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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 Jean-françois Vibert</h3></div><div class="js-work-strip profile--work_container" data-work-id="125967473"><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/125967473/Morbidit%C3%A9_et_facteurs_pronostiques_dans_la_pemphigo%C3%AFde_cicatricielle_%C3%A9tude_r%C3%A9trospective_sur_121_patients"><img alt="Research paper thumbnail of Morbidité et facteurs pronostiques dans la pemphigoïde cicatricielle : étude rétrospective sur 121 patients" class="work-thumbnail" src="https://attachments.academia-assets.com/119917973/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/125967473/Morbidit%C3%A9_et_facteurs_pronostiques_dans_la_pemphigo%C3%AFde_cicatricielle_%C3%A9tude_r%C3%A9trospective_sur_121_patients">Morbidité et facteurs pronostiques dans la pemphigoïde cicatricielle : étude rétrospective sur 121 patients</a></div><div class="wp-workCard_item"><span>Annales de Dermatologie et de Vénéréologie</span><span>, 2015</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">notre étude suggèrent que l'Elisa pourrait permettre de remplacer l'IFD pour poser le diagnostic ...</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">notre étude suggèrent que l'Elisa pourrait permettre de remplacer l'IFD pour poser le diagnostic de PG et ainsi limiter la rançon cicatricielle liée à la biopsie. Cet examen a également l'avantage d'être quantitatif et permet d'évaluer l'activité de la maladie, comme dans la pemphigoïde bulleuse. Conclusion L'Elisa PB180 est très sensible et spécifique pour le diagnostic de PG ou de PUPPP et devrait en pratique remplacer l'IFD. Mots clés Elisa BP180 ; Pemphigoïde de la grossesse ; PUPPP Déclaration de liens d'intérêts Les auteurs déclarent ne pas avoir de liens d'intérêts.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="c7da13d6137745ccaddb6929081a550e" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":119917973,"asset_id":125967473,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/119917973/download_file?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="125967473"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="125967473"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 125967473; 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$(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="125967459"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/125967459/Automatic_detection_of_microcalcifications_in_mammography_using_a_neuromimetic_system_based_on_retina"><img alt="Research paper thumbnail of Automatic detection of microcalcifications in mammography using a neuromimetic system based on retina" 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" rel="nofollow" href="https://www.academia.edu/125967459/Automatic_detection_of_microcalcifications_in_mammography_using_a_neuromimetic_system_based_on_retina">Automatic detection of microcalcifications in mammography using a neuromimetic system based on retina</a></div><div class="wp-workCard_item"><span>PubMed</span><span>, 2003</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The incidence of breast cancer in France is roughly 26,000 and the annual number of deaths is 11,...</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 incidence of breast cancer in France is roughly 26,000 and the annual number of deaths is 11,000. The mammography is the choice examination for the early identification of the tumours in an asymptomatic population. This is a simple, reliable, inexpensive examination, allowing to identify a grave and frequent pathology, but that can be the object of an effective treatment if early detected. The recognition of the microcalcifications in the mammographies is the key for early detection of cancers. Automatic detection methods were already proposed, but they have a very weak specificity and a relatively low sensibility. Currently, the eye of the expert still remains the better judge. We propose a neuromimetic method to localize automatically the microcalcifications. In this method, we devise a network of formal neurones inspired from the mammal retina architecture. This model mimics one characteristic of the retina which is is a sensor that automatically adapts to the image characteristics to analyse and realize the outlines extraction and adaptative filtering of the pictures, based on its network properties. The results were tested using a public standardized data set (DDSM), which was designed to test the automatic detection methods. We show that our "retina" can extracts most of the microcalcifications that can be grouped together in clusters. While we achieve a 95% sensitivity, we must acknowledge a low specificity (22%). Current efforts will focus to enhance this latter parameter.</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="125967459"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="125967459"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 125967459; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=125967459]").text(description); $(".js-view-count[data-work-id=125967459]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 125967459; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='125967459']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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" } } $('.js-work-strip[data-work-id=125967459]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":125967459,"title":"Automatic detection of microcalcifications in mammography using a neuromimetic system based on retina","internal_url":"https://www.academia.edu/125967459/Automatic_detection_of_microcalcifications_in_mammography_using_a_neuromimetic_system_based_on_retina","owner_id":35579672,"coauthors_can_edit":true,"owner":{"id":35579672,"first_name":"Jean-françois","middle_initials":null,"last_name":"Vibert","page_name":"JeanfrançoisVibert","domain_name":"independent","created_at":"2015-10-03T05:13:49.746-07:00","display_name":"Jean-françois Vibert","url":"https://independent.academia.edu/Jeanfran%C3%A7oisVibert"},"attachments":[]}, 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="122971034"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/122971034/Is_the_Respiratory_Rhythm_Multistable_in_Man"><img alt="Research paper thumbnail of Is the Respiratory Rhythm Multistable in Man?" 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" rel="nofollow" href="https://www.academia.edu/122971034/Is_the_Respiratory_Rhythm_Multistable_in_Man">Is the Respiratory Rhythm Multistable in Man?</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Multimodal distribution of the respiratory period (RP) recorded for several hours in cats was rep...</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">Multimodal distribution of the respiratory period (RP) recorded for several hours in cats was reported in recent investigations1–3. Under simplified conditions, in which unmedicated animals displayed three types of behavior only and gas exchange remained stable, RP distribution exhibited three modes: early during wakefulness, late during sleep and intermediate during drowsiness. When the sleep-wakefulness level shifted very slowly, RP always fell into one of the three modes for a while and then switched to one of the two others within few respiratory cycles. These observations suggested that the respiratory oscillation has several attracting or limit cycles, at least in the cat.