},{"id":2922956,"name":"Psychology and Cognitive Sciences","url":"https://www.academia.edu/Documents/in/Psychology_and_Cognitive_Sciences"},{"id":3763225,"name":"Medical and Health Sciences","url":"https://www.academia.edu/Documents/in/Medical_and_Health_Sciences"}],"urls":[{"id":19232103,"url":"https://journals.physiology.org/doi/pdf/10.1152/jn.00112.2020"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="75763339"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/75763339/Figure_ground_organization_in_the_visual_cortex_does_meaning_matter"><img alt="Research paper thumbnail of Figure-ground organization in the visual cortex: does meaning matter?" class="work-thumbnail" src="https://attachments.academia-assets.com/83404935/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/75763339/Figure_ground_organization_in_the_visual_cortex_does_meaning_matter">Figure-ground organization in the visual cortex: does meaning matter?</a></div><div class="wp-workCard_item"><span>Journal of Neurophysiology</span><span>, 2018</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Figure-ground organization in the visual cortex is generally assumed to be based partly on genera...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Figure-ground organization in the visual cortex is generally assumed to be based partly on general rules and partly on specific influences of object recognition in higher centers as found in the temporal lobe. To see if shape familiarity influences figure-ground organization, we tested border ownership-selective neurons in monkey V1/V2 with silhouettes of human and monkey face profiles and “nonsense” silhouettes constructed by mirror-reversing the front part of the profile. We found no superiority of face silhouettes compared with nonsense shapes in eliciting border-ownership signals overall. However, in some neurons, border-ownership signals differed strongly between the two categories consistently across many different profile shapes. Surprisingly, this category selectivity appeared as early as 70 ms after stimulus onset, which is earlier than the typical latency of shape-selective responses but compatible with the earliest face-selective responses in the inferior temporal lobe. A...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="4b5b8187d56d4cc4860ce8a86f27ca39" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":83404935,"asset_id":75763339,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/83404935/download_file?st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75763339"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75763339"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75763339; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75763339]").text(description); $(".js-view-count[data-work-id=75763339]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75763339; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75763339']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 75763339, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "4b5b8187d56d4cc4860ce8a86f27ca39" } } $('.js-work-strip[data-work-id=75763339]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75763339,"title":"Figure-ground organization in the visual cortex: does meaning matter?","translated_title":"","metadata":{"abstract":"Figure-ground organization in the visual cortex is generally assumed to be based partly on general rules and partly on specific influences of object recognition in higher centers as found in the temporal lobe. To see if shape familiarity influences figure-ground organization, we tested border ownership-selective neurons in monkey V1/V2 with silhouettes of human and monkey face profiles and “nonsense” silhouettes constructed by mirror-reversing the front part of the profile. We found no superiority of face silhouettes compared with nonsense shapes in eliciting border-ownership signals overall. However, in some neurons, border-ownership signals differed strongly between the two categories consistently across many different profile shapes. Surprisingly, this category selectivity appeared as early as 70 ms after stimulus onset, which is earlier than the typical latency of shape-selective responses but compatible with the earliest face-selective responses in the inferior temporal lobe. A...","publisher":"American Physiological Society","publication_date":{"day":null,"month":null,"year":2018,"errors":{}},"publication_name":"Journal of Neurophysiology"},"translated_abstract":"Figure-ground organization in the visual cortex is generally assumed to be based partly on general rules and partly on specific influences of object recognition in higher centers as found in the temporal lobe. To see if shape familiarity influences figure-ground organization, we tested border ownership-selective neurons in monkey V1/V2 with silhouettes of human and monkey face profiles and “nonsense” silhouettes constructed by mirror-reversing the front part of the profile. We found no superiority of face silhouettes compared with nonsense shapes in eliciting border-ownership signals overall. However, in some neurons, border-ownership signals differed strongly between the two categories consistently across many different profile shapes. Surprisingly, this category selectivity appeared as early as 70 ms after stimulus onset, which is earlier than the typical latency of shape-selective responses but compatible with the earliest face-selective responses in the inferior temporal lobe. A...","internal_url":"https://www.academia.edu/75763339/Figure_ground_organization_in_the_visual_cortex_does_meaning_matter","translated_internal_url":"","created_at":"2022-04-07T17:07:00.197-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":83404935,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/83404935/thumbnails/1.jpg","file_name":"jn.00131.pdf","download_url":"https://www.academia.edu/attachments/83404935/download_file?st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Figure_ground_organization_in_the_visual.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/83404935/jn.00131-libre.pdf?1649377056=\u0026response-content-disposition=attachment%3B+filename%3DFigure_ground_organization_in_the_visual.pdf\u0026Expires=1732785277\u0026Signature=ObJj27O~XSVHA5ou4MicuKL6P4bnyeUVA3l5h16JKJ5QB9ttySqfy-BlImWs3XT3xBIKmQZyBPOUl0WOj5gPlrWdeGQOWe5AWygRaPKKRlskQXZOiRNfSP9~RkfAgiNH51pCGAwjxdUncuek8PflzLfk2lhavh9~GMi77TyslVOztD4TKVFZF6Co58G70V6gZKFiJFB-eQs-rBpCxi5ob4tz0Az1p4JQg5TnFMojXKlx8mk21HOZlI8Rmc~c54~MmzHXbn0en~NEhglCzbVXE0tLugBar16hSP7WpelWtItLLn~LmAjmRsxcTIWb1wNYXpwqSkJF4-jKiX~mYZKvAg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Figure_ground_organization_in_the_visual_cortex_does_meaning_matter","translated_slug":"","page_count":17,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[{"id":83404935,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/83404935/thumbnails/1.jpg","file_name":"jn.00131.pdf","download_url":"https://www.academia.edu/attachments/83404935/download_file?st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Figure_ground_organization_in_the_visual.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/83404935/jn.00131-libre.pdf?1649377056=\u0026response-content-disposition=attachment%3B+filename%3DFigure_ground_organization_in_the_visual.pdf\u0026Expires=1732785277\u0026Signature=ObJj27O~XSVHA5ou4MicuKL6P4bnyeUVA3l5h16JKJ5QB9ttySqfy-BlImWs3XT3xBIKmQZyBPOUl0WOj5gPlrWdeGQOWe5AWygRaPKKRlskQXZOiRNfSP9~RkfAgiNH51pCGAwjxdUncuek8PflzLfk2lhavh9~GMi77TyslVOztD4TKVFZF6Co58G70V6gZKFiJFB-eQs-rBpCxi5ob4tz0Az1p4JQg5TnFMojXKlx8mk21HOZlI8Rmc~c54~MmzHXbn0en~NEhglCzbVXE0tLugBar16hSP7WpelWtItLLn~LmAjmRsxcTIWb1wNYXpwqSkJF4-jKiX~mYZKvAg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":221,"name":"Psychology","url":"https://www.academia.edu/Documents/in/Psychology"},{"id":22272,"name":"Neurophysiology","url":"https://www.academia.edu/Documents/in/Neurophysiology"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":2922956,"name":"Psychology and Cognitive Sciences","url":"https://www.academia.edu/Documents/in/Psychology_and_Cognitive_Sciences"},{"id":3763225,"name":"Medical and Health Sciences","url":"https://www.academia.edu/Documents/in/Medical_and_Health_Sciences"}],"urls":[{"id":19232102,"url":"http://www.physiology.org/doi/pdf/10.1152/jn.00131.2017"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="75763333"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/75763333/Figure_ground_organization_and_the_emergence_of_proto_objects_in_the_visual_cortex"><img alt="Research paper thumbnail of Figure–ground organization and the emergence of proto-objects in the visual cortex" class="work-thumbnail" src="https://attachments.academia-assets.com/83404929/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/75763333/Figure_ground_organization_and_the_emergence_of_proto_objects_in_the_visual_cortex">Figure–ground organization and the emergence of proto-objects in the visual cortex</a></div><div class="wp-workCard_item"><span>Frontiers in Psychology</span><span>, 2015</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="9d7aa9bdc950e2ea102ae660ee9bf26d" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":83404929,"asset_id":75763333,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/83404929/download_file?st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75763333"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75763333"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75763333; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75763333]").text(description); $(".js-view-count[data-work-id=75763333]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75763333; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75763333']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 75763333, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "9d7aa9bdc950e2ea102ae660ee9bf26d" } } $('.js-work-strip[data-work-id=75763333]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75763333,"title":"Figure–ground organization and the emergence of proto-objects in the visual cortex","translated_title":"","metadata":{"publisher":"Frontiers Media SA","publication_date":{"day":null,"month":null,"year":2015,"errors":{}},"publication_name":"Frontiers in Psychology"},"translated_abstract":null,"internal_url":"https://www.academia.edu/75763333/Figure_ground_organization_and_the_emergence_of_proto_objects_in_the_visual_cortex","translated_internal_url":"","created_at":"2022-04-07T17:06:25.519-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":83404929,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/83404929/thumbnails/1.jpg","file_name":"pmc4630502.pdf","download_url":"https://www.academia.edu/attachments/83404929/download_file?st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Figure_ground_organization_and_the_emerg.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/83404929/pmc4630502-libre.pdf?1649377058=\u0026response-content-disposition=attachment%3B+filename%3DFigure_ground_organization_and_the_emerg.pdf\u0026Expires=1732785277\u0026Signature=bTsX8TO27MM3BlTiHzJxYwb8tGJNIaMP4xoimoa8yDamz8Ins4yujzHBoGkaHL5h-KFmqlaENND5Bj2MvIK5SdNnwqKYj9F3zNQLpPD-Um5CZ6DB2PCAflNgBTAJetEt6jPYTkN9DG6HOtutJPq5kiurnvDDRKCMBZPyRjk6donG7RQ3ebtdjbqmPXtGeeLl7jl9Kzpeys~tTNvmy5Ue0QFMjvF10dO60gru9AOf2TDv99OCdJypg2lr7D0dwIw1pOGcwKRacpmh4sYq~f1rmhcCRt13KVXDPljyUdPZ15cnEvvWuBJUjkXCRVrb2g3QdDYVL5IczpR3NPaWN6UILg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Figure_ground_organization_and_the_emergence_of_proto_objects_in_the_visual_cortex","translated_slug":"","page_count":10,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[{"id":83404929,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/83404929/thumbnails/1.jpg","file_name":"pmc4630502.pdf","download_url":"https://www.academia.edu/attachments/83404929/download_file?st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Figure_ground_organization_and_the_emerg.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/83404929/pmc4630502-libre.pdf?1649377058=\u0026response-content-disposition=attachment%3B+filename%3DFigure_ground_organization_and_the_emerg.pdf\u0026Expires=1732785277\u0026Signature=bTsX8TO27MM3BlTiHzJxYwb8tGJNIaMP4xoimoa8yDamz8Ins4yujzHBoGkaHL5h-KFmqlaENND5Bj2MvIK5SdNnwqKYj9F3zNQLpPD-Um5CZ6DB2PCAflNgBTAJetEt6jPYTkN9DG6HOtutJPq5kiurnvDDRKCMBZPyRjk6donG7RQ3ebtdjbqmPXtGeeLl7jl9Kzpeys~tTNvmy5Ue0QFMjvF10dO60gru9AOf2TDv99OCdJypg2lr7D0dwIw1pOGcwKRacpmh4sYq~f1rmhcCRt13KVXDPljyUdPZ15cnEvvWuBJUjkXCRVrb2g3QdDYVL5IczpR3NPaWN6UILg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":221,"name":"Psychology","url":"https://www.academia.edu/Documents/in/Psychology"},{"id":2498386,"name":"Frontiers in Psychology","url":"https://www.academia.edu/Documents/in/Frontiers_in_Psychology"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="63017526"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/63017526/Visual_selectivity_and_top_down_modulation_of_neurons_in_monkey_V2_during_free_viewing"><img alt="Research paper thumbnail of Visual selectivity and top-down modulation of neurons in monkey V2 during free viewing" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/63017526/Visual_selectivity_and_top_down_modulation_of_neurons_in_monkey_V2_during_free_viewing">Visual selectivity and top-down modulation of neurons in monkey V2 during free viewing</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Neurons in early visual cortex are selective for local visual features but their responses can al...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Neurons in early visual cortex are selective for local visual features but their responses can also be influenced by factors like border ownership and selective attention. Most of what we know about the function of these neurons is based on neurophysiological studies in monkeys that hold their direction of gaze fixed while isolated visual stimuli are presented (controlled viewing). However, during natural behavior, primates visually explore cluttered environments by changing gaze direction several times each second (free viewing). How does the visual cortex work under these conditions? We explored neuronal responses using a foraging task in which the monkey chooses where to look and when. Geometrical figures were displayed and the monkey was rewarded for fixating the center of a figure for at least 200ms. In each trial an array of 10 figures (5 squares and 5 triangles) was presented, one of which was randomly associated with reward, and a cue informed the monkey whether it was a squ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="63017526"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="63017526"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 63017526; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=63017526]").text(description); $(".js-view-count[data-work-id=63017526]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 63017526; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='63017526']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 63017526, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=63017526]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":63017526,"title":"Visual selectivity and top-down modulation of neurons in monkey V2 during free viewing","translated_title":"","metadata":{"abstract":"Neurons in early visual cortex are selective for local visual features but their responses can also be influenced by factors like border ownership and selective attention. Most of what we know about the function of these neurons is based on neurophysiological studies in monkeys that hold their direction of gaze fixed while isolated visual stimuli are presented (controlled viewing). However, during natural behavior, primates visually explore cluttered environments by changing gaze direction several times each second (free viewing). How does the visual cortex work under these conditions? We explored neuronal responses using a foraging task in which the monkey chooses where to look and when. Geometrical figures were displayed and the monkey was rewarded for fixating the center of a figure for at least 200ms. In each trial an array of 10 figures (5 squares and 5 triangles) was presented, one of which was randomly associated with reward, and a cue informed the monkey whether it was a squ...","publisher":"Journal of vision","publication_date":{"day":null,"month":null,"year":2015,"errors":{}}},"translated_abstract":"Neurons in early visual cortex are selective for local visual features but their responses can also be influenced by factors like border ownership and selective attention. Most of what we know about the function of these neurons is based on neurophysiological studies in monkeys that hold their direction of gaze fixed while isolated visual stimuli are presented (controlled viewing). However, during natural behavior, primates visually explore cluttered environments by changing gaze direction several times each second (free viewing). How does the visual cortex work under these conditions? We explored neuronal responses using a foraging task in which the monkey chooses where to look and when. Geometrical figures were displayed and the monkey was rewarded for fixating the center of a figure for at least 200ms. In each trial an array of 10 figures (5 squares and 5 triangles) was presented, one of which was randomly associated with reward, and a cue informed the monkey whether it was a squ...","internal_url":"https://www.academia.edu/63017526/Visual_selectivity_and_top_down_modulation_of_neurons_in_monkey_V2_during_free_viewing","translated_internal_url":"","created_at":"2021-12-02T12:40:45.101-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Visual_selectivity_and_top_down_modulation_of_neurons_in_monkey_V2_during_free_viewing","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[],"research_interests":[{"id":59692,"name":"Vision","url":"https://www.academia.edu/Documents/in/Vision"},{"id":2922956,"name":"Psychology and Cognitive Sciences","url":"https://www.academia.edu/Documents/in/Psychology_and_Cognitive_Sciences"},{"id":3763225,"name":"Medical and Health Sciences","url":"https://www.academia.edu/Documents/in/Medical_and_Health_Sciences"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="63017525"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/63017525/The_speed_of_context_integration_in_the_visual_cortex"><img alt="Research paper thumbnail of The speed of context integration in the visual cortex" class="work-thumbnail" src="https://attachments.academia-assets.com/75586454/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/63017525/The_speed_of_context_integration_in_the_visual_cortex">The speed of context integration in the visual cortex</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The observation of figure-ground selectivity in neurons of the visual cortex shows that these neu...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The observation of figure-ground selectivity in neurons of the visual cortex shows that these neurons can be influenced by the image context far beyond the classical receptive field. To clarify the nature of the context integration mechanism, we studied the latencies of neural edge signals, comparing the emergence of context-dependent definition of border ownership with the onset of local edge definition (contrast polarity; stereoscopic depth order). Single-neuron activity was recorded in areas V1 and V2 of Macaca mulatta under behaviorally induced fixation. Whereas local edge definition emerged immediately (&lt;13 ms) after the edge onset response, the context-dependent signal was delayed by about 30 ms. To see if the context influence was mediated by horizontal fibers within cortex, we measured the latencies of border ownership signals for two conditions in which the relevant context information was located at different distances from the receptive field and compared the latency d...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="2a11512624e32cefeed45f88c79d40dd" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":75586454,"asset_id":63017525,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/75586454/download_file?st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="63017525"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="63017525"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 63017525; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=63017525]").text(description); $(".js-view-count[data-work-id=63017525]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 63017525; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='63017525']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 63017525, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "2a11512624e32cefeed45f88c79d40dd" } } $('.js-work-strip[data-work-id=63017525]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":63017525,"title":"The speed of context integration in the visual cortex","translated_title":"","metadata":{"abstract":"The observation of figure-ground selectivity in neurons of the visual cortex shows that these neurons can be influenced by the image context far beyond the classical receptive field. To clarify the nature of the context integration mechanism, we studied the latencies of neural edge signals, comparing the emergence of context-dependent definition of border ownership with the onset of local edge definition (contrast polarity; stereoscopic depth order). Single-neuron activity was recorded in areas V1 and V2 of Macaca mulatta under behaviorally induced fixation. Whereas local edge definition emerged immediately (\u0026lt;13 ms) after the edge onset response, the context-dependent signal was delayed by about 30 ms. To see if the context influence was mediated by horizontal fibers within cortex, we measured the latencies of border ownership signals for two conditions in which the relevant context information was located at different distances from the receptive field and compared the latency d...","publisher":"Journal of neurophysiology","publication_date":{"day":null,"month":null,"year":2011,"errors":{}}},"translated_abstract":"The observation of figure-ground selectivity in neurons of the visual cortex shows that these neurons can be influenced by the image context far beyond the classical receptive field. To clarify the nature of the context integration mechanism, we studied the latencies of neural edge signals, comparing the emergence of context-dependent definition of border ownership with the onset of local edge definition (contrast polarity; stereoscopic depth order). Single-neuron activity was recorded in areas V1 and V2 of Macaca mulatta under behaviorally induced fixation. Whereas local edge definition emerged immediately (\u0026lt;13 ms) after the edge onset response, the context-dependent signal was delayed by about 30 ms. To see if the context influence was mediated by horizontal fibers within cortex, we measured the latencies of border ownership signals for two conditions in which the relevant context information was located at different distances from the receptive field and compared the latency d...","internal_url":"https://www.academia.edu/63017525/The_speed_of_context_integration_in_the_visual_cortex","translated_internal_url":"","created_at":"2021-12-02T12:40:44.875-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":75586454,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/75586454/thumbnails/1.jpg","file_name":"374.full.pdf","download_url":"https://www.academia.edu/attachments/75586454/download_file?st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"The_speed_of_context_integration_in_the.