</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="122971034"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="122971034"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 122971034; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=122971034]").text(description); 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window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=122971033]").text(description); $(".js-view-count[data-work-id=122971033]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 122971033; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='122971033']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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); 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</script> <div class="js-work-strip profile--work_container" data-work-id="122971032"><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/122971032/Respiratory_oscillator_entrainment_by_periodic_vagal_afferentes_An_experimental_test_of_a_model"><img alt="Research paper thumbnail of Respiratory oscillator entrainment by periodic vagal afferentes: An experimental test of a model" class="work-thumbnail" src="https://attachments.academia-assets.com/117517000/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/122971032/Respiratory_oscillator_entrainment_by_periodic_vagal_afferentes_An_experimental_test_of_a_model">Respiratory oscillator entrainment by periodic vagal afferentes: An experimental test of a model</a></div><div class="wp-workCard_item"><span>Biological Cybernetics</span><span>, Aug 1, 1981</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="9e2056713ea6bf66a381e2a909806696" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":117517000,"asset_id":122971032,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/117517000/download_file?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="122971032"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="122971032"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 122971032; 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As a first step toward a better understanding of the influence of delay, we study the dynamics of a single graded-response neuron with a delayed excitatory self-connection. The behavior of this system is representative of that of a family of networks composed of graded-response neurons in which most trajectories converge to stable equilibrium points for any delay value. It is shown that changing the delay modifies the "location" of the boundary of the basin of attraction of the stable equilibrium points without affecting the stability of the equilibria. The dynamics of trajectories on the boundary are also delay dependent and influence the transient regime of trajectories within the adjacent basins. Our results suggest that when dealing with networks with delay, it is important to study not only the effect of the delay on the asymptotic convergence of the system but also on the boundary of the basins of attraction of the equilibria.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="a0df6e398501469b0075f8218d11ede0" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":117516999,"asset_id":122971031,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/117516999/download_file?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="122971031"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="122971031"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 122971031; 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As a first step toward a better understanding of the influence of delay, we study the dynamics of a single graded-response neuron with a delayed excitatory self-connection. The behavior of this system is representative of that of a family of networks composed of graded-response neurons in which most trajectories converge to stable equilibrium points for any delay value. It is shown that changing the delay modifies the &amp;quot;location&amp;quot; of the boundary of the basin of attraction of the stable equilibrium points without affecting the stability of the equilibria. The dynamics of trajectories on the boundary are also delay dependent and influence the transient regime of trajectories within the adjacent basins. Our results suggest that when dealing with networks with delay, it is important to study not only the effect of the delay on the asymptotic convergence of the system but also on the boundary of the basins of attraction of the equilibria.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="122971030"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="122971030"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 122971030; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); 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</script> <div class="js-work-strip profile--work_container" data-work-id="122971026"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/122971026/Single_graded_response_neuron_model_with_recurrent_excitation_distributed_delay"><img alt="Research paper thumbnail of Single graded-response neuron model with recurrent excitation: distributed delay" 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" rel="nofollow" href="https://www.academia.edu/122971026/Single_graded_response_neuron_model_with_recurrent_excitation_distributed_delay">Single graded-response neuron model with recurrent excitation: distributed delay</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="122971026"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="122971026"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 122971026; 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</script> <div class="js-work-strip profile--work_container" data-work-id="115596013"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/115596013/An_Educable_Wave_Form_Recognition_System_for_Sorting_Unit_Discharge_from_Multiunit_Signals"><img alt="Research paper thumbnail of An Educable Wave Form Recognition System for Sorting Unit Discharge from Multiunit Signals" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/115596013/An_Educable_Wave_Form_Recognition_System_for_Sorting_Unit_Discharge_from_Multiunit_Signals">An Educable Wave Form Recognition System for Sorting Unit Discharge from Multiunit Signals</a></div><div class="wp-workCard_item"><span>Springer eBooks</span><span>, 1979</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="115596013"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115596013"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115596013; 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</script> <div class="js-work-strip profile--work_container" data-work-id="115596012"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/115596012/Le_d%C3%A9sequiubre_des_besoins_et_des_moyens"><img alt="Research paper thumbnail of Le désequiubre des besoins et des moyens" 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" rel="nofollow" href="https://www.academia.edu/115596012/Le_d%C3%A9sequiubre_des_besoins_et_des_moyens">Le désequiubre des besoins et des moyens</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="115596012"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115596012"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115596012; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115596012]").text(description); $(".js-view-count[data-work-id=115596012]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115596012; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115596012']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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" } } $('.js-work-strip[data-work-id=115596012]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115596012,"title":"Le désequiubre des besoins et des moyens","internal_url":"https://www.academia.edu/115596012/Le_d%C3%A9sequiubre_des_besoins_et_des_moyens","owner_id":35579672,"coauthors_can_edit":true,"owner":{"id":35579672,"first_name":"Jean-françois","middle_initials":null,"last_name":"Vibert","page_name":"JeanfrançoisVibert","domain_name":"independent","created_at":"2015-10-03T05:13:49.746-07:00","display_name":"Jean-françois Vibert","url":"https://independent.academia.edu/Jeanfran%C3%A7oisVibert"},"attachments":[]}, 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="115596011"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/115596011/XNBC_A_Simulation_Tool_for_Neurobiologists"><img alt="Research paper thumbnail of XNBC: A Simulation Tool for Neurobiologists" 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" rel="nofollow" href="https://www.academia.edu/115596011/XNBC_A_Simulation_Tool_for_Neurobiologists">XNBC: A Simulation Tool for Neurobiologists</a></div><div class="wp-workCard_item"><span>Springer eBooks</span><span>, 1995</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">XNBC, the version 7 of NBC (Neuro_bio_clusters, Vibertet al. 1989, 1994) is X oriented and allows...