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/75586454/374.full-libre.pdf?1638479538=\u0026response-content-disposition=attachment%3B+filename%3DThe_speed_of_context_integration_in_the.pdf\u0026Expires=1732785277\u0026Signature=OrRDWHTGomBUI0wmYcgXD4EcrHsWzepglO6bpW0eT0QScn96RsE1GhmF4PJcSAqFJTzWtQ8-v39XY0WrYXY428ziIVe302r1iqJ50f88plc1qNdkdyuiLaLfx5mbbeQ8AqDA17sBcZIYg2k~LRY6yK-STLPlrWvhvZMXth6yEBiefrHToIbTamdE~LFl8YrhbR1BFUA1M528LJYwi28Ppvv1JEwDkIPqyGi0JAD1WXgJmEx4fzr-t8RnhFznawEKgy9mPNID~76aa~ua1VizxL2PVy2K2sn0utSHAio-rvzKggzyICM6ueJbGVXJAKt~aFF6sc3xuWPXhUuzYvEU8g__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"The_speed_of_context_integration_in_the_visual_cortex","translated_slug":"","page_count":12,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[{"id":75586454,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/75586454/thumbnails/1.jpg","file_name":"374.full.pdf","download_url":"https://www.academia.edu/attachments/75586454/download_file?st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"The_speed_of_context_integration_in_the.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/75586454/374.full-libre.pdf?1638479538=\u0026response-content-disposition=attachment%3B+filename%3DThe_speed_of_context_integration_in_the.pdf\u0026Expires=1732785277\u0026Signature=OrRDWHTGomBUI0wmYcgXD4EcrHsWzepglO6bpW0eT0QScn96RsE1GhmF4PJcSAqFJTzWtQ8-v39XY0WrYXY428ziIVe302r1iqJ50f88plc1qNdkdyuiLaLfx5mbbeQ8AqDA17sBcZIYg2k~LRY6yK-STLPlrWvhvZMXth6yEBiefrHToIbTamdE~LFl8YrhbR1BFUA1M528LJYwi28Ppvv1JEwDkIPqyGi0JAD1WXgJmEx4fzr-t8RnhFznawEKgy9mPNID~76aa~ua1VizxL2PVy2K2sn0utSHAio-rvzKggzyICM6ueJbGVXJAKt~aFF6sc3xuWPXhUuzYvEU8g__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"},{"id":75586453,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/75586453/thumbnails/1.jpg","file_name":"374.full.pdf","download_url":"https://www.academia.edu/attachments/75586453/download_file","bulk_download_file_name":"The_speed_of_context_integration_in_the.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/75586453/374.full-libre.pdf?1638479538=\u0026response-content-disposition=attachment%3B+filename%3DThe_speed_of_context_integration_in_the.pdf\u0026Expires=1732785277\u0026Signature=JH7KU~M4Ic5Wl7bXmYFkzVuJp1tKbbpHhWVl~YBJHQT-XHrdCKUVqHL~VlStau1itrd1xoS4DvI7lI4gKq58X1GJA6UiJBadhyq5gsQKQqSQ-nf-jFkaolwjJ5LY8yeyAIGqgHfTKI-5p-6ufqfxLFmkBokxPrtUFItYYn5WCrqjw-yCPhy5oykLG6EEu6eqqJrJSbkYDVJCnH5rBcWmM6JNUccyzp0N9R14GyymKCPu~we8nNV~7KUqV40Rx0hTPZtLmuuxLxuRgID4AwowsqyxwzjP0xmvTweksYdWrBslNSkidLHRPC85p00FrUvQNWHL9iaK34505Rj6KZYqfw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":22272,"name":"Neurophysiology","url":"https://www.academia.edu/Documents/in/Neurophysiology"},{"id":49962,"name":"Visual Cortex","url":"https://www.academia.edu/Documents/in/Visual_Cortex"},{"id":52176,"name":"Brain Mapping","url":"https://www.academia.edu/Documents/in/Brain_Mapping"},{"id":193974,"name":"Neurons","url":"https://www.academia.edu/Documents/in/Neurons"},{"id":573267,"name":"Macaca Mulatta","url":"https://www.academia.edu/Documents/in/Macaca_Mulatta"},{"id":2922956,"name":"Psychology and Cognitive Sciences","url":"https://www.academia.edu/Documents/in/Psychology_and_Cognitive_Sciences"},{"id":3763225,"name":"Medical and Health Sciences","url":"https://www.academia.edu/Documents/in/Medical_and_Health_Sciences"}],"urls":[{"id":14713534,"url":"http://jn.physiology.org/content/jn/106/1/374.full.pdf"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="63017509"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/63017509/Image_Parsing_Mechanisms_of_the_Visual_Cortex"><img alt="Research paper thumbnail of Image Parsing Mechanisms of the Visual Cortex" class="work-thumbnail" src="https://attachments.academia-assets.com/75586503/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/63017509/Image_Parsing_Mechanisms_of_the_Visual_Cortex">Image Parsing Mechanisms of the Visual Cortex</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">In this chapter I will discuss visual processes that are often labeled as &quot; intermediate lev...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">In this chapter I will discuss visual processes that are often labeled as &quot; intermediate level vision &quot;. As a useful framework we consider vision as a sequence of processes each of which is a mapping from one representation to another. Understanding vision then means analyzing how information is represented at each stage and how it is transformed between stages (Marr, 1982). It is clear that the first stage, the level of the photoreceptors, is an image representation. This is a 2-dimensional array of color values, resembling the bitmap format of digital computers. Retinal processes transform this representation into a format that is suitable for transmission through the optic nerve to central brain structures. A radical transformation then takes place in the primary visual cortex. At the output of area V1 we find visual information encoded as a &quot; feature map &quot; , a representation of local features. The two dimensions of retinal position are encoded in the location...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="c5f72e0593ff0bdf9b22eac36d2b4bf6" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":75586503,"asset_id":63017509,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/75586503/download_file?st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="63017509"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="63017509"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 63017509; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=63017509]").text(description); $(".js-view-count[data-work-id=63017509]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 63017509; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='63017509']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 63017509, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "c5f72e0593ff0bdf9b22eac36d2b4bf6" } } $('.js-work-strip[data-work-id=63017509]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":63017509,"title":"Image Parsing Mechanisms of the Visual Cortex","translated_title":"","metadata":{"abstract":"In this chapter I will discuss visual processes that are often labeled as \u0026quot; intermediate level vision \u0026quot;. As a useful framework we consider vision as a sequence of processes each of which is a mapping from one representation to another. Understanding vision then means analyzing how information is represented at each stage and how it is transformed between stages (Marr, 1982). It is clear that the first stage, the level of the photoreceptors, is an image representation. This is a 2-dimensional array of color values, resembling the bitmap format of digital computers. Retinal processes transform this representation into a format that is suitable for transmission through the optic nerve to central brain structures. A radical transformation then takes place in the primary visual cortex. At the output of area V1 we find visual information encoded as a \u0026quot; feature map \u0026quot; , a representation of local features. The two dimensions of retinal position are encoded in the location...","publication_date":{"day":null,"month":null,"year":2002,"errors":{}}},"translated_abstract":"In this chapter I will discuss visual processes that are often labeled as \u0026quot; intermediate level vision \u0026quot;. As a useful framework we consider vision as a sequence of processes each of which is a mapping from one representation to another. Understanding vision then means analyzing how information is represented at each stage and how it is transformed between stages (Marr, 1982). It is clear that the first stage, the level of the photoreceptors, is an image representation. This is a 2-dimensional array of color values, resembling the bitmap format of digital computers. Retinal processes transform this representation into a format that is suitable for transmission through the optic nerve to central brain structures. A radical transformation then takes place in the primary visual cortex. At the output of area V1 we find visual information encoded as a \u0026quot; feature map \u0026quot; , a representation of local features. The two dimensions of retinal position are encoded in the location...","internal_url":"https://www.academia.edu/63017509/Image_Parsing_Mechanisms_of_the_Visual_Cortex","translated_internal_url":"","created_at":"2021-12-02T12:40:21.359-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":75586503,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/75586503/thumbnails/1.jpg","file_name":"vonderHeydt_2004.pdf","download_url":"https://www.academia.edu/attachments/75586503/download_file?st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Image_Parsing_Mechanisms_of_the_Visual_C.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/75586503/vonderHeydt_2004-libre.pdf?1638479536=\u0026response-content-disposition=attachment%3B+filename%3DImage_Parsing_Mechanisms_of_the_Visual_C.pdf\u0026Expires=1732785277\u0026Signature=b1OhZNJxcaRbYAI4x~tAqJQo2dwm90Hzm7cPxyxep0lIjAYAOpiK2VhwxTai~YPIZI5MDZrVFxsKId06TdWRKVJp74nUs3Vh-qGP3623n8u6CMAn7HOx-TCoMm4ZPHJ5LbtK8pqzsm~lBt301wPrPI1bx7ByrqhEMSq9deYX11OUF61bkwgRTukdB3cnvf6CdrOE-k50FH3x7mDWrbdqG~ZEDEg6wmhZmlMquZAMKiIkeWh6X2olO9k5raauSRlZwHKYYH-dUBOEBDty91GC5jxE~Rp-~Eeu-XicMtCyu7qc8DKC14TZ8cK~bpKtEvZibX0nROybXIrTqKL9o7u58Q__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Image_Parsing_Mechanisms_of_the_Visual_Cortex","translated_slug":"","page_count":25,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[{"id":75586503,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/75586503/thumbnails/1.jpg","file_name":"vonderHeydt_2004.pdf","download_url":"https://www.academia.edu/attachments/75586503/download_file?st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Image_Parsing_Mechanisms_of_the_Visual_C.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/75586503/vonderHeydt_2004-libre.pdf?1638479536=\u0026response-content-disposition=attachment%3B+filename%3DImage_Parsing_Mechanisms_of_the_Visual_C.pdf\u0026Expires=1732785277\u0026Signature=b1OhZNJxcaRbYAI4x~tAqJQo2dwm90Hzm7cPxyxep0lIjAYAOpiK2VhwxTai~YPIZI5MDZrVFxsKId06TdWRKVJp74nUs3Vh-qGP3623n8u6CMAn7HOx-TCoMm4ZPHJ5LbtK8pqzsm~lBt301wPrPI1bx7ByrqhEMSq9deYX11OUF61bkwgRTukdB3cnvf6CdrOE-k50FH3x7mDWrbdqG~ZEDEg6wmhZmlMquZAMKiIkeWh6X2olO9k5raauSRlZwHKYYH-dUBOEBDty91GC5jxE~Rp-~Eeu-XicMtCyu7qc8DKC14TZ8cK~bpKtEvZibX0nROybXIrTqKL9o7u58Q__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":49962,"name":"Visual Cortex","url":"https://www.academia.edu/Documents/in/Visual_Cortex"}],"urls":[{"id":14713528,"url":"http://www.stat.ucla.edu/~yuille/courses/Stat271-Fall13/VonderHeydt_ImageParsing_neuroscience.pdf"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="57633070"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/57633070/Representation_and_Remapping_of_Occluded_Objects_in_the_Activity_of_V4"><img alt="Research paper thumbnail of Representation and Remapping of Occluded Objects in the Activity of V4" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/57633070/Representation_and_Remapping_of_Occluded_Objects_in_the_Activity_of_V4">Representation and Remapping of Occluded Objects in the Activity of V4</a></div><div class="wp-workCard_item"><span>Journal of Vision</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="57633070"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="57633070"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 57633070; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=57633070]").text(description); $(".js-view-count[data-work-id=57633070]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 57633070; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='57633070']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 57633070, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=57633070]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":57633070,"title":"Representation and Remapping of Occluded Objects in the Activity of V4","translated_title":"","metadata":{"publisher":"Association for Research in Vision and Ophthalmology (ARVO)","publication_name":"Journal of Vision"},"translated_abstract":null,"internal_url":"https://www.academia.edu/57633070/Representation_and_Remapping_of_Occluded_Objects_in_the_Activity_of_V4","translated_internal_url":"","created_at":"2021-10-13T16:27:05.364-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Representation_and_Remapping_of_Occluded_Objects_in_the_Activity_of_V4","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[],"research_interests":[{"id":59692,"name":"Vision","url":"https://www.academia.edu/Documents/in/Vision"},{"id":2922956,"name":"Psychology and Cognitive Sciences","url":"https://www.academia.edu/Documents/in/Psychology_and_Cognitive_Sciences"},{"id":3763225,"name":"Medical and Health Sciences","url":"https://www.academia.edu/Documents/in/Medical_and_Health_Sciences"}],"urls":[{"id":12933319,"url":"http://jov.arvojournals.org/article.aspx?articleid=2700038"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="57633069"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/57633069/Figure_and_Ground_How_the_Visual_Cortex_Integrates_Local_Cues_for_Global_Organization"><img alt="Research paper thumbnail of Figure and Ground: How the Visual Cortex Integrates Local Cues for Global Organization" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/57633069/Figure_and_Ground_How_the_Visual_Cortex_Integrates_Local_Cues_for_Global_Organization">Figure and Ground: How the Visual Cortex Integrates Local Cues for Global Organization</a></div><div class="wp-workCard_item"><span>Journal of neurophysiology</span><span>, Jan 25, 2018</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Inferring figure-ground organization in 2-dimensional images may require different complementary ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Inferring figure-ground organization in 2-dimensional images may require different complementary strategies. For isolated objects it has been shown that mechanisms in visual cortex exploit the overall distribution of contours, but in images of cluttered scenes where the grouping of contours is not obvious that strategy would fail. However, natural scenes contain local features, specifically contour junctions, that may contribute to the definition of object regions. To study the role of local features in the assignment of border ownership we recorded single-cell activity from visual cortex in awake behaving Macaca mulatta. We tested configurations perceived as two overlapping figures in which T- and L-junctions depend on the direction of overlap, while the overall distribution of contours provides no valid information. While recording responses to the occluding contour we varied direction of overlap and variably masked some of the critical contour features to determine their influenc...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="57633069"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="57633069"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 57633069; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=57633069]").text(description); $(".js-view-count[data-work-id=57633069]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 57633069; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='57633069']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 57633069, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=57633069]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":57633069,"title":"Figure and Ground: How the Visual Cortex Integrates Local Cues for Global Organization","translated_title":"","metadata":{"abstract":"Inferring figure-ground organization in 2-dimensional images may require different complementary strategies. For isolated objects it has been shown that mechanisms in visual cortex exploit the overall distribution of contours, but in images of cluttered scenes where the grouping of contours is not obvious that strategy would fail. However, natural scenes contain local features, specifically contour junctions, that may contribute to the definition of object regions. To study the role of local features in the assignment of border ownership we recorded single-cell activity from visual cortex in awake behaving Macaca mulatta. We tested configurations perceived as two overlapping figures in which T- and L-junctions depend on the direction of overlap, while the overall distribution of contours provides no valid information. While recording responses to the occluding contour we varied direction of overlap and variably masked some of the critical contour features to determine their influenc...","publication_date":{"day":25,"month":1,"year":2018,"errors":{}},"publication_name":"Journal of neurophysiology"},"translated_abstract":"Inferring figure-ground organization in 2-dimensional images may require different complementary strategies. For isolated objects it has been shown that mechanisms in visual cortex exploit the overall distribution of contours, but in images of cluttered scenes where the grouping of contours is not obvious that strategy would fail. However, natural scenes contain local features, specifically contour junctions, that may contribute to the definition of object regions. To study the role of local features in the assignment of border ownership we recorded single-cell activity from visual cortex in awake behaving Macaca mulatta. We tested configurations perceived as two overlapping figures in which T- and L-junctions depend on the direction of overlap, while the overall distribution of contours provides no valid information. While recording responses to the occluding contour we varied direction of overlap and variably masked some of the critical contour features to determine their influenc...","internal_url":"https://www.academia.edu/57633069/Figure_and_Ground_How_the_Visual_Cortex_Integrates_Local_Cues_for_Global_Organization","translated_internal_url":"","created_at":"2021-10-13T16:27:05.294-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Figure_and_Ground_How_the_Visual_Cortex_Integrates_Local_Cues_for_Global_Organization","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[],"research_interests":[{"id":22272,"name":"Neurophysiology","url":"https://www.academia.edu/Documents/in/Neurophysiology"},{"id":2922956,"name":"Psychology and Cognitive Sciences","url":"https://www.academia.edu/Documents/in/Psychology_and_Cognitive_Sciences"},{"id":3763225,"name":"Medical and Health Sciences","url":"https://www.academia.edu/Documents/in/Medical_and_Health_Sciences"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="57633068"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/57633068/The_role_of_horizontal_connections_for_the_modulation_of_border_ownership_selective_neurons_in_visual_cortex"><img alt="Research paper thumbnail of The role of horizontal connections for the modulation of border-ownership selective neurons in visual cortex" class="work-thumbnail" src="https://attachments.academia-assets.com/72439280/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/57633068/The_role_of_horizontal_connections_for_the_modulation_of_border_ownership_selective_neurons_in_visual_cortex">The role of horizontal connections for the modulation of border-ownership selective neurons in visual cortex</a></div><div class="wp-workCard_item"><span>BMC Neuroscience</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="9628f259331ff0e42e8ab6196e3e7298" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":72439280,"asset_id":57633068,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/72439280/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="57633068"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="57633068"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 57633068; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=57633068]").text(description); $(".js-view-count[data-work-id=57633068]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 57633068; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='57633068']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 57633068, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "9628f259331ff0e42e8ab6196e3e7298" } } $('.js-work-strip[data-work-id=57633068]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":57633068,"title":"The role of horizontal connections for the modulation of border-ownership selective neurons in visual cortex","translated_title":"","metadata":{"publisher":"Springer Nature","publication_name":"BMC Neuroscience"},"translated_abstract":null,"internal_url":"https://www.academia.edu/57633068/The_role_of_horizontal_connections_for_the_modulation_of_border_ownership_selective_neurons_in_visual_cortex","translated_internal_url":"","created_at":"2021-10-13T16:27:05.215-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":72439280,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/72439280/thumbnails/1.jpg","file_name":"pmc4697632.pdf","download_url":"https://www.academia.edu/attachments/72439280/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"The_role_of_horizontal_connections_for_t.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/72439280/pmc4697632-libre.pdf?1634272357=\u0026response-content-disposition=attachment%3B+filename%3DThe_role_of_horizontal_connections_for_t.pdf\u0026Expires=1732785278\u0026Signature=J42zLPMtZhxDbFjl~173RHIllBCKcRq4pEAijrIpTUOIQYmQKGNlcMnE-bEpzS-RrrGadmGSQNX4t-r0eeKiHcRSFjn3dD2QWa76br2QdIgt5ugh0Hdyb5~hs~GIc4Hg69uCXFMAFS50Vzrvur6KEMfV7fodmUnOnLNfTo7150OaG9yyMnAaxEaiEuu8fxjEnGn3hHwtm~RsYBf8EKdHpf48A8HBvb2FgQ6H7gaKpAu2Lh4SsNs9e5FMBIvQXFRcxbE3eqUZd0zv8xeC5Fc7FLGIPsNn8DSugU6gcGVu1pWVNvg8MTwyCWxO0Jh39DqvvquKDY7lo4PmkP1-hysf~A__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"The_role_of_horizontal_connections_for_the_modulation_of_border_ownership_selective_neurons_in_visual_cortex","translated_slug":"","page_count":2,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[{"id":72439280,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/72439280/thumbnails/1.jpg","file_name":"pmc4697632.pdf","download_url":"https://www.academia.edu/attachments/72439280/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"The_role_of_horizontal_connections_for_t.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/72439280/pmc4697632-libre.pdf?1634272357=\u0026response-content-disposition=attachment%3B+filename%3DThe_role_of_horizontal_connections_for_t.pdf\u0026Expires=1732785278\u0026Signature=J42zLPMtZhxDbFjl~173RHIllBCKcRq4pEAijrIpTUOIQYmQKGNlcMnE-bEpzS-RrrGadmGSQNX4t-r0eeKiHcRSFjn3dD2QWa76br2QdIgt5ugh0Hdyb5~hs~GIc4Hg69uCXFMAFS50Vzrvur6KEMfV7fodmUnOnLNfTo7150OaG9yyMnAaxEaiEuu8fxjEnGn3hHwtm~RsYBf8EKdHpf48A8HBvb2FgQ6H7gaKpAu2Lh4SsNs9e5FMBIvQXFRcxbE3eqUZd0zv8xeC5Fc7FLGIPsNn8DSugU6gcGVu1pWVNvg8MTwyCWxO0Jh39DqvvquKDY7lo4PmkP1-hysf~A__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":237,"name":"Cognitive Science","url":"https://www.academia.edu/Documents/in/Cognitive_Science"},{"id":1239755,"name":"Neurosciences","url":"https://www.academia.edu/Documents/in/Neurosciences"},{"id":1681026,"name":"Biochemistry and cell biology","url":"https://www.academia.edu/Documents/in/Biochemistry_and_cell_biology"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="57633066"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/57633066/Can_the_visual_cortex_represent_the_invisible"><img alt="Research paper thumbnail of Can the visual cortex represent the invisible?" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/57633066/Can_the_visual_cortex_represent_the_invisible">Can the visual cortex represent the invisible?</a></div><div class="wp-workCard_item"><span>Journal of Vision</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="57633066"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="57633066"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 57633066; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=57633066]").text(description); $(".js-view-count[data-work-id=57633066]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 57633066; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='57633066']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 57633066, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=57633066]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":57633066,"title":"Can the visual cortex represent the invisible?","translated_title":"","metadata":{"publisher":"Association for Research in Vision and Ophthalmology (ARVO)","publication_name":"Journal of Vision"},"translated_abstract":null,"internal_url":"https://www.academia.edu/57633066/Can_the_visual_cortex_represent_the_invisible","translated_internal_url":"","created_at":"2021-10-13T16:27:05.100-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Can_the_visual_cortex_represent_the_invisible","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[],"research_interests":[{"id":59692,"name":"Vision","url":"https://www.academia.edu/Documents/in/Vision"},{"id":2922956,"name":"Psychology and Cognitive Sciences","url":"https://www.academia.edu/Documents/in/Psychology_and_Cognitive_Sciences"},{"id":3763225,"name":"Medical and Health Sciences","url":"https://www.academia.edu/Documents/in/Medical_and_Health_Sciences"}],"urls":[{"id":12933317,"url":"http://jov.arvojournals.org/article.aspx?doi=10.1167/17.10.348"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="57633065"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/57633065/Selectivity_for_structural_depth_in_neurons_of_monkey_area_V2"><img alt="Research paper thumbnail of Selectivity for structural depth in neurons of monkey area V2" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/57633065/Selectivity_for_structural_depth_in_neurons_of_monkey_area_V2">Selectivity for structural depth in neurons of monkey area V2</a></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="57633065"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="57633065"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 57633065; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=57633065]").text(description); $(".js-view-count[data-work-id=57633065]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 57633065; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='57633065']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 57633065, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=57633065]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":57633065,"title":"Selectivity for structural depth in neurons of monkey area V2","translated_title":"","metadata":{"publication_date":{"day":null,"month":null,"year":2000,"errors":{}}},"translated_abstract":null,"internal_url":"https://www.academia.edu/57633065/Selectivity_for_structural_depth_in_neurons_of_monkey_area_V2","translated_internal_url":"","created_at":"2021-10-13T16:27:05.009-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Selectivity_for_structural_depth_in_neurons_of_monkey_area_V2","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[],"research_interests":[],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="57633064"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/57633064/Detektion_von_ein_und_zwei_dimensionalen_Bildstrukturen_in_komplexen_Grauwertbildern"><img alt="Research paper thumbnail of Detektion von ein- und zwei-dimensionalen Bildstrukturen in komplexen Grauwertbildern" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/57633064/Detektion_von_ein_und_zwei_dimensionalen_Bildstrukturen_in_komplexen_Grauwertbildern">Detektion von ein- und zwei-dimensionalen Bildstrukturen in komplexen Grauwertbildern</a></div><div class="wp-workCard_item"><span>DAGM Symposium Symposium for Pattern Recognition</span><span>, 1992</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="57633064"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="57633064"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 57633064; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=57633064]").text(description); $(".js-view-count[data-work-id=57633064]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 57633064; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='57633064']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 57633064, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=57633064]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":57633064,"title":"Detektion von ein- und zwei-dimensionalen Bildstrukturen in komplexen Grauwertbildern","translated_title":"","metadata":{"publication_date":{"day":null,"month":null,"year":1992,"errors":{}},"publication_name":"DAGM Symposium Symposium for Pattern Recognition"},"translated_abstract":null,"internal_url":"https://www.academia.edu/57633064/Detektion_von_ein_und_zwei_dimensionalen_Bildstrukturen_in_komplexen_Grauwertbildern","translated_internal_url":"","created_at":"2021-10-13T16:27:04.904-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Detektion_von_ein_und_zwei_dimensionalen_Bildstrukturen_in_komplexen_Grauwertbildern","translated_slug":"","page_count":null,"language":"de","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[],"research_interests":[],"urls":[{"id":12933316,"url":"http://www.informatik.uni-trier.de/~ley/db/conf/dagm/dagm1992.html#RosenthalerHKH92"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="57633063"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/57633063/Mechanism_of_contours_in_monkey_visual_cortex_I_Lines_of_pattern_discontinuity"><img alt="Research paper thumbnail of Mechanism of contours in monkey visual cortex. I. Lines of pattern discontinuity" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/57633063/Mechanism_of_contours_in_monkey_visual_cortex_I_Lines_of_pattern_discontinuity">Mechanism of contours in monkey visual cortex. I. Lines of pattern discontinuity</a></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="57633063"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="57633063"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 57633063; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=57633063]").text(description); $(".js-view-count[data-work-id=57633063]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 57633063; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='57633063']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 57633063, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=57633063]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":57633063,"title":"Mechanism of contours in monkey visual cortex. I. Lines of pattern discontinuity","translated_title":"","metadata":{"publication_date":{"day":null,"month":null,"year":1989,"errors":{}}},"translated_abstract":null,"internal_url":"https://www.academia.edu/57633063/Mechanism_of_contours_in_monkey_visual_cortex_I_Lines_of_pattern_discontinuity","translated_internal_url":"","created_at":"2021-10-13T16:27:04.841-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Mechanism_of_contours_in_monkey_visual_cortex_I_Lines_of_pattern_discontinuity","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[],"research_interests":[],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="57633062"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/57633062/Visual_selectivity_and_top_down_modulation_of_neurons_in_monkey_V2_during_free_viewing"><img alt="Research paper thumbnail of Visual selectivity and top-down modulation of neurons in monkey V2 during free viewing" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/57633062/Visual_selectivity_and_top_down_modulation_of_neurons_in_monkey_V2_during_free_viewing">Visual selectivity and top-down modulation of neurons in monkey V2 during free viewing</a></div><div class="wp-workCard_item"><span>Journal of vision</span><span>, 2015</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Neurons in early visual cortex are selective for local visual features but their responses can al...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Neurons in early visual cortex are selective for local visual features but their responses can also be influenced by factors like border ownership and selective attention. Most of what we know about the function of these neurons is based on neurophysiological studies in monkeys that hold their direction of gaze fixed while isolated visual stimuli are presented (controlled viewing). However, during natural behavior, primates visually explore cluttered environments by changing gaze direction several times each second (free viewing). How does the visual cortex work under these conditions? We explored neuronal responses using a foraging task in which the monkey chooses where to look and when. Geometrical figures were displayed and the monkey was rewarded for fixating the center of a figure for at least 200ms. In each trial an array of 10 figures (5 squares and 5 triangles) was presented, one of which was randomly associated with reward, and a cue informed the monkey whether it was a squ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="57633062"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="57633062"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 57633062; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=57633062]").text(description); $(".js-view-count[data-work-id=57633062]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 57633062; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='57633062']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 57633062, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=57633062]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":57633062,"title":"Visual selectivity and top-down modulation of neurons in monkey V2 during free viewing","translated_title":"","metadata":{"abstract":"Neurons in early visual cortex are selective for local visual features but their responses can also be influenced by factors like border ownership and selective attention. Most of what we know about the function of these neurons is based on neurophysiological studies in monkeys that hold their direction of gaze fixed while isolated visual stimuli are presented (controlled viewing). However, during natural behavior, primates visually explore cluttered environments by changing gaze direction several times each second (free viewing). How does the visual cortex work under these conditions? We explored neuronal responses using a foraging task in which the monkey chooses where to look and when. Geometrical figures were displayed and the monkey was rewarded for fixating the center of a figure for at least 200ms. In each trial an array of 10 figures (5 squares and 5 triangles) was presented, one of which was randomly associated with reward, and a cue informed the monkey whether it was a squ...","publication_date":{"day":null,"month":null,"year":2015,"errors":{}},"publication_name":"Journal of vision"},"translated_abstract":"Neurons in early visual cortex are selective for local visual features but their responses can also be influenced by factors like border ownership and selective attention. Most of what we know about the function of these neurons is based on neurophysiological studies in monkeys that hold their direction of gaze fixed while isolated visual stimuli are presented (controlled viewing). However, during natural behavior, primates visually explore cluttered environments by changing gaze direction several times each second (free viewing). How does the visual cortex work under these conditions? We explored neuronal responses using a foraging task in which the monkey chooses where to look and when. Geometrical figures were displayed and the monkey was rewarded for fixating the center of a figure for at least 200ms. In each trial an array of 10 figures (5 squares and 5 triangles) was presented, one of which was randomly associated with reward, and a cue informed the monkey whether it was a squ...","internal_url":"https://www.academia.edu/57633062/Visual_selectivity_and_top_down_modulation_of_neurons_in_monkey_V2_during_free_viewing","translated_internal_url":"","created_at":"2021-10-13T16:27:04.761-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Visual_selectivity_and_top_down_modulation_of_neurons_in_monkey_V2_during_free_viewing","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[],"research_interests":[{"id":59692,"name":"Vision","url":"https://www.academia.edu/Documents/in/Vision"},{"id":2922956,"name":"Psychology and Cognitive Sciences","url":"https://www.academia.edu/Documents/in/Psychology_and_Cognitive_Sciences"},{"id":3763225,"name":"Medical and Health Sciences","url":"https://www.academia.edu/Documents/in/Medical_and_Health_Sciences"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="57633061"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/57633061/Spike_synchrony_reveals_emergence_of_proto_objects_in_visual_cortex"><img alt="Research paper thumbnail of Spike synchrony reveals emergence of proto-objects in visual cortex" class="work-thumbnail" src="https://attachments.academia-assets.com/72439287/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/57633061/Spike_synchrony_reveals_emergence_of_proto_objects_in_visual_cortex">Spike synchrony reveals emergence of proto-objects in visual cortex</a></div><div class="wp-workCard_item"><span>The Journal of neuroscience : the official journal of the Society for Neuroscience</span><span>, Jan 29, 2015</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Neurons at early stages of the visual cortex signal elemental features, such as pieces of contour...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Neurons at early stages of the visual cortex signal elemental features, such as pieces of contour, but how these signals are organized into perceptual objects is unclear. Theories have proposed that spiking synchrony between these neurons encodes how features are grouped (binding-by-synchrony), but recent studies did not find the predicted increase in synchrony with binding. Here we propose that features are grouped to &quot;proto-objects&quot; by intrinsic feedback circuits that enhance the responses of the participating feature neurons. This hypothesis predicts synchrony exclusively between feature neurons that receive feedback from the same grouping circuit. We recorded from neurons in macaque visual cortex and used border-ownership selectivity, an intrinsic property of the neurons, to infer whether or not two neurons are part of the same grouping circuit. We found that binding produced synchrony between same-circuit neurons, but not between other pairs of neurons, as predicted b...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="669d1a19faba2fbaecb8e1c0cd5286c1" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":72439287,"asset_id":57633061,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/72439287/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="57633061"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="57633061"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 57633061; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=57633061]").text(description); $(".js-view-count[data-work-id=57633061]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 57633061; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='57633061']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 57633061, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "669d1a19faba2fbaecb8e1c0cd5286c1" } } $('.js-work-strip[data-work-id=57633061]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":57633061,"title":"Spike synchrony reveals emergence of proto-objects in visual cortex","translated_title":"","metadata":{"abstract":"Neurons at early stages of the visual cortex signal elemental features, such as pieces of contour, but how these signals are organized into perceptual objects is unclear. Theories have proposed that spiking synchrony between these neurons encodes how features are grouped (binding-by-synchrony), but recent studies did not find the predicted increase in synchrony with binding. Here we propose that features are grouped to \u0026quot;proto-objects\u0026quot; by intrinsic feedback circuits that enhance the responses of the participating feature neurons. This hypothesis predicts synchrony exclusively between feature neurons that receive feedback from the same grouping circuit. We recorded from neurons in macaque visual cortex and used border-ownership selectivity, an intrinsic property of the neurons, to infer whether or not two neurons are part of the same grouping circuit. We found that binding produced synchrony between same-circuit neurons, but not between other pairs of neurons, as predicted b...","publication_date":{"day":29,"month":1,"year":2015,"errors":{}},"publication_name":"The Journal of neuroscience : the official journal of the Society for Neuroscience"},"translated_abstract":"Neurons at early stages of the visual cortex signal elemental features, such as pieces of contour, but how these signals are organized into perceptual objects is unclear. Theories have proposed that spiking synchrony between these neurons encodes how features are grouped (binding-by-synchrony), but recent studies did not find the predicted increase in synchrony with binding. Here we propose that features are grouped to \u0026quot;proto-objects\u0026quot; by intrinsic feedback circuits that enhance the responses of the participating feature neurons. This hypothesis predicts synchrony exclusively between feature neurons that receive feedback from the same grouping circuit. We recorded from neurons in macaque visual cortex and used border-ownership selectivity, an intrinsic property of the neurons, to infer whether or not two neurons are part of the same grouping circuit. We found that binding produced synchrony between same-circuit neurons, but not between other pairs of neurons, as predicted b...","internal_url":"https://www.academia.edu/57633061/Spike_synchrony_reveals_emergence_of_proto_objects_in_visual_cortex","translated_internal_url":"","created_at":"2021-10-13T16:27:04.690-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":72439287,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/72439287/thumbnails/1.jpg","file_name":"6860.full.pdf","download_url":"https://www.academia.edu/attachments/72439287/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Spike_synchrony_reveals_emergence_of_pro.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/72439287/6860.full-libre.pdf?1634272359=\u0026response-content-disposition=attachment%3B+filename%3DSpike_synchrony_reveals_emergence_of_pro.pdf\u0026Expires=1732785278\u0026Signature=ctlIM4-Y~8cNdNuDhtK1OHs2ZDRwpwHp1SNfPH7yaqWI-w5HQVgDy~LRl69~vKL2gxaIrL-ROxDUm~QTFGSVAZe4dxT5CQXjUtekdEVPs-jtkJDppCiIKkOIn2w0hbeEqklVoWQYkptH5Fs7JBFxXU~m776iNbZRA3q5NaHJFLAF89Fz446sLGVrwp9ldJShkclvjONXFSrBdVnmnd4Z3zvVoK22YFnhK0GpgJe49whnDEVq59X4q1dZESMuG7Z3bvWl-J7E43fdBpK4I94IcDpvHaRvWB8TXWehqVWZEYJRw1~RGaCzU4Q7If4DB2mOmFEauGorbQq~4-ndJY7Dsg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Spike_synchrony_reveals_emergence_of_proto_objects_in_visual_cortex","translated_slug":"","page_count":11,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[{"id":72439287,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/72439287/thumbnails/1.jpg","file_name":"6860.full.pdf","download_url":"https://www.academia.edu/attachments/72439287/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Spike_synchrony_reveals_emergence_of_pro.