</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">XNBC, the version 7 of NBC (Neuro_bio_clusters, Vibertet al. 1989, 1994) is X oriented and allows the simulation of interacting biological neural networks. It is designed for computer naive neuroscientists. XNBC provides two simulation levels: one based on a leaky integrator model of neuron dynamics and another based on the Hodgkin-Huxley formalism describing ionic channel conductance dynamics XNBC allows the simulation of biologically plausible networks formed by several interconnected neural clusters connected through pathways of variable length and whose connection matrix is specified. Each cluster can receive external inputs, either simulated or coming from actual biological data, allowing hybrid experiments. Neuron parameters are selected and fine tuned on a graphic editor which immediately displays the modification effects on neural behavior. The network architecture, including the connection pattern and the inter neuron transmission delays, is also built using a graphic editor. XNBC also allows inputs, anatomical characteristics, and other properties of individual units and synapses to be modified during the simulation thereby taking into account the changes in environmental conditions due to learning or simulated pathological conditions. Time evolution of network variables can be followed on several types of dynamic(i.e. animated) visualization tools. XNBC also provides a wide collection of analysis tools to study the network behavior, at both global and unitary levels, and in both the frequency and the temporal domains. XNBC is menu driven with a user-friendly XWindow/Motif interface and produces color PostScript high quality graphic outputs.</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="115596011"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115596011"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115596011; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115596011]").text(description); $(".js-view-count[data-work-id=115596011]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115596011; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115596011']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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" } } $('.js-work-strip[data-work-id=115596011]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115596011,"title":"XNBC: A Simulation Tool for Neurobiologists","internal_url":"https://www.academia.edu/115596011/XNBC_A_Simulation_Tool_for_Neurobiologists","owner_id":35579672,"coauthors_can_edit":true,"owner":{"id":35579672,"first_name":"Jean-françois","middle_initials":null,"last_name":"Vibert","page_name":"JeanfrançoisVibert","domain_name":"independent","created_at":"2015-10-03T05:13:49.746-07:00","display_name":"Jean-françois Vibert","url":"https://independent.academia.edu/Jeanfran%C3%A7oisVibert"},"attachments":[]}, 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="115596010"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/115596010/Estimation_of_the_number_of_normal_subpopulations_in_an_heterogeneous_sample_and_of_their_parameters"><img alt="Research paper thumbnail of Estimation of the number of normal subpopulations in an heterogeneous sample and of their parameters" 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" rel="nofollow" href="https://www.academia.edu/115596010/Estimation_of_the_number_of_normal_subpopulations_in_an_heterogeneous_sample_and_of_their_parameters">Estimation of the number of normal subpopulations in an heterogeneous sample and of their parameters</a></div><div class="wp-workCard_item"><span>Pflügers Archiv: European Journal of Physiology</span><span>, Mar 1, 1978</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">A method is proposed to estimate the number of subpopulations which compose a heterogeneous exper...</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">A method is proposed to estimate the number of subpopulations which compose a heterogeneous experimental population. The method consists of reconstructing a population sample by adding computed subpopulations, postulated to be independent. The assumption is made that each subpopulation fits a normal distribution; the method may also be generalized to other distributions laws; each subpopulation can thus be entirely defined by its mean, variance and relative weight. Recurrent adjustments of number and parameters of subpopulations are carried out in order to minimize the difference between synthetized and experimental populations. This difference was measured by the quadratic distance chi2 between the two populations. Mean, variance and weight of the computed population must then be close to those of the experimental population in order to consider the results as acceptable. This method is discussed with regard to others proposed in the literature.</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="115596010"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115596010"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115596010; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115596010]").text(description); $(".js-view-count[data-work-id=115596010]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115596010; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115596010']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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" } } $('.js-work-strip[data-work-id=115596010]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115596010,"title":"Estimation of the number of normal subpopulations in an heterogeneous sample and of their parameters","internal_url":"https://www.academia.edu/115596010/Estimation_of_the_number_of_normal_subpopulations_in_an_heterogeneous_sample_and_of_their_parameters","owner_id":35579672,"coauthors_can_edit":true,"owner":{"id":35579672,"first_name":"Jean-françois","middle_initials":null,"last_name":"Vibert","page_name":"JeanfrançoisVibert","domain_name":"independent","created_at":"2015-10-03T05:13:49.746-07:00","display_name":"Jean-françois Vibert","url":"https://independent.academia.edu/Jeanfran%C3%A7oisVibert"},"attachments":[]}, 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="115596009"><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/115596009/Intelligent_software_for_spike_separation_in_multiunit_recordings"><img alt="Research paper thumbnail of Intelligent software for spike separation in multiunit recordings" class="work-thumbnail" src="https://attachments.academia-assets.com/111957558/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/115596009/Intelligent_software_for_spike_separation_in_multiunit_recordings">Intelligent software for spike separation in multiunit recordings</a></div><div class="wp-workCard_item"><span>Medical & Biological Engineering & Computing</span><span>, Jul 1, 1987</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Introduction EXTRACELLULAR RECORDING through low-impedance microelectrodes is a useful technique,...</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">Introduction EXTRACELLULAR RECORDING through low-impedance microelectrodes is a useful technique, as it makes possible the analysis of signals arising from several neurons surrounding the probe. The multiunit signal is made up of several recognisable spike families, each of them putatively originating from a particular neuron. Multiunit signal processing, however, raises difficult problems, mainly when online spike recognition is necessary for biological tests during the course of an experiment. We have previously reported (VIBERT and COSTA, 1979; COSTA et al., 1974; 1979) results of a statistical analysis showing that bi-and triphasic spikes are most efficiently detected on a slope criterion and described by a vector of their second monotony (voltage difference between its extrema and time elapsed between them). In another paper (COSTA and VIBERT, 1986) we described a computer peripheral device for online detection and parametering of spikes in a multiunit signal and mini-or microcomputer feeding. In the present paper we report on an algorithm for unsupervised spike recognition and separation of such spike parameters. The simplest way to identify spike families from a collection of measured spike parameters is visual examination of a set of graphs in which the parameters are plotted against each other, and the manual setting of limits to</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="22725980f66ee48fd93a74d12462af95" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":111957558,"asset_id":115596009,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/111957558/download_file?