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/72439287/6860.full-libre.pdf?1634272359=\u0026response-content-disposition=attachment%3B+filename%3DSpike_synchrony_reveals_emergence_of_pro.pdf\u0026Expires=1732785278\u0026Signature=ctlIM4-Y~8cNdNuDhtK1OHs2ZDRwpwHp1SNfPH7yaqWI-w5HQVgDy~LRl69~vKL2gxaIrL-ROxDUm~QTFGSVAZe4dxT5CQXjUtekdEVPs-jtkJDppCiIKkOIn2w0hbeEqklVoWQYkptH5Fs7JBFxXU~m776iNbZRA3q5NaHJFLAF89Fz446sLGVrwp9ldJShkclvjONXFSrBdVnmnd4Z3zvVoK22YFnhK0GpgJe49whnDEVq59X4q1dZESMuG7Z3bvWl-J7E43fdBpK4I94IcDpvHaRvWB8TXWehqVWZEYJRw1~RGaCzU4Q7If4DB2mOmFEauGorbQq~4-ndJY7Dsg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":161,"name":"Neuroscience","url":"https://www.academia.edu/Documents/in/Neuroscience"},{"id":7736,"name":"Attention","url":"https://www.academia.edu/Documents/in/Attention"},{"id":49962,"name":"Visual Cortex","url":"https://www.academia.edu/Documents/in/Visual_Cortex"},{"id":82283,"name":"Form perception","url":"https://www.academia.edu/Documents/in/Form_perception"},{"id":119665,"name":"Reaction Time","url":"https://www.academia.edu/Documents/in/Reaction_Time"},{"id":143507,"name":"Eye Movements","url":"https://www.academia.edu/Documents/in/Eye_Movements"},{"id":193974,"name":"Neurons","url":"https://www.academia.edu/Documents/in/Neurons"},{"id":386773,"name":"Sensory Feedback","url":"https://www.academia.edu/Documents/in/Sensory_Feedback"},{"id":573267,"name":"Macaca Mulatta","url":"https://www.academia.edu/Documents/in/Macaca_Mulatta"},{"id":955727,"name":"Action Potentials","url":"https://www.academia.edu/Documents/in/Action_Potentials"},{"id":968586,"name":"Visual Evoked Potentials","url":"https://www.academia.edu/Documents/in/Visual_Evoked_Potentials"},{"id":2463496,"name":"Statistics as Topic","url":"https://www.academia.edu/Documents/in/Statistics_as_Topic"},{"id":2849038,"name":"photic stimulation","url":"https://www.academia.edu/Documents/in/photic_stimulation"},{"id":2922956,"name":"Psychology and Cognitive Sciences","url":"https://www.academia.edu/Documents/in/Psychology_and_Cognitive_Sciences"},{"id":3763225,"name":"Medical and Health Sciences","url":"https://www.academia.edu/Documents/in/Medical_and_Health_Sciences"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="57633060"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/57633060/A_neural_model_for_perceptual_organization_of_3D_surfaces"><img alt="Research paper thumbnail of A neural model for perceptual organization of 3D surfaces" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/57633060/A_neural_model_for_perceptual_organization_of_3D_surfaces">A neural model for perceptual organization of 3D surfaces</a></div><div class="wp-workCard_item"><span>2015 49th Annual Conference on Information Sciences and Systems (CISS)</span><span>, 2015</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="57633060"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="57633060"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 57633060; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=57633060]").text(description); $(".js-view-count[data-work-id=57633060]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 57633060; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='57633060']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 57633060, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=57633060]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":57633060,"title":"A neural model for perceptual organization of 3D surfaces","translated_title":"","metadata":{"publisher":"IEEE","publication_date":{"day":null,"month":null,"year":2015,"errors":{}},"publication_name":"2015 49th Annual Conference on Information Sciences and Systems (CISS)"},"translated_abstract":null,"internal_url":"https://www.academia.edu/57633060/A_neural_model_for_perceptual_organization_of_3D_surfaces","translated_internal_url":"","created_at":"2021-10-13T16:27:04.618-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"A_neural_model_for_perceptual_organization_of_3D_surfaces","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[],"research_interests":[],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="57633059"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/57633059/Detektion_von_ein_und_zwei_dimensionalen_Bildstrukturen_in_komplexen_Grauwertbildern"><img alt="Research paper thumbnail of Detektion von ein- und zwei-dimensionalen Bildstrukturen in komplexen Grauwertbildern" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/57633059/Detektion_von_ein_und_zwei_dimensionalen_Bildstrukturen_in_komplexen_Grauwertbildern">Detektion von ein- und zwei-dimensionalen Bildstrukturen in komplexen Grauwertbildern</a></div><div class="wp-workCard_item"><span>Informatik aktuell</span><span>, 1992</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="57633059"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="57633059"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 57633059; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=57633059]").text(description); $(".js-view-count[data-work-id=57633059]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 57633059; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='57633059']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 57633059, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=57633059]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":57633059,"title":"Detektion von ein- und zwei-dimensionalen Bildstrukturen in komplexen Grauwertbildern","translated_title":"","metadata":{"publication_date":{"day":null,"month":null,"year":1992,"errors":{}},"publication_name":"Informatik aktuell"},"translated_abstract":null,"internal_url":"https://www.academia.edu/57633059/Detektion_von_ein_und_zwei_dimensionalen_Bildstrukturen_in_komplexen_Grauwertbildern","translated_internal_url":"","created_at":"2021-10-13T16:27:04.549-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Detektion_von_ein_und_zwei_dimensionalen_Bildstrukturen_in_komplexen_Grauwertbildern","translated_slug":"","page_count":null,"language":"de","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[],"research_interests":[],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="57633058"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/57633058/Searching_for_the_Neural_Mechanism_of_Color_Filling_In"><img alt="Research paper thumbnail of Searching for the Neural Mechanism of Color Filling-In" class="work-thumbnail" src="https://attachments.academia-assets.com/72439393/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/57633058/Searching_for_the_Neural_Mechanism_of_Color_Filling_In">Searching for the Neural Mechanism of Color Filling-In</a></div><div class="wp-workCard_item"><span>Filling-In</span><span>, 2003</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="54c3fc56f6690f116b7b8cc096943eef" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":72439393,"asset_id":57633058,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/72439393/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="57633058"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="57633058"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 57633058; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=57633058]").text(description); $(".js-view-count[data-work-id=57633058]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 57633058; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='57633058']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 57633058, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "54c3fc56f6690f116b7b8cc096943eef" } } $('.js-work-strip[data-work-id=57633058]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":57633058,"title":"Searching for the Neural Mechanism of Color Filling-In","translated_title":"","metadata":{"publisher":"Oxford University Press","publication_date":{"day":null,"month":null,"year":2003,"errors":{}},"publication_name":"Filling-In"},"translated_abstract":null,"internal_url":"https://www.academia.edu/57633058/Searching_for_the_Neural_Mechanism_of_Color_Filling_In","translated_internal_url":"","created_at":"2021-10-13T16:27:04.476-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":72439393,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/72439393/thumbnails/1.jpg","file_name":"59ae5f250011fec59722c0768a78a7a937a2.pdf","download_url":"https://www.academia.edu/attachments/72439393/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Searching_for_the_Neural_Mechanism_of_Co.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/72439393/59ae5f250011fec59722c0768a78a7a937a2-libre.pdf?1634272353=\u0026response-content-disposition=attachment%3B+filename%3DSearching_for_the_Neural_Mechanism_of_Co.pdf\u0026Expires=1732785278\u0026Signature=JVjBTCa~eEw8TA~ZjC0YGa9ZVRL6pMaBg1zXNrUgnX2Hl2-8t065V1Dg-aGTNAfCrcd6F0PEvvXF1dcYvy19f67d7HaTvSy~xqYtP4CjhMUmd4zJxYV9hnpWHyYMD42Sl6-NlgBqH-8p9LO9SIy5Y7bvKnnc5q0~7wPJaPWbSEtWgDG8Y38gpTZGOmhRAg8douzscpGguFJRLh7Eerh4ZYbtpOvq89sQ9dPaSFxTSlsdDwQKh1e9IRtO7wYMKp51MyoVvtxBdc0TAylesWMtz4butVXCY6bNL~8~s1qebTpwDG-z08GHRzFLXRjYP6bwUYpr0LlX24yAzQYb2wZnoA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Searching_for_the_Neural_Mechanism_of_Color_Filling_In","translated_slug":"","page_count":28,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[{"id":72439393,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/72439393/thumbnails/1.jpg","file_name":"59ae5f250011fec59722c0768a78a7a937a2.pdf","download_url":"https://www.academia.edu/attachments/72439393/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Searching_for_the_Neural_Mechanism_of_Co.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/72439393/59ae5f250011fec59722c0768a78a7a937a2-libre.pdf?1634272353=\u0026response-content-disposition=attachment%3B+filename%3DSearching_for_the_Neural_Mechanism_of_Co.pdf\u0026Expires=1732785278\u0026Signature=JVjBTCa~eEw8TA~ZjC0YGa9ZVRL6pMaBg1zXNrUgnX2Hl2-8t065V1Dg-aGTNAfCrcd6F0PEvvXF1dcYvy19f67d7HaTvSy~xqYtP4CjhMUmd4zJxYV9hnpWHyYMD42Sl6-NlgBqH-8p9LO9SIy5Y7bvKnnc5q0~7wPJaPWbSEtWgDG8Y38gpTZGOmhRAg8douzscpGguFJRLh7Eerh4ZYbtpOvq89sQ9dPaSFxTSlsdDwQKh1e9IRtO7wYMKp51MyoVvtxBdc0TAylesWMtz4butVXCY6bNL~8~s1qebTpwDG-z08GHRzFLXRjYP6bwUYpr0LlX24yAzQYb2wZnoA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":624348,"name":"Filling","url":"https://www.academia.edu/Documents/in/Filling"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="57633057"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/57633057/Form_Perception_and_Attention"><img alt="Research paper thumbnail of Form Perception and Attention" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/57633057/Form_Perception_and_Attention">Form Perception and Attention</a></div><div class="wp-workCard_item"><span>Visual Perception</span><span>, 1990</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="57633057"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="57633057"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 57633057; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=57633057]").text(description); $(".js-view-count[data-work-id=57633057]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 57633057; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='57633057']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 57633057, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=57633057]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":57633057,"title":"Form Perception and Attention","translated_title":"","metadata":{"publication_date":{"day":null,"month":null,"year":1990,"errors":{}},"publication_name":"Visual Perception"},"translated_abstract":null,"internal_url":"https://www.academia.edu/57633057/Form_Perception_and_Attention","translated_internal_url":"","created_at":"2021-10-13T16:27:04.375-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Form_Perception_and_Attention","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[],"research_interests":[{"id":5359,"name":"Visual perception","url":"https://www.academia.edu/Documents/in/Visual_perception"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> </div><div class="profile--tab_content_container js-tab-pane tab-pane" data-section-id="11999590" id="papers"><div class="js-work-strip profile--work_container" data-work-id="109893024"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/109893024/Visual_cortical_processing_From_image_to_object_representation"><img alt="Research paper thumbnail of Visual cortical processing-From image to object representation" class="work-thumbnail" src="https://attachments.academia-assets.com/107879736/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/109893024/Visual_cortical_processing_From_image_to_object_representation">Visual cortical processing-From image to object representation</a></div><div class="wp-workCard_item"><span>Frontiers in Computer Science</span><span>, 2023</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Image understanding is often conceived as a hierarchical process with many levels, where complexi...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Image understanding is often conceived as a hierarchical process with many levels, where complexity and invariance of object representation gradually increase with level in the hierarchy. In contrast, neurophysiological studies have shown that figure-ground organization and border ownership coding, which imply understanding of the object structure of an image, occur at levels as low as V1 and V2 of the visual cortex. This cannot be the result of back-projections from object recognition centers because border-ownership signals appear well-before shape selective responses emerge in inferotemporal cortex. Ultra-fast border-ownership signals have been found not only for simple figure displays, but also for complex natural scenes. In this paper I review neurophysiological evidence for the hypothesis that the brain uses dedicated grouping mechanisms early on to link elementary features to larger entities we might call "proto-objects", a process that is pre-attentive and does not rely on object recognition. The proto-object structures enable the system to individuate objects and provide permanence, to track moving objects and cope with the displacements caused by eye movements, and to select one object out of many and scrutinize the selected object. I sketch a novel experimental paradigm for identifying grouping circuits, describe a first application targeting area V4, which yielded negative results, and suggest targets for future applications of this paradigm.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="956ef6c89d0110b6f9b0f1fc25c4d2f9" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":107879736,"asset_id":109893024,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/107879736/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="109893024"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="109893024"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 109893024; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=109893024]").text(description); $(".js-view-count[data-work-id=109893024]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 109893024; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='109893024']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 109893024, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "956ef6c89d0110b6f9b0f1fc25c4d2f9" } } $('.js-work-strip[data-work-id=109893024]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":109893024,"title":"Visual cortical processing-From image to object representation","translated_title":"","metadata":{"doi":"10.3389/fcomp.2023.1136987","abstract":"Image understanding is often conceived as a hierarchical process with many levels, where complexity and invariance of object representation gradually increase with level in the hierarchy. In contrast, neurophysiological studies have shown that figure-ground organization and border ownership coding, which imply understanding of the object structure of an image, occur at levels as low as V1 and V2 of the visual cortex. This cannot be the result of back-projections from object recognition centers because border-ownership signals appear well-before shape selective responses emerge in inferotemporal cortex. Ultra-fast border-ownership signals have been found not only for simple figure displays, but also for complex natural scenes. In this paper I review neurophysiological evidence for the hypothesis that the brain uses dedicated grouping mechanisms early on to link elementary features to larger entities we might call \"proto-objects\", a process that is pre-attentive and does not rely on object recognition. The proto-object structures enable the system to individuate objects and provide permanence, to track moving objects and cope with the displacements caused by eye movements, and to select one object out of many and scrutinize the selected object. I sketch a novel experimental paradigm for identifying grouping circuits, describe a first application targeting area V4, which yielded negative results, and suggest targets for future applications of this paradigm.","publication_date":{"day":null,"month":null,"year":2023,"errors":{}},"publication_name":"Frontiers in Computer Science"},"translated_abstract":"Image understanding is often conceived as a hierarchical process with many levels, where complexity and invariance of object representation gradually increase with level in the hierarchy. In contrast, neurophysiological studies have shown that figure-ground organization and border ownership coding, which imply understanding of the object structure of an image, occur at levels as low as V1 and V2 of the visual cortex. This cannot be the result of back-projections from object recognition centers because border-ownership signals appear well-before shape selective responses emerge in inferotemporal cortex. Ultra-fast border-ownership signals have been found not only for simple figure displays, but also for complex natural scenes. In this paper I review neurophysiological evidence for the hypothesis that the brain uses dedicated grouping mechanisms early on to link elementary features to larger entities we might call \"proto-objects\", a process that is pre-attentive and does not rely on object recognition. The proto-object structures enable the system to individuate objects and provide permanence, to track moving objects and cope with the displacements caused by eye movements, and to select one object out of many and scrutinize the selected object. I sketch a novel experimental paradigm for identifying grouping circuits, describe a first application targeting area V4, which yielded negative results, and suggest targets for future applications of this paradigm.","internal_url":"https://www.academia.edu/109893024/Visual_cortical_processing_From_image_to_object_representation","translated_internal_url":"","created_at":"2023-11-26T16:01:57.163-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[{"id":40593739,"work_id":109893024,"tagging_user_id":99283352,"tagged_user_id":32407145,"co_author_invite_id":null,"email":"m***s@u.arizona.edu","affiliation":"The University of Arizona","display_order":1,"name":"Mary Peterson","title":"Visual cortical processing-From image to object representation"},{"id":40593740,"work_id":109893024,"tagging_user_id":99283352,"tagged_user_id":null,"co_author_invite_id":141508,"email":"g***t@berkeley.edu","display_order":2,"name":"Jack Gallant","title":"Visual cortical processing-From image to object representation"},{"id":40593741,"work_id":109893024,"tagging_user_id":99283352,"tagged_user_id":101974527,"co_author_invite_id":null,"email":"n***o@gmail.com","affiliation":"Radboud University Nijmegen","display_order":3,"name":"Naoki Kogo","title":"Visual cortical processing-From image to object representation"},{"id":40593742,"work_id":109893024,"tagging_user_id":99283352,"tagged_user_id":null,"co_author_invite_id":596605,"email":"v***t@jhu.edu","display_order":4,"name":"Rüdiger Von Der Heydt","title":"Visual cortical processing-From image to object representation"}],"downloadable_attachments":[{"id":107879736,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/107879736/thumbnails/1.jpg","file_name":"vonderHeydt_2023_From_image_to_object_representation.pdf","download_url":"https://www.academia.edu/attachments/107879736/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Visual_cortical_processing_From_image_to.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/107879736/vonderHeydt_2023_From_image_to_object_representation-libre.pdf?1701045059=\u0026response-content-disposition=attachment%3B+filename%3DVisual_cortical_processing_From_image_to.pdf\u0026Expires=1732785277\u0026Signature=SzQeBDA2cVu~N3gmvr6PX7g2JSmN624K~3FdB4XeWAqIvjcoP75Q5JImrwNDohpXl7VyVqVKt0e0gQLXZckbljD~JQueDFh-Ga8ssf2jc82oD2izAXv0siJKCmUzaFHSD7yIQw9-qEtomICYnqposO4~cInLh69Q-Jhnt8KDKn053pWvLUJh6SqwKZFWQcZObl4BR0XuYFINanqHpCsYiNA8GNarFLEUix0Q-EqbhEDUjp2br4Noh6wk1NSojUwZaO6I-jEehPSZMuo8H9y2d9j4PdT7EaULWEgdOlPXV6qQdVp~lM1dTh7-NTsO3xmzUURxd5~iJHd3zkJA7dmskQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Visual_cortical_processing_From_image_to_object_representation","translated_slug":"","page_count":18,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[{"id":107879736,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/107879736/thumbnails/1.jpg","file_name":"vonderHeydt_2023_From_image_to_object_representation.pdf","download_url":"https://www.academia.edu/attachments/107879736/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Visual_cortical_processing_From_image_to.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/107879736/vonderHeydt_2023_From_image_to_object_representation-libre.pdf?1701045059=\u0026response-content-disposition=attachment%3B+filename%3DVisual_cortical_processing_From_image_to.pdf\u0026Expires=1732785277\u0026Signature=SzQeBDA2cVu~N3gmvr6PX7g2JSmN624K~3FdB4XeWAqIvjcoP75Q5JImrwNDohpXl7VyVqVKt0e0gQLXZckbljD~JQueDFh-Ga8ssf2jc82oD2izAXv0siJKCmUzaFHSD7yIQw9-qEtomICYnqposO4~cInLh69Q-Jhnt8KDKn053pWvLUJh6SqwKZFWQcZObl4BR0XuYFINanqHpCsYiNA8GNarFLEUix0Q-EqbhEDUjp2br4Noh6wk1NSojUwZaO6I-jEehPSZMuo8H9y2d9j4PdT7EaULWEgdOlPXV6qQdVp~lM1dTh7-NTsO3xmzUURxd5~iJHd3zkJA7dmskQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":161,"name":"Neuroscience","url":"https://www.academia.edu/Documents/in/Neuroscience"},{"id":59692,"name":"Vision","url":"https://www.academia.edu/Documents/in/Vision"},{"id":118256,"name":"Object Perception","url":"https://www.academia.edu/Documents/in/Object_Perception"},{"id":242845,"name":"Object Permanence","url":"https://www.academia.edu/Documents/in/Object_Permanence"},{"id":700621,"name":"Visual Short Term Memory","url":"https://www.academia.edu/Documents/in/Visual_Short_Term_Memory"},{"id":1181061,"name":"Neural Signal","url":"https://www.academia.edu/Documents/in/Neural_Signal"},{"id":1851775,"name":"Perceptual organization","url":"https://www.academia.edu/Documents/in/Perceptual_organization"},{"id":2707350,"name":"Brain Mechanisms","url":"https://www.academia.edu/Documents/in/Brain_Mechanisms"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="75763340"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/75763340/Searching_for_object_pointers_in_the_visual_cortex"><img alt="Research paper thumbnail of Searching for object pointers in the visual cortex" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/75763340/Searching_for_object_pointers_in_the_visual_cortex">Searching for object pointers in the visual cortex</a></div><div class="wp-workCard_item"><span>Journal of Neurophysiology</span><span>, 2020</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The way we perceive objects as permanent contrasts with the short-lived responses of visual corti...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The way we perceive objects as permanent contrasts with the short-lived responses of visual cortical neurons. A theory postulates pointers that give objects continuity, predicting a class of neurons that respond not only to visual objects but also when an occluded object moves into their receptive field. Here, we tested this theory with a novel paradigm in which a monkey freely scans an array of objects while some of them are transiently occluded.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75763340"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75763340"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75763340; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75763340]").text(description); $(".js-view-count[data-work-id=75763340]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75763340; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75763340']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 75763340, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=75763340]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75763340,"title":"Searching for object pointers in the visual cortex","translated_title":"","metadata":{"abstract":"The way we perceive objects as permanent contrasts with the short-lived responses of visual cortical neurons. A theory postulates pointers that give objects continuity, predicting a class of neurons that respond not only to visual objects but also when an occluded object moves into their receptive field. Here, we tested this theory with a novel paradigm in which a monkey freely scans an array of objects while some of them are transiently occluded.","publisher":"American Physiological Society","publication_date":{"day":null,"month":null,"year":2020,"errors":{}},"publication_name":"Journal of Neurophysiology"},"translated_abstract":"The way we perceive objects as permanent contrasts with the short-lived responses of visual cortical neurons. A theory postulates pointers that give objects continuity, predicting a class of neurons that respond not only to visual objects but also when an occluded object moves into their receptive field. Here, we tested this theory with a novel paradigm in which a monkey freely scans an array of objects while some of them are transiently occluded.","internal_url":"https://www.academia.edu/75763340/Searching_for_object_pointers_in_the_visual_cortex","translated_internal_url":"","created_at":"2022-04-07T17:07:00.449-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Searching_for_object_pointers_in_the_visual_cortex","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[],"research_interests":[{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science"},{"id":465,"name":"Artificial Intelligence","url":"https://www.academia.edu/Documents/in/Artificial_Intelligence"},{"id":22272,"name":"Neurophysiology","url":"https://www.academia.edu/Documents/in/Neurophysiology"},{"id":2922956,"name":"Psychology and Cognitive Sciences","url":"https://www.academia.edu/Documents/in/Psychology_and_Cognitive_Sciences"},{"id":3763225,"name":"Medical and Health Sciences","url":"https://www.academia.edu/Documents/in/Medical_and_Health_Sciences"}],"urls":[{"id":19232103,"url":"https://journals.physiology.org/doi/pdf/10.1152/jn.00112.2020"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="75763339"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/75763339/Figure_ground_organization_in_the_visual_cortex_does_meaning_matter"><img alt="Research paper thumbnail of Figure-ground organization in the visual cortex: does meaning matter?" class="work-thumbnail" src="https://attachments.academia-assets.com/83404935/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/75763339/Figure_ground_organization_in_the_visual_cortex_does_meaning_matter">Figure-ground organization in the visual cortex: does meaning matter?</a></div><div class="wp-workCard_item"><span>Journal of Neurophysiology</span><span>, 2018</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Figure-ground organization in the visual cortex is generally assumed to be based partly on genera...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Figure-ground organization in the visual cortex is generally assumed to be based partly on general rules and partly on specific influences of object recognition in higher centers as found in the temporal lobe. To see if shape familiarity influences figure-ground organization, we tested border ownership-selective neurons in monkey V1/V2 with silhouettes of human and monkey face profiles and “nonsense” silhouettes constructed by mirror-reversing the front part of the profile. We found no superiority of face silhouettes compared with nonsense shapes in eliciting border-ownership signals overall. However, in some neurons, border-ownership signals differed strongly between the two categories consistently across many different profile shapes. Surprisingly, this category selectivity appeared as early as 70 ms after stimulus onset, which is earlier than the typical latency of shape-selective responses but compatible with the earliest face-selective responses in the inferior temporal lobe. A...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="4b5b8187d56d4cc4860ce8a86f27ca39" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":83404935,"asset_id":75763339,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/83404935/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75763339"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75763339"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75763339; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75763339]").text(description); $(".js-view-count[data-work-id=75763339]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75763339; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75763339']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 75763339, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "4b5b8187d56d4cc4860ce8a86f27ca39" } } $('.js-work-strip[data-work-id=75763339]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75763339,"title":"Figure-ground organization in the visual cortex: does meaning matter?","translated_title":"","metadata":{"abstract":"Figure-ground organization in the visual cortex is generally assumed to be based partly on general rules and partly on specific influences of object recognition in higher centers as found in the temporal lobe. To see if shape familiarity influences figure-ground organization, we tested border ownership-selective neurons in monkey V1/V2 with silhouettes of human and monkey face profiles and “nonsense” silhouettes constructed by mirror-reversing the front part of the profile. We found no superiority of face silhouettes compared with nonsense shapes in eliciting border-ownership signals overall. However, in some neurons, border-ownership signals differed strongly between the two categories consistently across many different profile shapes. Surprisingly, this category selectivity appeared as early as 70 ms after stimulus onset, which is earlier than the typical latency of shape-selective responses but compatible with the earliest face-selective responses in the inferior temporal lobe. A...","publisher":"American Physiological Society","publication_date":{"day":null,"month":null,"year":2018,"errors":{}},"publication_name":"Journal of Neurophysiology"},"translated_abstract":"Figure-ground organization in the visual cortex is generally assumed to be based partly on general rules and partly on specific influences of object recognition in higher centers as found in the temporal lobe. To see if shape familiarity influences figure-ground organization, we tested border ownership-selective neurons in monkey V1/V2 with silhouettes of human and monkey face profiles and “nonsense” silhouettes constructed by mirror-reversing the front part of the profile. We found no superiority of face silhouettes compared with nonsense shapes in eliciting border-ownership signals overall. However, in some neurons, border-ownership signals differed strongly between the two categories consistently across many different profile shapes. Surprisingly, this category selectivity appeared as early as 70 ms after stimulus onset, which is earlier than the typical latency of shape-selective responses but compatible with the earliest face-selective responses in the inferior temporal lobe. A...","internal_url":"https://www.academia.edu/75763339/Figure_ground_organization_in_the_visual_cortex_does_meaning_matter","translated_internal_url":"","created_at":"2022-04-07T17:07:00.197-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":83404935,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/83404935/thumbnails/1.jpg","file_name":"jn.00131.pdf","download_url":"https://www.academia.edu/attachments/83404935/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Figure_ground_organization_in_the_visual.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/83404935/jn.00131-libre.pdf?1649377056=\u0026response-content-disposition=attachment%3B+filename%3DFigure_ground_organization_in_the_visual.pdf\u0026Expires=1732785277\u0026Signature=ObJj27O~XSVHA5ou4MicuKL6P4bnyeUVA3l5h16JKJ5QB9ttySqfy-BlImWs3XT3xBIKmQZyBPOUl0WOj5gPlrWdeGQOWe5AWygRaPKKRlskQXZOiRNfSP9~RkfAgiNH51pCGAwjxdUncuek8PflzLfk2lhavh9~GMi77TyslVOztD4TKVFZF6Co58G70V6gZKFiJFB-eQs-rBpCxi5ob4tz0Az1p4JQg5TnFMojXKlx8mk21HOZlI8Rmc~c54~MmzHXbn0en~NEhglCzbVXE0tLugBar16hSP7WpelWtItLLn~LmAjmRsxcTIWb1wNYXpwqSkJF4-jKiX~mYZKvAg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Figure_ground_organization_in_the_visual_cortex_does_meaning_matter","translated_slug":"","page_count":17,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[{"id":83404935,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/83404935/thumbnails/1.jpg","file_name":"jn.00131.pdf","download_url":"https://www.academia.edu/attachments/83404935/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Figure_ground_organization_in_the_visual.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/83404935/jn.00131-libre.pdf?1649377056=\u0026response-content-disposition=attachment%3B+filename%3DFigure_ground_organization_in_the_visual.pdf\u0026Expires=1732785277\u0026Signature=ObJj27O~XSVHA5ou4MicuKL6P4bnyeUVA3l5h16JKJ5QB9ttySqfy-BlImWs3XT3xBIKmQZyBPOUl0WOj5gPlrWdeGQOWe5AWygRaPKKRlskQXZOiRNfSP9~RkfAgiNH51pCGAwjxdUncuek8PflzLfk2lhavh9~GMi77TyslVOztD4TKVFZF6Co58G70V6gZKFiJFB-eQs-rBpCxi5ob4tz0Az1p4JQg5TnFMojXKlx8mk21HOZlI8Rmc~c54~MmzHXbn0en~NEhglCzbVXE0tLugBar16hSP7WpelWtItLLn~LmAjmRsxcTIWb1wNYXpwqSkJF4-jKiX~mYZKvAg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":221,"name":"Psychology","url":"https://www.academia.edu/Documents/in/Psychology"},{"id":22272,"name":"Neurophysiology","url":"https://www.academia.edu/Documents/in/Neurophysiology"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":2922956,"name":"Psychology and Cognitive Sciences","url":"https://www.academia.edu/Documents/in/Psychology_and_Cognitive_Sciences"},{"id":3763225,"name":"Medical and Health Sciences","url":"https://www.academia.edu/Documents/in/Medical_and_Health_Sciences"}],"urls":[{"id":19232102,"url":"http://www.physiology.org/doi/pdf/10.1152/jn.00131.2017"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="75763333"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/75763333/Figure_ground_organization_and_the_emergence_of_proto_objects_in_the_visual_cortex"><img alt="Research paper thumbnail of Figure–ground organization and the emergence of proto-objects in the visual cortex" class="work-thumbnail" src="https://attachments.academia-assets.com/83404929/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/75763333/Figure_ground_organization_and_the_emergence_of_proto_objects_in_the_visual_cortex">Figure–ground organization and the emergence of proto-objects in the visual cortex</a></div><div class="wp-workCard_item"><span>Frontiers in Psychology</span><span>, 2015</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="9d7aa9bdc950e2ea102ae660ee9bf26d" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":83404929,"asset_id":75763333,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/83404929/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="75763333"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="75763333"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 75763333; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=75763333]").text(description); $(".js-view-count[data-work-id=75763333]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 75763333; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='75763333']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 75763333, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "9d7aa9bdc950e2ea102ae660ee9bf26d" } } $('.js-work-strip[data-work-id=75763333]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":75763333,"title":"Figure–ground organization and the emergence of proto-objects in the visual cortex","translated_title":"","metadata":{"publisher":"Frontiers Media SA","publication_date":{"day":null,"month":null,"year":2015,"errors":{}},"publication_name":"Frontiers in Psychology"},"translated_abstract":null,"internal_url":"https://www.academia.edu/75763333/Figure_ground_organization_and_the_emergence_of_proto_objects_in_the_visual_cortex","translated_internal_url":"","created_at":"2022-04-07T17:06:25.519-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":83404929,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/83404929/thumbnails/1.jpg","file_name":"pmc4630502.pdf","download_url":"https://www.academia.edu/attachments/83404929/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Figure_ground_organization_and_the_emerg.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/83404929/pmc4630502-libre.pdf?1649377058=\u0026response-content-disposition=attachment%3B+filename%3DFigure_ground_organization_and_the_emerg.pdf\u0026Expires=1732785277\u0026Signature=bTsX8TO27MM3BlTiHzJxYwb8tGJNIaMP4xoimoa8yDamz8Ins4yujzHBoGkaHL5h-KFmqlaENND5Bj2MvIK5SdNnwqKYj9F3zNQLpPD-Um5CZ6DB2PCAflNgBTAJetEt6jPYTkN9DG6HOtutJPq5kiurnvDDRKCMBZPyRjk6donG7RQ3ebtdjbqmPXtGeeLl7jl9Kzpeys~tTNvmy5Ue0QFMjvF10dO60gru9AOf2TDv99OCdJypg2lr7D0dwIw1pOGcwKRacpmh4sYq~f1rmhcCRt13KVXDPljyUdPZ15cnEvvWuBJUjkXCRVrb2g3QdDYVL5IczpR3NPaWN6UILg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Figure_ground_organization_and_the_emergence_of_proto_objects_in_the_visual_cortex","translated_slug":"","page_count":10,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[{"id":83404929,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/83404929/thumbnails/1.jpg","file_name":"pmc4630502.pdf","download_url":"https://www.academia.edu/attachments/83404929/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Figure_ground_organization_and_the_emerg.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/83404929/pmc4630502-libre.pdf?1649377058=\u0026response-content-disposition=attachment%3B+filename%3DFigure_ground_organization_and_the_emerg.pdf\u0026Expires=1732785277\u0026Signature=bTsX8TO27MM3BlTiHzJxYwb8tGJNIaMP4xoimoa8yDamz8Ins4yujzHBoGkaHL5h-KFmqlaENND5Bj2MvIK5SdNnwqKYj9F3zNQLpPD-Um5CZ6DB2PCAflNgBTAJetEt6jPYTkN9DG6HOtutJPq5kiurnvDDRKCMBZPyRjk6donG7RQ3ebtdjbqmPXtGeeLl7jl9Kzpeys~tTNvmy5Ue0QFMjvF10dO60gru9AOf2TDv99OCdJypg2lr7D0dwIw1pOGcwKRacpmh4sYq~f1rmhcCRt13KVXDPljyUdPZ15cnEvvWuBJUjkXCRVrb2g3QdDYVL5IczpR3NPaWN6UILg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":221,"name":"Psychology","url":"https://www.academia.edu/Documents/in/Psychology"},{"id":2498386,"name":"Frontiers in Psychology","url":"https://www.academia.edu/Documents/in/Frontiers_in_Psychology"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="63017526"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/63017526/Visual_selectivity_and_top_down_modulation_of_neurons_in_monkey_V2_during_free_viewing"><img alt="Research paper thumbnail of Visual selectivity and top-down modulation of neurons in monkey V2 during free viewing" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/63017526/Visual_selectivity_and_top_down_modulation_of_neurons_in_monkey_V2_during_free_viewing">Visual selectivity and top-down modulation of neurons in monkey V2 during free viewing</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Neurons in early visual cortex are selective for local visual features but their responses can al...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Neurons in early visual cortex are selective for local visual features but their responses can also be influenced by factors like border ownership and selective attention. Most of what we know about the function of these neurons is based on neurophysiological studies in monkeys that hold their direction of gaze fixed while isolated visual stimuli are presented (controlled viewing). However, during natural behavior, primates visually explore cluttered environments by changing gaze direction several times each second (free viewing). How does the visual cortex work under these conditions? We explored neuronal responses using a foraging task in which the monkey chooses where to look and when. Geometrical figures were displayed and the monkey was rewarded for fixating the center of a figure for at least 200ms. In each trial an array of 10 figures (5 squares and 5 triangles) was presented, one of which was randomly associated with reward, and a cue informed the monkey whether it was a squ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="63017526"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="63017526"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 63017526; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=63017526]").text(description); $(".js-view-count[data-work-id=63017526]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 63017526; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='63017526']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 63017526, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=63017526]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":63017526,"title":"Visual selectivity and top-down modulation of neurons in monkey V2 during free viewing","translated_title":"","metadata":{"abstract":"Neurons in early visual cortex are selective for local visual features but their responses can also be influenced by factors like border ownership and selective attention. Most of what we know about the function of these neurons is based on neurophysiological studies in monkeys that hold their direction of gaze fixed while isolated visual stimuli are presented (controlled viewing). However, during natural behavior, primates visually explore cluttered environments by changing gaze direction several times each second (free viewing). How does the visual cortex work under these conditions? We explored neuronal responses using a foraging task in which the monkey chooses where to look and when. Geometrical figures were displayed and the monkey was rewarded for fixating the center of a figure for at least 200ms. In each trial an array of 10 figures (5 squares and 5 triangles) was presented, one of which was randomly associated with reward, and a cue informed the monkey whether it was a squ...","publisher":"Journal of vision","publication_date":{"day":null,"month":null,"year":2015,"errors":{}}},"translated_abstract":"Neurons in early visual cortex are selective for local visual features but their responses can also be influenced by factors like border ownership and selective attention. Most of what we know about the function of these neurons is based on neurophysiological studies in monkeys that hold their direction of gaze fixed while isolated visual stimuli are presented (controlled viewing). However, during natural behavior, primates visually explore cluttered environments by changing gaze direction several times each second (free viewing). How does the visual cortex work under these conditions? We explored neuronal responses using a foraging task in which the monkey chooses where to look and when. Geometrical figures were displayed and the monkey was rewarded for fixating the center of a figure for at least 200ms. In each trial an array of 10 figures (5 squares and 5 triangles) was presented, one of which was randomly associated with reward, and a cue informed the monkey whether it was a squ...","internal_url":"https://www.academia.edu/63017526/Visual_selectivity_and_top_down_modulation_of_neurons_in_monkey_V2_during_free_viewing","translated_internal_url":"","created_at":"2021-12-02T12:40:45.101-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Visual_selectivity_and_top_down_modulation_of_neurons_in_monkey_V2_during_free_viewing","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[],"research_interests":[{"id":59692,"name":"Vision","url":"https://www.academia.edu/Documents/in/Vision"},{"id":2922956,"name":"Psychology and Cognitive Sciences","url":"https://www.academia.edu/Documents/in/Psychology_and_Cognitive_Sciences"},{"id":3763225,"name":"Medical and Health Sciences","url":"https://www.academia.edu/Documents/in/Medical_and_Health_Sciences"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="63017525"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/63017525/The_speed_of_context_integration_in_the_visual_cortex"><img alt="Research paper thumbnail of The speed of context integration in the visual cortex" class="work-thumbnail" src="https://attachments.academia-assets.com/75586454/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/63017525/The_speed_of_context_integration_in_the_visual_cortex">The speed of context integration in the visual cortex</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The observation of figure-ground selectivity in neurons of the visual cortex shows that these neu...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">The observation of figure-ground selectivity in neurons of the visual cortex shows that these neurons can be influenced by the image context far beyond the classical receptive field. To clarify the nature of the context integration mechanism, we studied the latencies of neural edge signals, comparing the emergence of context-dependent definition of border ownership with the onset of local edge definition (contrast polarity; stereoscopic depth order). Single-neuron activity was recorded in areas V1 and V2 of Macaca mulatta under behaviorally induced fixation. Whereas local edge definition emerged immediately (&lt;13 ms) after the edge onset response, the context-dependent signal was delayed by about 30 ms. To see if the context influence was mediated by horizontal fibers within cortex, we measured the latencies of border ownership signals for two conditions in which the relevant context information was located at different distances from the receptive field and compared the latency d...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="2a11512624e32cefeed45f88c79d40dd" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":75586454,"asset_id":63017525,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/75586454/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="63017525"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="63017525"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 63017525; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=63017525]").text(description); $(".js-view-count[data-work-id=63017525]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 63017525; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='63017525']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 63017525, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "2a11512624e32cefeed45f88c79d40dd" } } $('.js-work-strip[data-work-id=63017525]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":63017525,"title":"The speed of context integration in the visual cortex","translated_title":"","metadata":{"abstract":"The observation of figure-ground selectivity in neurons of the visual cortex shows that these neurons can be influenced by the image context far beyond the classical receptive field. To clarify the nature of the context integration mechanism, we studied the latencies of neural edge signals, comparing the emergence of context-dependent definition of border ownership with the onset of local edge definition (contrast polarity; stereoscopic depth order). Single-neuron activity was recorded in areas V1 and V2 of Macaca mulatta under behaviorally induced fixation. Whereas local edge definition emerged immediately (\u0026lt;13 ms) after the edge onset response, the context-dependent signal was delayed by about 30 ms. To see if the context influence was mediated by horizontal fibers within cortex, we measured the latencies of border ownership signals for two conditions in which the relevant context information was located at different distances from the receptive field and compared the latency d...","publisher":"Journal of neurophysiology","publication_date":{"day":null,"month":null,"year":2011,"errors":{}}},"translated_abstract":"The observation of figure-ground selectivity in neurons of the visual cortex shows that these neurons can be influenced by the image context far beyond the classical receptive field. To clarify the nature of the context integration mechanism, we studied the latencies of neural edge signals, comparing the emergence of context-dependent definition of border ownership with the onset of local edge definition (contrast polarity; stereoscopic depth order). Single-neuron activity was recorded in areas V1 and V2 of Macaca mulatta under behaviorally induced fixation. Whereas local edge definition emerged immediately (\u0026lt;13 ms) after the edge onset response, the context-dependent signal was delayed by about 30 ms. To see if the context influence was mediated by horizontal fibers within cortex, we measured the latencies of border ownership signals for two conditions in which the relevant context information was located at different distances from the receptive field and compared the latency d...","internal_url":"https://www.academia.edu/63017525/The_speed_of_context_integration_in_the_visual_cortex","translated_internal_url":"","created_at":"2021-12-02T12:40:44.875-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":75586454,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/75586454/thumbnails/1.jpg","file_name":"374.full.pdf","download_url":"https://www.academia.edu/attachments/75586454/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"The_speed_of_context_integration_in_the.