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="115596009"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115596009"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115596009; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="115596008"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/115596008/Organisation_des_neurones_r%C3%A9ticulaires_%C3%A0_modulation_respiratoire_au_niveau_du_pont"><img alt="Research paper thumbnail of Organisation des neurones réticulaires à modulation respiratoire au niveau du pont" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/115596008/Organisation_des_neurones_r%C3%A9ticulaires_%C3%A0_modulation_respiratoire_au_niveau_du_pont">Organisation des neurones réticulaires à modulation respiratoire au niveau du pont</a></div><div class="wp-workCard_item"><span>Journal de physiologie</span><span>, 1972</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="115596008"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115596008"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115596008; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115596008]").text(description); $(".js-view-count[data-work-id=115596008]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115596008; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115596008']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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); 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</script> <div class="js-work-strip profile--work_container" data-work-id="115596007"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/115596007/Interstitial_lung_diseases_in_children_The_French_national_cohort_study"><img alt="Research paper thumbnail of Interstitial lung diseases in children: The French national cohort study" 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" rel="nofollow" href="https://www.academia.edu/115596007/Interstitial_lung_diseases_in_children_The_French_national_cohort_study">Interstitial lung diseases in children: The French national cohort study</a></div><div class="wp-workCard_item"><span>European Respiratory Journal</span><span>, 2011</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Introduction: In France rare orphan diseases as pediatric interstitial lung diseases (ILDs) have ...</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">Introduction: In France rare orphan diseases as pediatric interstitial lung diseases (ILDs) have been identified as a public health priority. A national pediatric reference center for rare lung diseases, RespiRare, was created several years ago. Objective: To investigate the prevalence and the expression of pediatric ILDs within a national cohort in France. Methods: Children presenting with ILD from 1995 to 2010 were identified through the RespiRare network. Clinical, radiological, functional, pathological, biological and genetical longitudinal data were collected by the physicians in charge of ILDs patients using a unique national biomedical database. Results: Data were available for 197 children presenting with ILD. The mean incidence was 26/year. Median age at diagnosis was 20 months [0-16 years], and the sex ratio was 0.87 male/female. Investigations including thoracic high resolution computed tomography scan (n=197), broncho-alveolar lavages (n=97), lung biopsies (n=30) and ana...</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="115596007"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115596007"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115596007; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115596007]").text(description); $(".js-view-count[data-work-id=115596007]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115596007; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115596007']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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" } } $('.js-work-strip[data-work-id=115596007]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115596007,"title":"Interstitial lung diseases in children: The French national cohort study","internal_url":"https://www.academia.edu/115596007/Interstitial_lung_diseases_in_children_The_French_national_cohort_study","owner_id":35579672,"coauthors_can_edit":true,"owner":{"id":35579672,"first_name":"Jean-françois","middle_initials":null,"last_name":"Vibert","page_name":"JeanfrançoisVibert","domain_name":"independent","created_at":"2015-10-03T05:13:49.746-07:00","display_name":"Jean-françois Vibert","url":"https://independent.academia.edu/Jeanfran%C3%A7oisVibert"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="115596006"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/115596006/A_Method_for_Estimation_of_the_Number_of_Normal_Subpopulations_in_Heterogeneous_Experimental_Samples_Application_to_Neurobiology"><img alt="Research paper thumbnail of A Method for Estimation of the Number of Normal Subpopulations in Heterogeneous Experimental Samples. Application to Neurobiology" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/115596006/A_Method_for_Estimation_of_the_Number_of_Normal_Subpopulations_in_Heterogeneous_Experimental_Samples_Application_to_Neurobiology">A Method for Estimation of the Number of Normal Subpopulations in Heterogeneous Experimental Samples. Application to Neurobiology</a></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="115596006"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115596006"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115596006; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115596006]").text(description); $(".js-view-count[data-work-id=115596006]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115596006; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115596006']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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" } } $('.js-work-strip[data-work-id=115596006]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115596006,"title":"A Method for Estimation of the Number of Normal Subpopulations in Heterogeneous Experimental Samples. Application to Neurobiology","internal_url":"https://www.academia.edu/115596006/A_Method_for_Estimation_of_the_Number_of_Normal_Subpopulations_in_Heterogeneous_Experimental_Samples_Application_to_Neurobiology","owner_id":35579672,"coauthors_can_edit":true,"owner":{"id":35579672,"first_name":"Jean-françois","middle_initials":null,"last_name":"Vibert","page_name":"JeanfrançoisVibert","domain_name":"independent","created_at":"2015-10-03T05:13:49.746-07:00","display_name":"Jean-françois Vibert","url":"https://independent.academia.edu/Jeanfran%C3%A7oisVibert"},"attachments":[]}, 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="115596005"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/115596005/A_stereologic_model_of_pneumotaxic_oscillator_based_on_spatial_and_temporal_distributions_of_neuronal_bursts"><img alt="Research paper thumbnail of A stereologic model of pneumotaxic oscillator based on spatial and temporal distributions of neuronal bursts" 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" rel="nofollow" href="https://www.academia.edu/115596005/A_stereologic_model_of_pneumotaxic_oscillator_based_on_spatial_and_temporal_distributions_of_neuronal_bursts">A stereologic model of pneumotaxic oscillator based on spatial and temporal distributions of neuronal bursts</a></div><div class="wp-workCard_item"><span>Journal of Neurophysiology</span><span>, 1974</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">ABSTRACT</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="115596005"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115596005"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115596005; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115596005]").text(description); $(".js-view-count[data-work-id=115596005]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115596005; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115596005']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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); 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</script> <div class="js-work-strip profile--work_container" data-work-id="115596004"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/115596004/Is_Respiratory_Period_Spectrum_Characteristic_of_State_Individual_Sex_and_Species"><img alt="Research paper thumbnail of Is Respiratory Period Spectrum Characteristic of State, Individual, Sex and Species?" 