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/75586454/374.full-libre.pdf?1638479538=\u0026response-content-disposition=attachment%3B+filename%3DThe_speed_of_context_integration_in_the.pdf\u0026Expires=1732785277\u0026Signature=OrRDWHTGomBUI0wmYcgXD4EcrHsWzepglO6bpW0eT0QScn96RsE1GhmF4PJcSAqFJTzWtQ8-v39XY0WrYXY428ziIVe302r1iqJ50f88plc1qNdkdyuiLaLfx5mbbeQ8AqDA17sBcZIYg2k~LRY6yK-STLPlrWvhvZMXth6yEBiefrHToIbTamdE~LFl8YrhbR1BFUA1M528LJYwi28Ppvv1JEwDkIPqyGi0JAD1WXgJmEx4fzr-t8RnhFznawEKgy9mPNID~76aa~ua1VizxL2PVy2K2sn0utSHAio-rvzKggzyICM6ueJbGVXJAKt~aFF6sc3xuWPXhUuzYvEU8g__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"The_speed_of_context_integration_in_the_visual_cortex","translated_slug":"","page_count":12,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[{"id":75586454,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/75586454/thumbnails/1.jpg","file_name":"374.full.pdf","download_url":"https://www.academia.edu/attachments/75586454/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"The_speed_of_context_integration_in_the.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/75586454/374.full-libre.pdf?1638479538=\u0026response-content-disposition=attachment%3B+filename%3DThe_speed_of_context_integration_in_the.pdf\u0026Expires=1732785277\u0026Signature=OrRDWHTGomBUI0wmYcgXD4EcrHsWzepglO6bpW0eT0QScn96RsE1GhmF4PJcSAqFJTzWtQ8-v39XY0WrYXY428ziIVe302r1iqJ50f88plc1qNdkdyuiLaLfx5mbbeQ8AqDA17sBcZIYg2k~LRY6yK-STLPlrWvhvZMXth6yEBiefrHToIbTamdE~LFl8YrhbR1BFUA1M528LJYwi28Ppvv1JEwDkIPqyGi0JAD1WXgJmEx4fzr-t8RnhFznawEKgy9mPNID~76aa~ua1VizxL2PVy2K2sn0utSHAio-rvzKggzyICM6ueJbGVXJAKt~aFF6sc3xuWPXhUuzYvEU8g__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"},{"id":75586453,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/75586453/thumbnails/1.jpg","file_name":"374.full.pdf","download_url":"https://www.academia.edu/attachments/75586453/download_file","bulk_download_file_name":"The_speed_of_context_integration_in_the.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/75586453/374.full-libre.pdf?1638479538=\u0026response-content-disposition=attachment%3B+filename%3DThe_speed_of_context_integration_in_the.pdf\u0026Expires=1732785277\u0026Signature=JH7KU~M4Ic5Wl7bXmYFkzVuJp1tKbbpHhWVl~YBJHQT-XHrdCKUVqHL~VlStau1itrd1xoS4DvI7lI4gKq58X1GJA6UiJBadhyq5gsQKQqSQ-nf-jFkaolwjJ5LY8yeyAIGqgHfTKI-5p-6ufqfxLFmkBokxPrtUFItYYn5WCrqjw-yCPhy5oykLG6EEu6eqqJrJSbkYDVJCnH5rBcWmM6JNUccyzp0N9R14GyymKCPu~we8nNV~7KUqV40Rx0hTPZtLmuuxLxuRgID4AwowsqyxwzjP0xmvTweksYdWrBslNSkidLHRPC85p00FrUvQNWHL9iaK34505Rj6KZYqfw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":22272,"name":"Neurophysiology","url":"https://www.academia.edu/Documents/in/Neurophysiology"},{"id":49962,"name":"Visual Cortex","url":"https://www.academia.edu/Documents/in/Visual_Cortex"},{"id":52176,"name":"Brain Mapping","url":"https://www.academia.edu/Documents/in/Brain_Mapping"},{"id":193974,"name":"Neurons","url":"https://www.academia.edu/Documents/in/Neurons"},{"id":573267,"name":"Macaca Mulatta","url":"https://www.academia.edu/Documents/in/Macaca_Mulatta"},{"id":2922956,"name":"Psychology and Cognitive Sciences","url":"https://www.academia.edu/Documents/in/Psychology_and_Cognitive_Sciences"},{"id":3763225,"name":"Medical and Health Sciences","url":"https://www.academia.edu/Documents/in/Medical_and_Health_Sciences"}],"urls":[{"id":14713534,"url":"http://jn.physiology.org/content/jn/106/1/374.full.pdf"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="63017509"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/63017509/Image_Parsing_Mechanisms_of_the_Visual_Cortex"><img alt="Research paper thumbnail of Image Parsing Mechanisms of the Visual Cortex" class="work-thumbnail" src="https://attachments.academia-assets.com/75586503/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/63017509/Image_Parsing_Mechanisms_of_the_Visual_Cortex">Image Parsing Mechanisms of the Visual Cortex</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">In this chapter I will discuss visual processes that are often labeled as &quot; intermediate lev...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">In this chapter I will discuss visual processes that are often labeled as &quot; intermediate level vision &quot;. As a useful framework we consider vision as a sequence of processes each of which is a mapping from one representation to another. Understanding vision then means analyzing how information is represented at each stage and how it is transformed between stages (Marr, 1982). It is clear that the first stage, the level of the photoreceptors, is an image representation. This is a 2-dimensional array of color values, resembling the bitmap format of digital computers. Retinal processes transform this representation into a format that is suitable for transmission through the optic nerve to central brain structures. A radical transformation then takes place in the primary visual cortex. At the output of area V1 we find visual information encoded as a &quot; feature map &quot; , a representation of local features. The two dimensions of retinal position are encoded in the location...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="c5f72e0593ff0bdf9b22eac36d2b4bf6" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":75586503,"asset_id":63017509,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/75586503/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="63017509"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="63017509"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 63017509; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=63017509]").text(description); $(".js-view-count[data-work-id=63017509]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 63017509; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='63017509']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 63017509, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "c5f72e0593ff0bdf9b22eac36d2b4bf6" } } $('.js-work-strip[data-work-id=63017509]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":63017509,"title":"Image Parsing Mechanisms of the Visual Cortex","translated_title":"","metadata":{"abstract":"In this chapter I will discuss visual processes that are often labeled as \u0026quot; intermediate level vision \u0026quot;. As a useful framework we consider vision as a sequence of processes each of which is a mapping from one representation to another. Understanding vision then means analyzing how information is represented at each stage and how it is transformed between stages (Marr, 1982). It is clear that the first stage, the level of the photoreceptors, is an image representation. This is a 2-dimensional array of color values, resembling the bitmap format of digital computers. Retinal processes transform this representation into a format that is suitable for transmission through the optic nerve to central brain structures. A radical transformation then takes place in the primary visual cortex. At the output of area V1 we find visual information encoded as a \u0026quot; feature map \u0026quot; , a representation of local features. The two dimensions of retinal position are encoded in the location...","publication_date":{"day":null,"month":null,"year":2002,"errors":{}}},"translated_abstract":"In this chapter I will discuss visual processes that are often labeled as \u0026quot; intermediate level vision \u0026quot;. As a useful framework we consider vision as a sequence of processes each of which is a mapping from one representation to another. Understanding vision then means analyzing how information is represented at each stage and how it is transformed between stages (Marr, 1982). It is clear that the first stage, the level of the photoreceptors, is an image representation. This is a 2-dimensional array of color values, resembling the bitmap format of digital computers. Retinal processes transform this representation into a format that is suitable for transmission through the optic nerve to central brain structures. A radical transformation then takes place in the primary visual cortex. At the output of area V1 we find visual information encoded as a \u0026quot; feature map \u0026quot; , a representation of local features. The two dimensions of retinal position are encoded in the location...","internal_url":"https://www.academia.edu/63017509/Image_Parsing_Mechanisms_of_the_Visual_Cortex","translated_internal_url":"","created_at":"2021-12-02T12:40:21.359-08:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":75586503,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/75586503/thumbnails/1.jpg","file_name":"vonderHeydt_2004.pdf","download_url":"https://www.academia.edu/attachments/75586503/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Image_Parsing_Mechanisms_of_the_Visual_C.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/75586503/vonderHeydt_2004-libre.pdf?1638479536=\u0026response-content-disposition=attachment%3B+filename%3DImage_Parsing_Mechanisms_of_the_Visual_C.pdf\u0026Expires=1732785277\u0026Signature=b1OhZNJxcaRbYAI4x~tAqJQo2dwm90Hzm7cPxyxep0lIjAYAOpiK2VhwxTai~YPIZI5MDZrVFxsKId06TdWRKVJp74nUs3Vh-qGP3623n8u6CMAn7HOx-TCoMm4ZPHJ5LbtK8pqzsm~lBt301wPrPI1bx7ByrqhEMSq9deYX11OUF61bkwgRTukdB3cnvf6CdrOE-k50FH3x7mDWrbdqG~ZEDEg6wmhZmlMquZAMKiIkeWh6X2olO9k5raauSRlZwHKYYH-dUBOEBDty91GC5jxE~Rp-~Eeu-XicMtCyu7qc8DKC14TZ8cK~bpKtEvZibX0nROybXIrTqKL9o7u58Q__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Image_Parsing_Mechanisms_of_the_Visual_Cortex","translated_slug":"","page_count":25,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[{"id":75586503,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/75586503/thumbnails/1.jpg","file_name":"vonderHeydt_2004.pdf","download_url":"https://www.academia.edu/attachments/75586503/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&st=MTczMjc4MTY3Nyw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Image_Parsing_Mechanisms_of_the_Visual_C.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/75586503/vonderHeydt_2004-libre.pdf?1638479536=\u0026response-content-disposition=attachment%3B+filename%3DImage_Parsing_Mechanisms_of_the_Visual_C.pdf\u0026Expires=1732785277\u0026Signature=b1OhZNJxcaRbYAI4x~tAqJQo2dwm90Hzm7cPxyxep0lIjAYAOpiK2VhwxTai~YPIZI5MDZrVFxsKId06TdWRKVJp74nUs3Vh-qGP3623n8u6CMAn7HOx-TCoMm4ZPHJ5LbtK8pqzsm~lBt301wPrPI1bx7ByrqhEMSq9deYX11OUF61bkwgRTukdB3cnvf6CdrOE-k50FH3x7mDWrbdqG~ZEDEg6wmhZmlMquZAMKiIkeWh6X2olO9k5raauSRlZwHKYYH-dUBOEBDty91GC5jxE~Rp-~Eeu-XicMtCyu7qc8DKC14TZ8cK~bpKtEvZibX0nROybXIrTqKL9o7u58Q__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":49962,"name":"Visual Cortex","url":"https://www.academia.edu/Documents/in/Visual_Cortex"}],"urls":[{"id":14713528,"url":"http://www.stat.ucla.edu/~yuille/courses/Stat271-Fall13/VonderHeydt_ImageParsing_neuroscience.pdf"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="57633070"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/57633070/Representation_and_Remapping_of_Occluded_Objects_in_the_Activity_of_V4"><img alt="Research paper thumbnail of Representation and Remapping of Occluded Objects in the Activity of V4" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/57633070/Representation_and_Remapping_of_Occluded_Objects_in_the_Activity_of_V4">Representation and Remapping of Occluded Objects in the Activity of V4</a></div><div class="wp-workCard_item"><span>Journal of Vision</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="57633070"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="57633070"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 57633070; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=57633070]").text(description); $(".js-view-count[data-work-id=57633070]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 57633070; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='57633070']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 57633070, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=57633070]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":57633070,"title":"Representation and Remapping of Occluded Objects in the Activity of V4","translated_title":"","metadata":{"publisher":"Association for Research in Vision and Ophthalmology (ARVO)","publication_name":"Journal of Vision"},"translated_abstract":null,"internal_url":"https://www.academia.edu/57633070/Representation_and_Remapping_of_Occluded_Objects_in_the_Activity_of_V4","translated_internal_url":"","created_at":"2021-10-13T16:27:05.364-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Representation_and_Remapping_of_Occluded_Objects_in_the_Activity_of_V4","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[],"research_interests":[{"id":59692,"name":"Vision","url":"https://www.academia.edu/Documents/in/Vision"},{"id":2922956,"name":"Psychology and Cognitive Sciences","url":"https://www.academia.edu/Documents/in/Psychology_and_Cognitive_Sciences"},{"id":3763225,"name":"Medical and Health Sciences","url":"https://www.academia.edu/Documents/in/Medical_and_Health_Sciences"}],"urls":[{"id":12933319,"url":"http://jov.arvojournals.org/article.aspx?articleid=2700038"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="57633069"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/57633069/Figure_and_Ground_How_the_Visual_Cortex_Integrates_Local_Cues_for_Global_Organization"><img alt="Research paper thumbnail of Figure and Ground: How the Visual Cortex Integrates Local Cues for Global Organization" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/57633069/Figure_and_Ground_How_the_Visual_Cortex_Integrates_Local_Cues_for_Global_Organization">Figure and Ground: How the Visual Cortex Integrates Local Cues for Global Organization</a></div><div class="wp-workCard_item"><span>Journal of neurophysiology</span><span>, Jan 25, 2018</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Inferring figure-ground organization in 2-dimensional images may require different complementary ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Inferring figure-ground organization in 2-dimensional images may require different complementary strategies. For isolated objects it has been shown that mechanisms in visual cortex exploit the overall distribution of contours, but in images of cluttered scenes where the grouping of contours is not obvious that strategy would fail. However, natural scenes contain local features, specifically contour junctions, that may contribute to the definition of object regions. To study the role of local features in the assignment of border ownership we recorded single-cell activity from visual cortex in awake behaving Macaca mulatta. We tested configurations perceived as two overlapping figures in which T- and L-junctions depend on the direction of overlap, while the overall distribution of contours provides no valid information. While recording responses to the occluding contour we varied direction of overlap and variably masked some of the critical contour features to determine their influenc...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="57633069"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="57633069"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 57633069; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=57633069]").text(description); $(".js-view-count[data-work-id=57633069]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 57633069; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='57633069']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 57633069, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=57633069]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":57633069,"title":"Figure and Ground: How the Visual Cortex Integrates Local Cues for Global Organization","translated_title":"","metadata":{"abstract":"Inferring figure-ground organization in 2-dimensional images may require different complementary strategies. For isolated objects it has been shown that mechanisms in visual cortex exploit the overall distribution of contours, but in images of cluttered scenes where the grouping of contours is not obvious that strategy would fail. However, natural scenes contain local features, specifically contour junctions, that may contribute to the definition of object regions. To study the role of local features in the assignment of border ownership we recorded single-cell activity from visual cortex in awake behaving Macaca mulatta. We tested configurations perceived as two overlapping figures in which T- and L-junctions depend on the direction of overlap, while the overall distribution of contours provides no valid information. While recording responses to the occluding contour we varied direction of overlap and variably masked some of the critical contour features to determine their influenc...","publication_date":{"day":25,"month":1,"year":2018,"errors":{}},"publication_name":"Journal of neurophysiology"},"translated_abstract":"Inferring figure-ground organization in 2-dimensional images may require different complementary strategies. For isolated objects it has been shown that mechanisms in visual cortex exploit the overall distribution of contours, but in images of cluttered scenes where the grouping of contours is not obvious that strategy would fail. However, natural scenes contain local features, specifically contour junctions, that may contribute to the definition of object regions. To study the role of local features in the assignment of border ownership we recorded single-cell activity from visual cortex in awake behaving Macaca mulatta. We tested configurations perceived as two overlapping figures in which T- and L-junctions depend on the direction of overlap, while the overall distribution of contours provides no valid information. While recording responses to the occluding contour we varied direction of overlap and variably masked some of the critical contour features to determine their influenc...","internal_url":"https://www.academia.edu/57633069/Figure_and_Ground_How_the_Visual_Cortex_Integrates_Local_Cues_for_Global_Organization","translated_internal_url":"","created_at":"2021-10-13T16:27:05.294-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Figure_and_Ground_How_the_Visual_Cortex_Integrates_Local_Cues_for_Global_Organization","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[],"research_interests":[{"id":22272,"name":"Neurophysiology","url":"https://www.academia.edu/Documents/in/Neurophysiology"},{"id":2922956,"name":"Psychology and Cognitive Sciences","url":"https://www.academia.edu/Documents/in/Psychology_and_Cognitive_Sciences"},{"id":3763225,"name":"Medical and Health Sciences","url":"https://www.academia.edu/Documents/in/Medical_and_Health_Sciences"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="57633068"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/57633068/The_role_of_horizontal_connections_for_the_modulation_of_border_ownership_selective_neurons_in_visual_cortex"><img alt="Research paper thumbnail of The role of horizontal connections for the modulation of border-ownership selective neurons in visual cortex" class="work-thumbnail" src="https://attachments.academia-assets.com/72439280/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/57633068/The_role_of_horizontal_connections_for_the_modulation_of_border_ownership_selective_neurons_in_visual_cortex">The role of horizontal connections for the modulation of border-ownership selective neurons in visual cortex</a></div><div class="wp-workCard_item"><span>BMC Neuroscience</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="9628f259331ff0e42e8ab6196e3e7298" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":72439280,"asset_id":57633068,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/72439280/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="57633068"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="57633068"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 57633068; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=57633068]").text(description); $(".js-view-count[data-work-id=57633068]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 57633068; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='57633068']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 57633068, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "9628f259331ff0e42e8ab6196e3e7298" } } $('.js-work-strip[data-work-id=57633068]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":57633068,"title":"The role of horizontal connections for the modulation of border-ownership selective neurons in visual cortex","translated_title":"","metadata":{"publisher":"Springer Nature","publication_name":"BMC Neuroscience"},"translated_abstract":null,"internal_url":"https://www.academia.edu/57633068/The_role_of_horizontal_connections_for_the_modulation_of_border_ownership_selective_neurons_in_visual_cortex","translated_internal_url":"","created_at":"2021-10-13T16:27:05.215-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":72439280,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/72439280/thumbnails/1.jpg","file_name":"pmc4697632.pdf","download_url":"https://www.academia.edu/attachments/72439280/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"The_role_of_horizontal_connections_for_t.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/72439280/pmc4697632-libre.pdf?1634272357=\u0026response-content-disposition=attachment%3B+filename%3DThe_role_of_horizontal_connections_for_t.pdf\u0026Expires=1732785278\u0026Signature=J42zLPMtZhxDbFjl~173RHIllBCKcRq4pEAijrIpTUOIQYmQKGNlcMnE-bEpzS-RrrGadmGSQNX4t-r0eeKiHcRSFjn3dD2QWa76br2QdIgt5ugh0Hdyb5~hs~GIc4Hg69uCXFMAFS50Vzrvur6KEMfV7fodmUnOnLNfTo7150OaG9yyMnAaxEaiEuu8fxjEnGn3hHwtm~RsYBf8EKdHpf48A8HBvb2FgQ6H7gaKpAu2Lh4SsNs9e5FMBIvQXFRcxbE3eqUZd0zv8xeC5Fc7FLGIPsNn8DSugU6gcGVu1pWVNvg8MTwyCWxO0Jh39DqvvquKDY7lo4PmkP1-hysf~A__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"The_role_of_horizontal_connections_for_the_modulation_of_border_ownership_selective_neurons_in_visual_cortex","translated_slug":"","page_count":2,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[{"id":72439280,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/72439280/thumbnails/1.jpg","file_name":"pmc4697632.pdf","download_url":"https://www.academia.edu/attachments/72439280/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"The_role_of_horizontal_connections_for_t.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/72439280/pmc4697632-libre.pdf?1634272357=\u0026response-content-disposition=attachment%3B+filename%3DThe_role_of_horizontal_connections_for_t.pdf\u0026Expires=1732785278\u0026Signature=J42zLPMtZhxDbFjl~173RHIllBCKcRq4pEAijrIpTUOIQYmQKGNlcMnE-bEpzS-RrrGadmGSQNX4t-r0eeKiHcRSFjn3dD2QWa76br2QdIgt5ugh0Hdyb5~hs~GIc4Hg69uCXFMAFS50Vzrvur6KEMfV7fodmUnOnLNfTo7150OaG9yyMnAaxEaiEuu8fxjEnGn3hHwtm~RsYBf8EKdHpf48A8HBvb2FgQ6H7gaKpAu2Lh4SsNs9e5FMBIvQXFRcxbE3eqUZd0zv8xeC5Fc7FLGIPsNn8DSugU6gcGVu1pWVNvg8MTwyCWxO0Jh39DqvvquKDY7lo4PmkP1-hysf~A__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":237,"name":"Cognitive Science","url":"https://www.academia.edu/Documents/in/Cognitive_Science"},{"id":1239755,"name":"Neurosciences","url":"https://www.academia.edu/Documents/in/Neurosciences"},{"id":1681026,"name":"Biochemistry and cell biology","url":"https://www.academia.edu/Documents/in/Biochemistry_and_cell_biology"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="57633066"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/57633066/Can_the_visual_cortex_represent_the_invisible"><img alt="Research paper thumbnail of Can the visual cortex represent the invisible?" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/57633066/Can_the_visual_cortex_represent_the_invisible">Can the visual cortex represent the invisible?</a></div><div class="wp-workCard_item"><span>Journal of Vision</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="57633066"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="57633066"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 57633066; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=57633066]").text(description); $(".js-view-count[data-work-id=57633066]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 57633066; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='57633066']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 57633066, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=57633066]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":57633066,"title":"Can the visual cortex represent the invisible?","translated_title":"","metadata":{"publisher":"Association for Research in Vision and Ophthalmology (ARVO)","publication_name":"Journal of Vision"},"translated_abstract":null,"internal_url":"https://www.academia.edu/57633066/Can_the_visual_cortex_represent_the_invisible","translated_internal_url":"","created_at":"2021-10-13T16:27:05.100-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Can_the_visual_cortex_represent_the_invisible","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[],"research_interests":[{"id":59692,"name":"Vision","url":"https://www.academia.edu/Documents/in/Vision"},{"id":2922956,"name":"Psychology and Cognitive Sciences","url":"https://www.academia.edu/Documents/in/Psychology_and_Cognitive_Sciences"},{"id":3763225,"name":"Medical and Health Sciences","url":"https://www.academia.edu/Documents/in/Medical_and_Health_Sciences"}],"urls":[{"id":12933317,"url":"http://jov.arvojournals.org/article.aspx?doi=10.1167/17.10.348"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="57633065"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/57633065/Selectivity_for_structural_depth_in_neurons_of_monkey_area_V2"><img alt="Research paper thumbnail of Selectivity for structural depth in neurons of monkey area V2" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/57633065/Selectivity_for_structural_depth_in_neurons_of_monkey_area_V2">Selectivity for structural depth in neurons of monkey area V2</a></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="57633065"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="57633065"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 57633065; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=57633065]").text(description); $(".js-view-count[data-work-id=57633065]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 57633065; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='57633065']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 57633065, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=57633065]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":57633065,"title":"Selectivity for structural depth in neurons of monkey area V2","translated_title":"","metadata":{"publication_date":{"day":null,"month":null,"year":2000,"errors":{}}},"translated_abstract":null,"internal_url":"https://www.academia.edu/57633065/Selectivity_for_structural_depth_in_neurons_of_monkey_area_V2","translated_internal_url":"","created_at":"2021-10-13T16:27:05.009-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Selectivity_for_structural_depth_in_neurons_of_monkey_area_V2","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[],"research_interests":[],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="57633064"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/57633064/Detektion_von_ein_und_zwei_dimensionalen_Bildstrukturen_in_komplexen_Grauwertbildern"><img alt="Research paper thumbnail of Detektion von ein- und zwei-dimensionalen Bildstrukturen in komplexen Grauwertbildern" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/57633064/Detektion_von_ein_und_zwei_dimensionalen_Bildstrukturen_in_komplexen_Grauwertbildern">Detektion von ein- und zwei-dimensionalen Bildstrukturen in komplexen Grauwertbildern</a></div><div class="wp-workCard_item"><span>DAGM Symposium Symposium for Pattern Recognition</span><span>, 1992</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="57633064"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="57633064"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 57633064; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=57633064]").text(description); $(".js-view-count[data-work-id=57633064]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 57633064; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='57633064']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 57633064, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=57633064]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":57633064,"title":"Detektion von ein- und zwei-dimensionalen Bildstrukturen in komplexen Grauwertbildern","translated_title":"","metadata":{"publication_date":{"day":null,"month":null,"year":1992,"errors":{}},"publication_name":"DAGM Symposium Symposium for Pattern Recognition"},"translated_abstract":null,"internal_url":"https://www.academia.edu/57633064/Detektion_von_ein_und_zwei_dimensionalen_Bildstrukturen_in_komplexen_Grauwertbildern","translated_internal_url":"","created_at":"2021-10-13T16:27:04.904-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Detektion_von_ein_und_zwei_dimensionalen_Bildstrukturen_in_komplexen_Grauwertbildern","translated_slug":"","page_count":null,"language":"de","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[],"research_interests":[],"urls":[{"id":12933316,"url":"http://www.informatik.uni-trier.de/~ley/db/conf/dagm/dagm1992.html#RosenthalerHKH92"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="57633063"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/57633063/Mechanism_of_contours_in_monkey_visual_cortex_I_Lines_of_pattern_discontinuity"><img alt="Research paper thumbnail of Mechanism of contours in monkey visual cortex. I. Lines of pattern discontinuity" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/57633063/Mechanism_of_contours_in_monkey_visual_cortex_I_Lines_of_pattern_discontinuity">Mechanism of contours in monkey visual cortex. I. Lines of pattern discontinuity</a></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="57633063"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="57633063"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 57633063; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=57633063]").text(description); $(".js-view-count[data-work-id=57633063]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 57633063; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='57633063']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 57633063, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=57633063]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":57633063,"title":"Mechanism of contours in monkey visual cortex. I. Lines of pattern discontinuity","translated_title":"","metadata":{"publication_date":{"day":null,"month":null,"year":1989,"errors":{}}},"translated_abstract":null,"internal_url":"https://www.academia.edu/57633063/Mechanism_of_contours_in_monkey_visual_cortex_I_Lines_of_pattern_discontinuity","translated_internal_url":"","created_at":"2021-10-13T16:27:04.841-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Mechanism_of_contours_in_monkey_visual_cortex_I_Lines_of_pattern_discontinuity","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[],"research_interests":[],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="57633062"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/57633062/Visual_selectivity_and_top_down_modulation_of_neurons_in_monkey_V2_during_free_viewing"><img alt="Research paper thumbnail of Visual selectivity and top-down modulation of neurons in monkey V2 during free viewing" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/57633062/Visual_selectivity_and_top_down_modulation_of_neurons_in_monkey_V2_during_free_viewing">Visual selectivity and top-down modulation of neurons in monkey V2 during free viewing</a></div><div class="wp-workCard_item"><span>Journal of vision</span><span>, 2015</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Neurons in early visual cortex are selective for local visual features but their responses can al...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Neurons in early visual cortex are selective for local visual features but their responses can also be influenced by factors like border ownership and selective attention. Most of what we know about the function of these neurons is based on neurophysiological studies in monkeys that hold their direction of gaze fixed while isolated visual stimuli are presented (controlled viewing). However, during natural behavior, primates visually explore cluttered environments by changing gaze direction several times each second (free viewing). How does the visual cortex work under these conditions? We explored neuronal responses using a foraging task in which the monkey chooses where to look and when. Geometrical figures were displayed and the monkey was rewarded for fixating the center of a figure for at least 200ms. In each trial an array of 10 figures (5 squares and 5 triangles) was presented, one of which was randomly associated with reward, and a cue informed the monkey whether it was a squ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="57633062"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="57633062"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 57633062; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=57633062]").text(description); $(".js-view-count[data-work-id=57633062]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 57633062; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='57633062']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 57633062, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=57633062]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":57633062,"title":"Visual selectivity and top-down modulation of neurons in monkey V2 during free viewing","translated_title":"","metadata":{"abstract":"Neurons in early visual cortex are selective for local visual features but their responses can also be influenced by factors like border ownership and selective attention. Most of what we know about the function of these neurons is based on neurophysiological studies in monkeys that hold their direction of gaze fixed while isolated visual stimuli are presented (controlled viewing). However, during natural behavior, primates visually explore cluttered environments by changing gaze direction several times each second (free viewing). How does the visual cortex work under these conditions? We explored neuronal responses using a foraging task in which the monkey chooses where to look and when. Geometrical figures were displayed and the monkey was rewarded for fixating the center of a figure for at least 200ms. In each trial an array of 10 figures (5 squares and 5 triangles) was presented, one of which was randomly associated with reward, and a cue informed the monkey whether it was a squ...","publication_date":{"day":null,"month":null,"year":2015,"errors":{}},"publication_name":"Journal of vision"},"translated_abstract":"Neurons in early visual cortex are selective for local visual features but their responses can also be influenced by factors like border ownership and selective attention. Most of what we know about the function of these neurons is based on neurophysiological studies in monkeys that hold their direction of gaze fixed while isolated visual stimuli are presented (controlled viewing). However, during natural behavior, primates visually explore cluttered environments by changing gaze direction several times each second (free viewing). How does the visual cortex work under these conditions? We explored neuronal responses using a foraging task in which the monkey chooses where to look and when. Geometrical figures were displayed and the monkey was rewarded for fixating the center of a figure for at least 200ms. In each trial an array of 10 figures (5 squares and 5 triangles) was presented, one of which was randomly associated with reward, and a cue informed the monkey whether it was a squ...","internal_url":"https://www.academia.edu/57633062/Visual_selectivity_and_top_down_modulation_of_neurons_in_monkey_V2_during_free_viewing","translated_internal_url":"","created_at":"2021-10-13T16:27:04.761-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Visual_selectivity_and_top_down_modulation_of_neurons_in_monkey_V2_during_free_viewing","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[],"research_interests":[{"id":59692,"name":"Vision","url":"https://www.academia.edu/Documents/in/Vision"},{"id":2922956,"name":"Psychology and Cognitive Sciences","url":"https://www.academia.edu/Documents/in/Psychology_and_Cognitive_Sciences"},{"id":3763225,"name":"Medical and Health Sciences","url":"https://www.academia.edu/Documents/in/Medical_and_Health_Sciences"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="57633061"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/57633061/Spike_synchrony_reveals_emergence_of_proto_objects_in_visual_cortex"><img alt="Research paper thumbnail of Spike synchrony reveals emergence of proto-objects in visual cortex" class="work-thumbnail" src="https://attachments.academia-assets.com/72439287/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/57633061/Spike_synchrony_reveals_emergence_of_proto_objects_in_visual_cortex">Spike synchrony reveals emergence of proto-objects in visual cortex</a></div><div class="wp-workCard_item"><span>The Journal of neuroscience : the official journal of the Society for Neuroscience</span><span>, Jan 29, 2015</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Neurons at early stages of the visual cortex signal elemental features, such as pieces of contour...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Neurons at early stages of the visual cortex signal elemental features, such as pieces of contour, but how these signals are organized into perceptual objects is unclear. Theories have proposed that spiking synchrony between these neurons encodes how features are grouped (binding-by-synchrony), but recent studies did not find the predicted increase in synchrony with binding. Here we propose that features are grouped to &quot;proto-objects&quot; by intrinsic feedback circuits that enhance the responses of the participating feature neurons. This hypothesis predicts synchrony exclusively between feature neurons that receive feedback from the same grouping circuit. We recorded from neurons in macaque visual cortex and used border-ownership selectivity, an intrinsic property of the neurons, to infer whether or not two neurons are part of the same grouping circuit. We found that binding produced synchrony between same-circuit neurons, but not between other pairs of neurons, as predicted b...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="669d1a19faba2fbaecb8e1c0cd5286c1" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":72439287,"asset_id":57633061,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/72439287/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="57633061"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="57633061"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 57633061; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=57633061]").text(description); $(".js-view-count[data-work-id=57633061]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 57633061; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='57633061']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 57633061, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "669d1a19faba2fbaecb8e1c0cd5286c1" } } $('.js-work-strip[data-work-id=57633061]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":57633061,"title":"Spike synchrony reveals emergence of proto-objects in visual cortex","translated_title":"","metadata":{"abstract":"Neurons at early stages of the visual cortex signal elemental features, such as pieces of contour, but how these signals are organized into perceptual objects is unclear. Theories have proposed that spiking synchrony between these neurons encodes how features are grouped (binding-by-synchrony), but recent studies did not find the predicted increase in synchrony with binding. Here we propose that features are grouped to \u0026quot;proto-objects\u0026quot; by intrinsic feedback circuits that enhance the responses of the participating feature neurons. This hypothesis predicts synchrony exclusively between feature neurons that receive feedback from the same grouping circuit. We recorded from neurons in macaque visual cortex and used border-ownership selectivity, an intrinsic property of the neurons, to infer whether or not two neurons are part of the same grouping circuit. We found that binding produced synchrony between same-circuit neurons, but not between other pairs of neurons, as predicted b...","publication_date":{"day":29,"month":1,"year":2015,"errors":{}},"publication_name":"The Journal of neuroscience : the official journal of the Society for Neuroscience"},"translated_abstract":"Neurons at early stages of the visual cortex signal elemental features, such as pieces of contour, but how these signals are organized into perceptual objects is unclear. Theories have proposed that spiking synchrony between these neurons encodes how features are grouped (binding-by-synchrony), but recent studies did not find the predicted increase in synchrony with binding. Here we propose that features are grouped to \u0026quot;proto-objects\u0026quot; by intrinsic feedback circuits that enhance the responses of the participating feature neurons. This hypothesis predicts synchrony exclusively between feature neurons that receive feedback from the same grouping circuit. We recorded from neurons in macaque visual cortex and used border-ownership selectivity, an intrinsic property of the neurons, to infer whether or not two neurons are part of the same grouping circuit. We found that binding produced synchrony between same-circuit neurons, but not between other pairs of neurons, as predicted b...","internal_url":"https://www.academia.edu/57633061/Spike_synchrony_reveals_emergence_of_proto_objects_in_visual_cortex","translated_internal_url":"","created_at":"2021-10-13T16:27:04.690-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":72439287,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/72439287/thumbnails/1.jpg","file_name":"6860.full.pdf","download_url":"https://www.academia.edu/attachments/72439287/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Spike_synchrony_reveals_emergence_of_pro.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/72439287/6860.full-libre.pdf?1634272359=\u0026response-content-disposition=attachment%3B+filename%3DSpike_synchrony_reveals_emergence_of_pro.pdf\u0026Expires=1732785278\u0026Signature=ctlIM4-Y~8cNdNuDhtK1OHs2ZDRwpwHp1SNfPH7yaqWI-w5HQVgDy~LRl69~vKL2gxaIrL-ROxDUm~QTFGSVAZe4dxT5CQXjUtekdEVPs-jtkJDppCiIKkOIn2w0hbeEqklVoWQYkptH5Fs7JBFxXU~m776iNbZRA3q5NaHJFLAF89Fz446sLGVrwp9ldJShkclvjONXFSrBdVnmnd4Z3zvVoK22YFnhK0GpgJe49whnDEVq59X4q1dZESMuG7Z3bvWl-J7E43fdBpK4I94IcDpvHaRvWB8TXWehqVWZEYJRw1~RGaCzU4Q7If4DB2mOmFEauGorbQq~4-ndJY7Dsg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Spike_synchrony_reveals_emergence_of_proto_objects_in_visual_cortex","translated_slug":"","page_count":11,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[{"id":72439287,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/72439287/thumbnails/1.jpg","file_name":"6860.full.pdf","download_url":"https://www.academia.edu/attachments/72439287/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Spike_synchrony_reveals_emergence_of_pro.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/72439287/6860.full-libre.pdf?1634272359=\u0026response-content-disposition=attachment%3B+filename%3DSpike_synchrony_reveals_emergence_of_pro.pdf\u0026Expires=1732785278\u0026Signature=ctlIM4-Y~8cNdNuDhtK1OHs2ZDRwpwHp1SNfPH7yaqWI-w5HQVgDy~LRl69~vKL2gxaIrL-ROxDUm~QTFGSVAZe4dxT5CQXjUtekdEVPs-jtkJDppCiIKkOIn2w0hbeEqklVoWQYkptH5Fs7JBFxXU~m776iNbZRA3q5NaHJFLAF89Fz446sLGVrwp9ldJShkclvjONXFSrBdVnmnd4Z3zvVoK22YFnhK0GpgJe49whnDEVq59X4q1dZESMuG7Z3bvWl-J7E43fdBpK4I94IcDpvHaRvWB8TXWehqVWZEYJRw1~RGaCzU4Q7If4DB2mOmFEauGorbQq~4-ndJY7Dsg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":161,"name":"Neuroscience","url":"https://www.academia.edu/Documents/in/Neuroscience"},{"id":7736,"name":"Attention","url":"https://www.academia.edu/Documents/in/Attention"},{"id":49962,"name":"Visual Cortex","url":"https://www.academia.edu/Documents/in/Visual_Cortex"},{"id":82283,"name":"Form perception","url":"https://www.academia.edu/Documents/in/Form_perception"},{"id":119665,"name":"Reaction Time","url":"https://www.academia.edu/Documents/in/Reaction_Time"},{"id":143507,"name":"Eye Movements","url":"https://www.academia.edu/Documents/in/Eye_Movements"},{"id":193974,"name":"Neurons","url":"https://www.academia.edu/Documents/in/Neurons"},{"id":386773,"name":"Sensory Feedback","url":"https://www.academia.edu/Documents/in/Sensory_Feedback"},{"id":573267,"name":"Macaca Mulatta","url":"https://www.academia.edu/Documents/in/Macaca_Mulatta"},{"id":955727,"name":"Action Potentials","url":"https://www.academia.edu/Documents/in/Action_Potentials"},{"id":968586,"name":"Visual Evoked Potentials","url":"https://www.academia.edu/Documents/in/Visual_Evoked_Potentials"},{"id":2463496,"name":"Statistics as Topic","url":"https://www.academia.edu/Documents/in/Statistics_as_Topic"},{"id":2849038,"name":"photic stimulation","url":"https://www.academia.edu/Documents/in/photic_stimulation"},{"id":2922956,"name":"Psychology and Cognitive Sciences","url":"https://www.academia.edu/Documents/in/Psychology_and_Cognitive_Sciences"},{"id":3763225,"name":"Medical and Health Sciences","url":"https://www.academia.edu/Documents/in/Medical_and_Health_Sciences"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="57633060"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/57633060/A_neural_model_for_perceptual_organization_of_3D_surfaces"><img alt="Research paper thumbnail of A neural model for perceptual organization of 3D surfaces" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/57633060/A_neural_model_for_perceptual_organization_of_3D_surfaces">A neural model for perceptual organization of 3D surfaces</a></div><div class="wp-workCard_item"><span>2015 49th Annual Conference on Information Sciences and Systems (CISS)</span><span>, 2015</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="57633060"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="57633060"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 57633060; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=57633060]").text(description); $(".js-view-count[data-work-id=57633060]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 57633060; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='57633060']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 57633060, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=57633060]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":57633060,"title":"A neural model for perceptual organization of 3D surfaces","translated_title":"","metadata":{"publisher":"IEEE","publication_date":{"day":null,"month":null,"year":2015,"errors":{}},"publication_name":"2015 