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" rel="nofollow" href="https://www.academia.edu/115596004/Is_Respiratory_Period_Spectrum_Characteristic_of_State_Individual_Sex_and_Species">Is Respiratory Period Spectrum Characteristic of State, Individual, Sex and Species?</a></div><div class="wp-workCard_item"><span>Respiratory Control</span><span>, 1989</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">In a preceding work9 5 we observed that in motionless subjects, the distribution of respiratory p...</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 a preceding work9 5 we observed that in motionless subjects, the distribution of respiratory period (RP) was currently non-gaussian and in 24 % of cases clearly polymodal. Some preferential RP were observed to be constant in the same subject, regardless of physiological and behavioral states. The aim of the present work was to ascertain whether, in subjects leading a normal life, RP spectrum could be considered characteristic of state, individual, or sex.</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="115596004"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115596004"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115596004; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115596004]").text(description); $(".js-view-count[data-work-id=115596004]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115596004; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115596004']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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" } } $('.js-work-strip[data-work-id=115596004]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115596004,"title":"Is Respiratory Period Spectrum Characteristic of State, Individual, Sex and Species?","internal_url":"https://www.academia.edu/115596004/Is_Respiratory_Period_Spectrum_Characteristic_of_State_Individual_Sex_and_Species","owner_id":35579672,"coauthors_can_edit":true,"owner":{"id":35579672,"first_name":"Jean-françois","middle_initials":null,"last_name":"Vibert","page_name":"JeanfrançoisVibert","domain_name":"independent","created_at":"2015-10-03T05:13:49.746-07:00","display_name":"Jean-françois Vibert","url":"https://independent.academia.edu/Jeanfran%C3%A7oisVibert"},"attachments":[]}, 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="115596003"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/115596003/Apneusis_and_apnea_after_parabrachial_or_K%C3%B6lliker_Fuse_N_Lesion_Influence_of_wakefulness"><img alt="Research paper thumbnail of Apneusis and apnea after parabrachial or Kölliker-Fuse N. Lesion; Influence of wakefulness" 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" rel="nofollow" href="https://www.academia.edu/115596003/Apneusis_and_apnea_after_parabrachial_or_K%C3%B6lliker_Fuse_N_Lesion_Influence_of_wakefulness">Apneusis and apnea after parabrachial or Kölliker-Fuse N. Lesion; Influence of wakefulness</a></div><div class="wp-workCard_item"><span>Respiration Physiology</span><span>, 1981</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Comparisons were made between the effects of bilateral lesions of either the nucleus parabrachial...</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">Comparisons were made between the effects of bilateral lesions of either the nucleus parabrachialis medialis (NPBM) or the Kölliker-Fuse (KF) nuclei in bivagotomized, spinalized and immobilized cats. In a first group animals were electrolytically decerebrated; in a second group animals were locally anaesthetized and atraumatically restrained (semi-chronic encéphale isolé preparation). Lesions resulted in: (1) a marked increase in TI (apneusis); (2) 50--80% decrease in amplitude of the integrated phrenic discharge (IPD); (3) variable lengthening, of TE. Following KF lesion, effects were significantly larger on TE in the decerebrate group, and on TI in the encéphale isolé group. In the encéphale isolé group awakening reduced TE and TI and brought them close to their prelesion values following both NPBM and KF lesion; on the other hand light sleep induced by pentobarbital led to expiratory apnea after KF lesion and reduced IPD amplitude to zero after NPBM lesion. It is proposed that the onset, tonic drive and cut off of the I discharge are normally controlled by three differently weighted influences originating from NPBM, KF and reticular formation respectively.</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="115596003"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115596003"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115596003; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115596003]").text(description); $(".js-view-count[data-work-id=115596003]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115596003; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115596003']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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" } } $('.js-work-strip[data-work-id=115596003]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115596003,"title":"Apneusis and apnea after parabrachial or Kölliker-Fuse N. Lesion; Influence of wakefulness","internal_url":"https://www.academia.edu/115596003/Apneusis_and_apnea_after_parabrachial_or_K%C3%B6lliker_Fuse_N_Lesion_Influence_of_wakefulness","owner_id":35579672,"coauthors_can_edit":true,"owner":{"id":35579672,"first_name":"Jean-françois","middle_initials":null,"last_name":"Vibert","page_name":"JeanfrançoisVibert","domain_name":"independent","created_at":"2015-10-03T05:13:49.746-07:00","display_name":"Jean-françois Vibert","url":"https://independent.academia.edu/Jeanfran%C3%A7oisVibert"},"attachments":[]}, 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="3668489" id="papers"><div class="js-work-strip profile--work_container" data-work-id="125967473"><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/125967473/Morbidit%C3%A9_et_facteurs_pronostiques_dans_la_pemphigo%C3%AFde_cicatricielle_%C3%A9tude_r%C3%A9trospective_sur_121_patients"><img alt="Research paper thumbnail of Morbidité et facteurs pronostiques dans la pemphigoïde cicatricielle : étude rétrospective sur 121 patients" class="work-thumbnail" src="https://attachments.academia-assets.com/119917973/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/125967473/Morbidit%C3%A9_et_facteurs_pronostiques_dans_la_pemphigo%C3%AFde_cicatricielle_%C3%A9tude_r%C3%A9trospective_sur_121_patients">Morbidité et facteurs pronostiques dans la pemphigoïde cicatricielle : étude rétrospective sur 121 patients</a></div><div class="wp-workCard_item"><span>Annales de Dermatologie et de Vénéréologie</span><span>, 2015</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">notre étude suggèrent que l'Elisa pourrait permettre de remplacer l'IFD pour poser le diagnostic ...</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">notre étude suggèrent que l'Elisa pourrait permettre de remplacer l'IFD pour poser le diagnostic de PG et ainsi limiter la rançon cicatricielle liée à la biopsie. Cet examen a également l'avantage d'être quantitatif et permet d'évaluer l'activité de la maladie, comme dans la pemphigoïde bulleuse. Conclusion L'Elisa PB180 est très sensible et spécifique pour le diagnostic de PG ou de PUPPP et devrait en pratique remplacer l'IFD. Mots clés Elisa BP180 ; Pemphigoïde de la grossesse ; PUPPP Déclaration de liens d'intérêts Les auteurs déclarent ne pas avoir de liens d'intérêts.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="c7da13d6137745ccaddb6929081a550e" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":119917973,"asset_id":125967473,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/119917973/download_file?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="125967473"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="125967473"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 125967473; 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$(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="125967459"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/125967459/Automatic_detection_of_microcalcifications_in_mammography_using_a_neuromimetic_system_based_on_retina"><img alt="Research paper thumbnail of Automatic detection of microcalcifications in mammography using a neuromimetic system based on retina" 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" rel="nofollow" href="https://www.academia.edu/125967459/Automatic_detection_of_microcalcifications_in_mammography_using_a_neuromimetic_system_based_on_retina">Automatic detection of microcalcifications in mammography using a neuromimetic system based on retina</a></div><div class="wp-workCard_item"><span>PubMed</span><span>, 2003</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">The incidence of breast cancer in France is roughly 26,000 and the annual number of deaths is 11,...</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 incidence of breast cancer in France is roughly 26,000 and the annual number of deaths is 11,000. The mammography is the choice examination for the early identification of the tumours in an asymptomatic population. This is a simple, reliable, inexpensive examination, allowing to identify a grave and frequent pathology, but that can be the object of an effective treatment if early detected. The recognition of the microcalcifications in the mammographies is the key for early detection of cancers. Automatic detection methods were already proposed, but they have a very weak specificity and a relatively low sensibility. Currently, the eye of the expert still remains the better judge. We propose a neuromimetic method to localize automatically the microcalcifications. In this method, we devise a network of formal neurones inspired from the mammal retina architecture. This model mimics one characteristic of the retina which is is a sensor that automatically adapts to the image characteristics to analyse and realize the outlines extraction and adaptative filtering of the pictures, based on its network properties. The results were tested using a public standardized data set (DDSM), which was designed to test the automatic detection methods. We show that our "retina" can extracts most of the microcalcifications that can be grouped together in clusters. While we achieve a 95% sensitivity, we must acknowledge a low specificity (22%). Current efforts will focus to enhance this latter parameter.</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="125967459"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="125967459"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 125967459; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=125967459]").text(description); $(".js-view-count[data-work-id=125967459]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 125967459; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='125967459']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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" } } $('.js-work-strip[data-work-id=125967459]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":125967459,"title":"Automatic detection of microcalcifications in mammography using a neuromimetic system based on retina","internal_url":"https://www.academia.edu/125967459/Automatic_detection_of_microcalcifications_in_mammography_using_a_neuromimetic_system_based_on_retina","owner_id":35579672,"coauthors_can_edit":true,"owner":{"id":35579672,"first_name":"Jean-françois","middle_initials":null,"last_name":"Vibert","page_name":"JeanfrançoisVibert","domain_name":"independent","created_at":"2015-10-03T05:13:49.746-07:00","display_name":"Jean-françois Vibert","url":"https://independent.academia.edu/Jeanfran%C3%A7oisVibert"},"attachments":[]}, 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="122971034"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/122971034/Is_the_Respiratory_Rhythm_Multistable_in_Man"><img alt="Research paper thumbnail of Is the Respiratory Rhythm Multistable in Man?" 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" rel="nofollow" href="https://www.academia.edu/122971034/Is_the_Respiratory_Rhythm_Multistable_in_Man">Is the Respiratory Rhythm Multistable in Man?</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Multimodal distribution of the respiratory period (RP) recorded for several hours in cats was rep...</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">Multimodal distribution of the respiratory period (RP) recorded for several hours in cats was reported in recent investigations1–3. Under simplified conditions, in which unmedicated animals displayed three types of behavior only and gas exchange remained stable, RP distribution exhibited three modes: early during wakefulness, late during sleep and intermediate during drowsiness. When the sleep-wakefulness level shifted very slowly, RP always fell into one of the three modes for a while and then switched to one of the two others within few respiratory cycles. These observations suggested that the respiratory oscillation has several attracting or limit cycles, at least in the cat.</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="122971034"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="122971034"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 122971034; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=122971034]").text(description); 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</script> <div class="js-work-strip profile--work_container" data-work-id="122971032"><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/122971032/Respiratory_oscillator_entrainment_by_periodic_vagal_afferentes_An_experimental_test_of_a_model"><img alt="Research paper thumbnail of Respiratory oscillator entrainment by periodic vagal afferentes: An experimental test of a model" class="work-thumbnail" src="https://attachments.academia-assets.com/117517000/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/122971032/Respiratory_oscillator_entrainment_by_periodic_vagal_afferentes_An_experimental_test_of_a_model">Respiratory oscillator entrainment by periodic vagal afferentes: An experimental test of a model</a></div><div class="wp-workCard_item"><span>Biological Cybernetics</span><span>, Aug 1, 1981</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="9e2056713ea6bf66a381e2a909806696" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":117517000,"asset_id":122971032,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/117517000/download_file?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="122971032"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="122971032"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 122971032; 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As a first step toward a better understanding of the influence of delay, we study the dynamics of a single graded-response neuron with a delayed excitatory self-connection. The behavior of this system is representative of that of a family of networks composed of graded-response neurons in which most trajectories converge to stable equilibrium points for any delay value. It is shown that changing the delay modifies the "location" of the boundary of the basin of attraction of the stable equilibrium points without affecting the stability of the equilibria. The dynamics of trajectories on the boundary are also delay dependent and influence the transient regime of trajectories within the adjacent basins. 