49th Annual Conference on Information Sciences and Systems (CISS)"},"translated_abstract":null,"internal_url":"https://www.academia.edu/57633060/A_neural_model_for_perceptual_organization_of_3D_surfaces","translated_internal_url":"","created_at":"2021-10-13T16:27:04.618-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"A_neural_model_for_perceptual_organization_of_3D_surfaces","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[],"research_interests":[],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="57633059"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/57633059/Detektion_von_ein_und_zwei_dimensionalen_Bildstrukturen_in_komplexen_Grauwertbildern"><img alt="Research paper thumbnail of Detektion von ein- und zwei-dimensionalen Bildstrukturen in komplexen Grauwertbildern" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/57633059/Detektion_von_ein_und_zwei_dimensionalen_Bildstrukturen_in_komplexen_Grauwertbildern">Detektion von ein- und zwei-dimensionalen Bildstrukturen in komplexen Grauwertbildern</a></div><div class="wp-workCard_item"><span>Informatik aktuell</span><span>, 1992</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="57633059"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="57633059"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 57633059; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=57633059]").text(description); $(".js-view-count[data-work-id=57633059]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 57633059; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='57633059']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 57633059, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=57633059]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":57633059,"title":"Detektion von ein- und zwei-dimensionalen Bildstrukturen in komplexen Grauwertbildern","translated_title":"","metadata":{"publication_date":{"day":null,"month":null,"year":1992,"errors":{}},"publication_name":"Informatik aktuell"},"translated_abstract":null,"internal_url":"https://www.academia.edu/57633059/Detektion_von_ein_und_zwei_dimensionalen_Bildstrukturen_in_komplexen_Grauwertbildern","translated_internal_url":"","created_at":"2021-10-13T16:27:04.549-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Detektion_von_ein_und_zwei_dimensionalen_Bildstrukturen_in_komplexen_Grauwertbildern","translated_slug":"","page_count":null,"language":"de","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[],"research_interests":[],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="57633058"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/57633058/Searching_for_the_Neural_Mechanism_of_Color_Filling_In"><img alt="Research paper thumbnail of Searching for the Neural Mechanism of Color Filling-In" class="work-thumbnail" src="https://attachments.academia-assets.com/72439393/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/57633058/Searching_for_the_Neural_Mechanism_of_Color_Filling_In">Searching for the Neural Mechanism of Color Filling-In</a></div><div class="wp-workCard_item"><span>Filling-In</span><span>, 2003</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="54c3fc56f6690f116b7b8cc096943eef" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":72439393,"asset_id":57633058,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/72439393/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="57633058"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="57633058"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 57633058; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=57633058]").text(description); $(".js-view-count[data-work-id=57633058]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 57633058; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='57633058']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 57633058, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "54c3fc56f6690f116b7b8cc096943eef" } } $('.js-work-strip[data-work-id=57633058]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":57633058,"title":"Searching for the Neural Mechanism of Color Filling-In","translated_title":"","metadata":{"publisher":"Oxford University Press","publication_date":{"day":null,"month":null,"year":2003,"errors":{}},"publication_name":"Filling-In"},"translated_abstract":null,"internal_url":"https://www.academia.edu/57633058/Searching_for_the_Neural_Mechanism_of_Color_Filling_In","translated_internal_url":"","created_at":"2021-10-13T16:27:04.476-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[{"id":72439393,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/72439393/thumbnails/1.jpg","file_name":"59ae5f250011fec59722c0768a78a7a937a2.pdf","download_url":"https://www.academia.edu/attachments/72439393/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Searching_for_the_Neural_Mechanism_of_Co.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/72439393/59ae5f250011fec59722c0768a78a7a937a2-libre.pdf?1634272353=\u0026response-content-disposition=attachment%3B+filename%3DSearching_for_the_Neural_Mechanism_of_Co.pdf\u0026Expires=1732785278\u0026Signature=JVjBTCa~eEw8TA~ZjC0YGa9ZVRL6pMaBg1zXNrUgnX2Hl2-8t065V1Dg-aGTNAfCrcd6F0PEvvXF1dcYvy19f67d7HaTvSy~xqYtP4CjhMUmd4zJxYV9hnpWHyYMD42Sl6-NlgBqH-8p9LO9SIy5Y7bvKnnc5q0~7wPJaPWbSEtWgDG8Y38gpTZGOmhRAg8douzscpGguFJRLh7Eerh4ZYbtpOvq89sQ9dPaSFxTSlsdDwQKh1e9IRtO7wYMKp51MyoVvtxBdc0TAylesWMtz4butVXCY6bNL~8~s1qebTpwDG-z08GHRzFLXRjYP6bwUYpr0LlX24yAzQYb2wZnoA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"slug":"Searching_for_the_Neural_Mechanism_of_Color_Filling_In","translated_slug":"","page_count":28,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[{"id":72439393,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/72439393/thumbnails/1.jpg","file_name":"59ae5f250011fec59722c0768a78a7a937a2.pdf","download_url":"https://www.academia.edu/attachments/72439393/download_file?st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&st=MTczMjc4MTY3OCw4LjIyMi4yMDguMTQ2&","bulk_download_file_name":"Searching_for_the_Neural_Mechanism_of_Co.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/72439393/59ae5f250011fec59722c0768a78a7a937a2-libre.pdf?1634272353=\u0026response-content-disposition=attachment%3B+filename%3DSearching_for_the_Neural_Mechanism_of_Co.pdf\u0026Expires=1732785278\u0026Signature=JVjBTCa~eEw8TA~ZjC0YGa9ZVRL6pMaBg1zXNrUgnX2Hl2-8t065V1Dg-aGTNAfCrcd6F0PEvvXF1dcYvy19f67d7HaTvSy~xqYtP4CjhMUmd4zJxYV9hnpWHyYMD42Sl6-NlgBqH-8p9LO9SIy5Y7bvKnnc5q0~7wPJaPWbSEtWgDG8Y38gpTZGOmhRAg8douzscpGguFJRLh7Eerh4ZYbtpOvq89sQ9dPaSFxTSlsdDwQKh1e9IRtO7wYMKp51MyoVvtxBdc0TAylesWMtz4butVXCY6bNL~8~s1qebTpwDG-z08GHRzFLXRjYP6bwUYpr0LlX24yAzQYb2wZnoA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}],"research_interests":[{"id":624348,"name":"Filling","url":"https://www.academia.edu/Documents/in/Filling"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="57633057"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/57633057/Form_Perception_and_Attention"><img alt="Research paper thumbnail of Form Perception and Attention" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/57633057/Form_Perception_and_Attention">Form Perception and Attention</a></div><div class="wp-workCard_item"><span>Visual Perception</span><span>, 1990</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="57633057"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="57633057"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 57633057; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=57633057]").text(description); $(".js-view-count[data-work-id=57633057]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 57633057; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='57633057']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 57633057, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=57633057]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":57633057,"title":"Form Perception and Attention","translated_title":"","metadata":{"publication_date":{"day":null,"month":null,"year":1990,"errors":{}},"publication_name":"Visual Perception"},"translated_abstract":null,"internal_url":"https://www.academia.edu/57633057/Form_Perception_and_Attention","translated_internal_url":"","created_at":"2021-10-13T16:27:04.375-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":99283352,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Form_Perception_and_Attention","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":99283352,"first_name":"RUDIGER","middle_initials":null,"last_name":"VONDERHEYDT","page_name":"RUDIGERVONDERHEYDT","domain_name":"johnshopkins","created_at":"2018-12-17T11:05:52.842-08:00","display_name":"RUDIGER VONDERHEYDT","url":"https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT"},"attachments":[],"research_interests":[{"id":5359,"name":"Visual perception","url":"https://www.academia.edu/Documents/in/Visual_perception"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> </div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/google_contacts-0dfb882d836b94dbcb4a2d123d6933fc9533eda5be911641f20b4eb428429600.js"], function() { // from javascript_helper.rb $('.js-google-connect-button').click(function(e) { e.preventDefault(); GoogleContacts.authorize_and_show_contacts(); Aedu.Dismissibles.recordClickthrough("WowProfileImportContactsPrompt"); }); $('.js-update-biography-button').click(function(e) { e.preventDefault(); Aedu.Dismissibles.recordClickthrough("UpdateUserBiographyPrompt"); $.ajax({ url: $r.api_v0_profiles_update_about_path({ subdomain_param: 'api', about: "", }), type: 'PUT', success: function(response) { location.reload(); } }); }); $('.js-work-creator-button').click(function (e) { e.preventDefault(); window.location = $r.upload_funnel_document_path({ source: encodeURIComponent(""), }); }); $('.js-video-upload-button').click(function (e) { e.preventDefault(); window.location = $r.upload_funnel_video_path({ source: encodeURIComponent(""), }); }); $('.js-do-this-later-button').click(function() { $(this).closest('.js-profile-nag-panel').remove(); Aedu.Dismissibles.recordDismissal("WowProfileImportContactsPrompt"); }); $('.js-update-biography-do-this-later-button').click(function(){ $(this).closest('.js-profile-nag-panel').remove(); Aedu.Dismissibles.recordDismissal("UpdateUserBiographyPrompt"); }); $('.wow-profile-mentions-upsell--close').click(function(){ $('.wow-profile-mentions-upsell--panel').hide(); Aedu.Dismissibles.recordDismissal("WowProfileMentionsUpsell"); }); $('.wow-profile-mentions-upsell--button').click(function(){ Aedu.Dismissibles.recordClickthrough("WowProfileMentionsUpsell"); }); new WowProfile.SocialRedesignUserWorks({ initialWorksOffset: 20, allWorksOffset: 20, maxSections: 1 }) }); </script> </div></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile_edit-5ea339ee107c863779f560dd7275595239fed73f1a13d279d2b599a28c0ecd33.js","https://a.academia-assets.com/assets/add_coauthor-22174b608f9cb871d03443cafa7feac496fb50d7df2d66a53f5ee3c04ba67f53.js","https://a.academia-assets.com/assets/tab-dcac0130902f0cc2d8cb403714dd47454f11fc6fb0e99ae6a0827b06613abc20.js","https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js"], function() { // from javascript_helper.rb window.ae = window.ae || {}; window.ae.WowProfile = window.ae.WowProfile || {}; if(Aedu.User.current && Aedu.User.current.id === $viewedUser.id) { window.ae.WowProfile.current_user_edit = {}; new WowProfileEdit.EditUploadView({ el: '.js-edit-upload-button-wrapper', model: window.$current_user, }); new AddCoauthor.AddCoauthorsController(); } var userInfoView = new WowProfile.SocialRedesignUserInfo({ recaptcha_key: "6LdxlRMTAAAAADnu_zyLhLg0YF9uACwz78shpjJB" }); WowProfile.router = new WowProfile.Router({ userInfoView: userInfoView }); Backbone.history.start({ pushState: true, root: "/" + $viewedUser.page_name }); new WowProfile.UserWorksNav() }); </script> </div> <div class="bootstrap login"><div class="modal fade login-modal" id="login-modal"><div class="login-modal-dialog modal-dialog"><div class="modal-content"><div class="modal-header"><button class="close close" data-dismiss="modal" type="button"><span aria-hidden="true">×</span><span class="sr-only">Close</span></button><h4 class="modal-title text-center"><strong>Log In</strong></h4></div><div class="modal-body"><div class="row"><div class="col-xs-10 col-xs-offset-1"><button class="btn btn-fb btn-lg btn-block btn-v-center-content" id="login-facebook-oauth-button"><svg style="float: left; width: 19px; line-height: 1em; margin-right: .3em;" aria-hidden="true" focusable="false" data-prefix="fab" data-icon="facebook-square" class="svg-inline--fa fa-facebook-square fa-w-14" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 448 512"><path fill="currentColor" d="M400 32H48A48 48 0 0 0 0 80v352a48 48 0 0 0 48 48h137.25V327.69h-63V256h63v-54.64c0-62.15 37-96.48 93.67-96.48 27.14 0 55.52 4.84 55.52 4.84v61h-31.27c-30.81 0-40.42 19.12-40.42 38.73V256h68.78l-11 71.69h-57.78V480H400a48 48 0 0 0 48-48V80a48 48 0 0 0-48-48z"></path></svg><small><strong>Log in</strong> with <strong>Facebook</strong></small></button><br /><button class="btn btn-google btn-lg btn-block btn-v-center-content" id="login-google-oauth-button"><svg style="float: left; width: 22px; line-height: 1em; margin-right: .3em;" aria-hidden="true" focusable="false" data-prefix="fab" data-icon="google-plus" class="svg-inline--fa fa-google-plus fa-w-16" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><path fill="currentColor" d="M256,8C119.1,8,8,119.1,8,256S119.1,504,256,504,504,392.9,504,256,392.9,8,256,8ZM185.3,380a124,124,0,0,1,0-248c31.3,0,60.1,11,83,32.3l-33.6,32.6c-13.2-12.9-31.3-19.1-49.4-19.1-42.9,0-77.2,35.5-77.2,78.1S142.3,334,185.3,334c32.6,0,64.9-19.1,70.1-53.3H185.3V238.1H302.2a109.2,109.2,0,0,1,1.9,20.7c0,70.8-47.5,121.2-118.8,121.2ZM415.5,273.8v35.5H380V273.8H344.5V238.3H380V202.8h35.5v35.5h35.2v35.5Z"></path></svg><small><strong>Log in</strong> with <strong>Google</strong></small></button><br /><style type="text/css">.sign-in-with-apple-button { width: 100%; height: 52px; border-radius: 3px; border: 1px solid black; cursor: pointer; }</style><script src="https://appleid.cdn-apple.com/appleauth/static/jsapi/appleid/1/en_US/appleid.auth.js" type="text/javascript"></script><div class="sign-in-with-apple-button" data-border="false" data-color="white" id="appleid-signin"><span   ="Sign Up with Apple" class="u-fs11"></span></div><script>AppleID.auth.init({ clientId: 'edu.academia.applesignon', scope: 'name email', redirectURI: 'https://www.academia.edu/sessions', state: "d8625e86ff8736fcf149d3c96d484eb190e5a6e16007443f198d4eacc7839393", });</script><script>// Hacky way of checking if on fast loswp if (window.loswp == null) { (function() { const Google = window?.Aedu?.Auth?.OauthButton?.Login?.Google; const Facebook = window?.Aedu?.Auth?.OauthButton?.Login?.Facebook; if (Google) { new Google({ el: '#login-google-oauth-button', rememberMeCheckboxId: 'remember_me', track: null }); } if (Facebook) { new Facebook({ el: '#login-facebook-oauth-button', rememberMeCheckboxId: 'remember_me', track: null }); } })(); }</script></div></div></div><div class="modal-body"><div class="row"><div class="col-xs-10 col-xs-offset-1"><div class="hr-heading login-hr-heading"><span class="hr-heading-text">or</span></div></div></div></div><div class="modal-body"><div class="row"><div class="col-xs-10 col-xs-offset-1"><form class="js-login-form" action="https://www.academia.edu/sessions" accept-charset="UTF-8" method="post"><input name="utf8" type="hidden" value="✓" autocomplete="off" /><input type="hidden" name="authenticity_token" value="YsCQHViWUOg1dd/8IvKtrMb7kcjemuOPGPESg0X/Mh8PDHnyR38L4Hd0JBm5MuktFCKFoJCo9lWx9IN8m4VzcA==" autocomplete="off" /><div class="form-group"><label class="control-label" for="login-modal-email-input" style="font-size: 14px;">Email</label><input class="form-control" id="login-modal-email-input" name="login" type="email" /></div><div class="form-group"><label class="control-label" for="login-modal-password-input" style="font-size: 14px;">Password</label><input class="form-control" id="login-modal-password-input" name="password" type="password" /></div><input type="hidden" name="post_login_redirect_url" id="post_login_redirect_url" value="https://johnshopkins.academia.edu/RUDIGERVONDERHEYDT" autocomplete="off" /><div class="checkbox"><label><input type="checkbox" name="remember_me" id="remember_me" value="1" checked="checked" /><small style="font-size: 12px; margin-top: 2px; display: inline-block;">Remember me on this computer</small></label></div><br><input type="submit" name="commit" value="Log In" class="btn btn-primary btn-block btn-lg js-login-submit" data-disable-with="Log In" /></br></form><script>typeof window?.Aedu?.recaptchaManagedForm === 'function' && window.Aedu.recaptchaManagedForm( document.querySelector('.js-login-form'), document.querySelector('.js-login-submit') );</script><small style="font-size: 12px;"><br />or <a data-target="#login-modal-reset-password-container" data-toggle="collapse" href="javascript:void(0)">reset password</a></small><div class="collapse" id="login-modal-reset-password-container"><br /><div class="well margin-0x"><form class="js-password-reset-form" action="https://www.academia.edu/reset_password" accept-charset="UTF-8" method="post"><input name="utf8" type="hidden" value="✓" autocomplete="off" /><input type="hidden" name="authenticity_token" value="nRFmVzwN9VwWBGmLzM55ZVZeYQCh/0JMmXNNqysWK97w3Y+4I+SuVFQFkm5XDj3khId1aO/NV5YwdtxU9WxqsQ==" autocomplete="off" /><p>Enter the email address you signed up with and we'll email you a reset link.</p><div class="form-group"><input class="form-control" name="email" type="email" /></div><script src="https://recaptcha.net/recaptcha/api.js" async defer></script> <script> var invisibleRecaptchaSubmit = function () { var closestForm = function (ele) { var curEle = ele.parentNode; while (curEle.nodeName !== 'FORM' && curEle.nodeName !== 'BODY'){ curEle = curEle.parentNode; } return curEle.nodeName === 'FORM' ? curEle : null }; var eles = document.getElementsByClassName('g-recaptcha'); if (eles.length > 0) { var form = closestForm(eles[0]); if (form) { form.submit(); } } }; </script> <input type="submit" data-sitekey="6Lf3KHUUAAAAACggoMpmGJdQDtiyrjVlvGJ6BbAj" data-callback="invisibleRecaptchaSubmit" class="g-recaptcha btn btn-primary btn-block" value="Email me a link" value=""/> </form></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/collapse-45805421cf446ca5adf7aaa1935b08a3a8d1d9a6cc5d91a62a2a3a00b20b3e6a.js"], function() { // from javascript_helper.rb $("#login-modal-reset-password-container").on("shown.bs.collapse", function() { $(this).find("input[type=email]").focus(); }); }); </script> </div></div></div><div class="modal-footer"><div class="text-center"><small style="font-size: 12px;">Need an account? <a rel="nofollow" href="https://www.academia.edu/signup">Click here to sign up</a></small></div></div></div></div></div></div><script>// If we are on subdomain or non-bootstrapped page, redirect to login page instead of showing modal (function(){ if (typeof $ === 'undefined') return; var host = window.location.hostname; if ((host === $domain || host === "www."+$domain) && (typeof $().modal === 'function')) { $("#nav_log_in").click(function(e) { // Don't follow the link and open the modal e.preventDefault(); $("#login-modal").on('shown.bs.modal', function() { $(this).find("#login-modal-email-input").focus() }).modal('show'); }); } })()</script> <div class="bootstrap" id="footer"><div class="footer-content clearfix text-center padding-top-7x" style="width:100%;"><ul class="footer-links-secondary footer-links-wide list-inline margin-bottom-1x"><li><a href="https://www.academia.edu/about">About</a></li><li><a href="https://www.academia.edu/press">Press</a></li><li><a rel="nofollow" href="https://medium.com/academia">Blog</a></li><li><a href="https://www.academia.edu/documents">Papers</a></li><li><a href="https://www.academia.edu/topics">Topics</a></li><li><a href="https://www.academia.edu/journals">Academia.edu Journals</a></li><li><a rel="nofollow" href="https://www.academia.edu/hiring"><svg style="width: 13px; height: 13px;" aria-hidden="true" focusable="false" data-prefix="fas" data-icon="briefcase" class="svg-inline--fa fa-briefcase fa-w-16" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><path fill="currentColor" d="M320 336c0 8.84-7.16 16-16 16h-96c-8.84 0-16-7.16-16-16v-48H0v144c0 25.6 22.4 48 48 48h416c25.6 0 48-22.4 48-48V288H320v48zm144-208h-80V80c0-25.6-22.4-48-48-48H176c-25.6 0-48 22.4-48 48v48H48c-25.6 0-48 22.4-48 48v80h512v-80c0-25.6-22.4-48-48-48zm-144 0H192V96h128v32z"></path></svg> <strong>We're Hiring!</strong></a></li><li><a rel="nofollow" href="https://support.academia.edu/"><svg style="width: 12px; height: 12px;" aria-hidden="true" focusable="false" data-prefix="fas" data-icon="question-circle" class="svg-inline--fa fa-question-circle fa-w-16" role="img" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512"><path fill="currentColor" d="M504 256c0 136.997-111.043 248-248 248S8 392.997 8 256C8 119.083 119.043 8 256 8s248 111.083 248 248zM262.655 90c-54.497 0-89.255 22.957-116.549 63.758-3.536 5.286-2.353 12.415 2.715 16.258l34.699 26.31c5.205 3.947 12.621 3.008 16.665-2.122 17.864-22.658 30.113-35.797 57.303-35.797 20.429 0 45.698 13.148 45.698 32.958 0 14.976-12.363 22.667-32.534 33.976C247.128 238.528 216 254.941 216 296v4c0 6.627 5.373 12 12 12h56c6.627 0 12-5.373 12-12v-1.333c0-28.462 83.186-29.647 83.186-106.667 0-58.002-60.165-102-116.531-102zM256 338c-25.365 0-46 20.635-46 46 0 25.364 20.635 46 46 46s46-20.636 46-46c0-25.365-20.635-46-46-46z"></path></svg> <strong>Help Center</strong></a></li></ul><ul class="footer-links-tertiary list-inline margin-bottom-1x"><li class="small">Find new research papers in:</li><li class="small"><a href="https://www.academia.edu/Documents/in/Physics">Physics</a></li><li class="small"><a href="https://www.academia.edu/Documents/in/Chemistry">Chemistry</a></li><li class="small"><a href="https://www.academia.edu/Documents/in/Biology">Biology</a></li><li class="small"><a href="https://www.academia.edu/Documents/in/Health_Sciences">Health Sciences</a></li><li class="small"><a href="https://www.academia.edu/Documents/in/Ecology">Ecology</a></li><li class="small"><a href="https://www.academia.edu/Documents/in/Earth_Sciences">Earth Sciences</a></li><li class="small"><a href="https://www.academia.edu/Documents/in/Cognitive_Science">Cognitive Science</a></li><li class="small"><a href="https://www.academia.edu/Documents/in/Mathematics">Mathematics</a></li><li class="small"><a href="https://www.academia.edu/Documents/in/Computer_Science">Computer Science</a></li></ul></div></div><div class="DesignSystem" id="credit" style="width:100%;"><ul class="u-pl0x footer-links-legal list-inline"><li><a rel="nofollow" href="https://www.academia.edu/terms">Terms</a></li><li><a rel="nofollow" href="https://www.academia.edu/privacy">Privacy</a></li><li><a rel="nofollow" href="https://www.academia.edu/copyright">Copyright</a></li><li>Academia ©2024</li></ul></div><script> //<![CDATA[ window.detect_gmtoffset = true; window.Academia && window.Academia.set_gmtoffset && Academia.set_gmtoffset('/gmtoffset'); //]]> </script> <div id='overlay_background'></div> <div id='bootstrap-modal-container' class='bootstrap'></div> <div id='ds-modal-container' class='bootstrap DesignSystem'></div> <div id='full-screen-modal'></div> </div> </body> </html>