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$(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="122971030"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/122971030/Effect_of_delay_on_the_boundary_of_the_basin_of_attraction_in_a_system_of_two_neurons"><img alt="Research paper thumbnail of Effect of delay on the boundary of the basin of attraction in a system of two neurons" 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" rel="nofollow" href="https://www.academia.edu/122971030/Effect_of_delay_on_the_boundary_of_the_basin_of_attraction_in_a_system_of_two_neurons">Effect of delay on the boundary of the basin of attraction in a system of two neurons</a></div><div class="wp-workCard_item"><span>Neural Networks</span><span>, Apr 1, 1998</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Little attention has been paid in the past to the effects of interunit transmission delays (repre...</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">Little attention has been paid in the past to the effects of interunit transmission delays (representing axonal and synaptic delays) on the boundary of the basin of attraction of stable equilibrium points in neural networks. As a first step toward a better understanding of the influence of delay, we study the dynamics of a single graded-response neuron with a delayed excitatory self-connection. The behavior of this system is representative of that of a family of networks composed of graded-response neurons in which most trajectories converge to stable equilibrium points for any delay value. It is shown that changing the delay modifies the &amp;quot;location&amp;quot; of the boundary of the basin of attraction of the stable equilibrium points without affecting the stability of the equilibria. The dynamics of trajectories on the boundary are also delay dependent and influence the transient regime of trajectories within the adjacent basins. Our results suggest that when dealing with networks with delay, it is important to study not only the effect of the delay on the asymptotic convergence of the system but also on the boundary of the basins of attraction of the equilibria.</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="122971030"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="122971030"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 122971030; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); 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</script> <div class="js-work-strip profile--work_container" data-work-id="115596013"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/115596013/An_Educable_Wave_Form_Recognition_System_for_Sorting_Unit_Discharge_from_Multiunit_Signals"><img alt="Research paper thumbnail of An Educable Wave Form Recognition System for Sorting Unit Discharge from Multiunit Signals" 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" rel="nofollow" href="https://www.academia.edu/115596013/An_Educable_Wave_Form_Recognition_System_for_Sorting_Unit_Discharge_from_Multiunit_Signals">An Educable Wave Form Recognition System for Sorting Unit Discharge from Multiunit Signals</a></div><div class="wp-workCard_item"><span>Springer eBooks</span><span>, 1979</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="115596013"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115596013"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115596013; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115596013]").text(description); $(".js-view-count[data-work-id=115596013]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115596013; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115596013']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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); 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</script> <div class="js-work-strip profile--work_container" data-work-id="115596012"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/115596012/Le_d%C3%A9sequiubre_des_besoins_et_des_moyens"><img alt="Research paper thumbnail of Le désequiubre des besoins et des moyens" 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" rel="nofollow" href="https://www.academia.edu/115596012/Le_d%C3%A9sequiubre_des_besoins_et_des_moyens">Le désequiubre des besoins et des moyens</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="115596012"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115596012"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115596012; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=115596012]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115596012,"title":"Le désequiubre des besoins et des moyens","internal_url":"https://www.academia.edu/115596012/Le_d%C3%A9sequiubre_des_besoins_et_des_moyens","owner_id":35579672,"coauthors_can_edit":true,"owner":{"id":35579672,"first_name":"Jean-françois","middle_initials":null,"last_name":"Vibert","page_name":"JeanfrançoisVibert","domain_name":"independent","created_at":"2015-10-03T05:13:49.746-07:00","display_name":"Jean-françois Vibert","url":"https://independent.academia.edu/Jeanfran%C3%A7oisVibert"},"attachments":[]}, 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="115596011"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/115596011/XNBC_A_Simulation_Tool_for_Neurobiologists"><img alt="Research paper thumbnail of XNBC: A Simulation Tool for Neurobiologists" 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" rel="nofollow" href="https://www.academia.edu/115596011/XNBC_A_Simulation_Tool_for_Neurobiologists">XNBC: A Simulation Tool for Neurobiologists</a></div><div class="wp-workCard_item"><span>Springer eBooks</span><span>, 1995</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">XNBC, the version 7 of NBC (Neuro_bio_clusters, Vibertet al. 1989, 1994) is X oriented and allows...</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">XNBC, the version 7 of NBC (Neuro_bio_clusters, Vibertet al. 1989, 1994) is X oriented and allows the simulation of interacting biological neural networks. It is designed for computer naive neuroscientists. XNBC provides two simulation levels: one based on a leaky integrator model of neuron dynamics and another based on the Hodgkin-Huxley formalism describing ionic channel conductance dynamics XNBC allows the simulation of biologically plausible networks formed by several interconnected neural clusters connected through pathways of variable length and whose connection matrix is specified. Each cluster can receive external inputs, either simulated or coming from actual biological data, allowing hybrid experiments. Neuron parameters are selected and fine tuned on a graphic editor which immediately displays the modification effects on neural behavior. The network architecture, including the connection pattern and the inter neuron transmission delays, is also built using a graphic editor. XNBC also allows inputs, anatomical characteristics, and other properties of individual units and synapses to be modified during the simulation thereby taking into account the changes in environmental conditions due to learning or simulated pathological conditions. Time evolution of network variables can be followed on several types of dynamic(i.e. animated) visualization tools. XNBC also provides a wide collection of analysis tools to study the network behavior, at both global and unitary levels, and in both the frequency and the temporal domains. XNBC is menu driven with a user-friendly XWindow/Motif interface and produces color PostScript high quality graphic outputs.</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="115596011"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115596011"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115596011; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115596011]").text(description); $(".js-view-count[data-work-id=115596011]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115596011; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115596011']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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" } } $('.js-work-strip[data-work-id=115596011]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115596011,"title":"XNBC: A Simulation Tool for Neurobiologists","internal_url":"https://www.academia.edu/115596011/XNBC_A_Simulation_Tool_for_Neurobiologists","owner_id":35579672,"coauthors_can_edit":true,"owner":{"id":35579672,"first_name":"Jean-françois","middle_initials":null,"last_name":"Vibert","page_name":"JeanfrançoisVibert","domain_name":"independent","created_at":"2015-10-03T05:13:49.746-07:00","display_name":"Jean-françois Vibert","url":"https://independent.academia.edu/Jeanfran%C3%A7oisVibert"},"attachments":[]}, 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="115596010"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/115596010/Estimation_of_the_number_of_normal_subpopulations_in_an_heterogeneous_sample_and_of_their_parameters"><img alt="Research paper thumbnail of Estimation of the number of normal subpopulations in an heterogeneous sample and of their parameters" 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" rel="nofollow" href="https://www.academia.edu/115596010/Estimation_of_the_number_of_normal_subpopulations_in_an_heterogeneous_sample_and_of_their_parameters">Estimation of the number of normal subpopulations in an heterogeneous sample and of their parameters</a></div><div class="wp-workCard_item"><span>Pflügers Archiv: European Journal of Physiology</span><span>, Mar 1, 1978</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">A method is proposed to estimate the number of subpopulations which compose a heterogeneous exper...</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">A method is proposed to estimate the number of subpopulations which compose a heterogeneous experimental population. The method consists of reconstructing a population sample by adding computed subpopulations, postulated to be independent. The assumption is made that each subpopulation fits a normal distribution; the method may also be generalized to other distributions laws; each subpopulation can thus be entirely defined by its mean, variance and relative weight. Recurrent adjustments of number and parameters of subpopulations are carried out in order to minimize the difference between synthetized and experimental populations. This difference was measured by the quadratic distance chi2 between the two populations. Mean, variance and weight of the computed population must then be close to those of the experimental population in order to consider the results as acceptable. This method is discussed with regard to others proposed in the literature.</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="115596010"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115596010"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115596010; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115596010]").text(description); $(".js-view-count[data-work-id=115596010]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115596010; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115596010']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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" } } $('.js-work-strip[data-work-id=115596010]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115596010,"title":"Estimation of the number of normal subpopulations in an heterogeneous sample and of their parameters","internal_url":"https://www.academia.edu/115596010/Estimation_of_the_number_of_normal_subpopulations_in_an_heterogeneous_sample_and_of_their_parameters","owner_id":35579672,"coauthors_can_edit":true,"owner":{"id":35579672,"first_name":"Jean-françois","middle_initials":null,"last_name":"Vibert","page_name":"JeanfrançoisVibert","domain_name":"independent","created_at":"2015-10-03T05:13:49.746-07:00","display_name":"Jean-françois Vibert","url":"https://independent.academia.edu/Jeanfran%C3%A7oisVibert"},"attachments":[]}, 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="115596009"><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/115596009/Intelligent_software_for_spike_separation_in_multiunit_recordings"><img alt="Research paper thumbnail of Intelligent software for spike separation in multiunit recordings" class="work-thumbnail" src="https://attachments.academia-assets.com/111957558/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/115596009/Intelligent_software_for_spike_separation_in_multiunit_recordings">Intelligent software for spike separation in multiunit recordings</a></div><div class="wp-workCard_item"><span>Medical & Biological Engineering & Computing</span><span>, Jul 1, 1987</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Introduction EXTRACELLULAR RECORDING through low-impedance microelectrodes is a useful technique,...</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">Introduction EXTRACELLULAR RECORDING through low-impedance microelectrodes is a useful technique, as it makes possible the analysis of signals arising from several neurons surrounding the probe. The multiunit signal is made up of several recognisable spike families, each of them putatively originating from a particular neuron. Multiunit signal processing, however, raises difficult problems, mainly when online spike recognition is necessary for biological tests during the course of an experiment. We have previously reported (VIBERT and COSTA, 1979; COSTA et al., 1974; 1979) results of a statistical analysis showing that bi-and triphasic spikes are most efficiently detected on a slope criterion and described by a vector of their second monotony (voltage difference between its extrema and time elapsed between them). In another paper (COSTA and VIBERT, 1986) we described a computer peripheral device for online detection and parametering of spikes in a multiunit signal and mini-or microcomputer feeding. In the present paper we report on an algorithm for unsupervised spike recognition and separation of such spike parameters. The simplest way to identify spike families from a collection of measured spike parameters is visual examination of a set of graphs in which the parameters are plotted against each other, and the manual setting of limits to</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="22725980f66ee48fd93a74d12462af95" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":111957558,"asset_id":115596009,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/111957558/download_file?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="115596009"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115596009"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115596009; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="115596008"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/115596008/Organisation_des_neurones_r%C3%A9ticulaires_%C3%A0_modulation_respiratoire_au_niveau_du_pont"><img alt="Research paper thumbnail of Organisation des neurones réticulaires à modulation respiratoire au niveau du pont" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/115596008/Organisation_des_neurones_r%C3%A9ticulaires_%C3%A0_modulation_respiratoire_au_niveau_du_pont">Organisation des neurones réticulaires à modulation respiratoire au niveau du pont</a></div><div class="wp-workCard_item"><span>Journal de physiologie</span><span>, 1972</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="115596008"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115596008"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115596008; 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</script> <div class="js-work-strip profile--work_container" data-work-id="115596007"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/115596007/Interstitial_lung_diseases_in_children_The_French_national_cohort_study"><img alt="Research paper thumbnail of Interstitial lung diseases in children: The French national cohort study" 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" rel="nofollow" href="https://www.academia.edu/115596007/Interstitial_lung_diseases_in_children_The_French_national_cohort_study">Interstitial lung diseases in children: The French national cohort study</a></div><div class="wp-workCard_item"><span>European Respiratory Journal</span><span>, 2011</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Introduction: In France rare orphan diseases as pediatric interstitial lung diseases (ILDs) have ...</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">Introduction: In France rare orphan diseases as pediatric interstitial lung diseases (ILDs) have been identified as a public health priority. A national pediatric reference center for rare lung diseases, RespiRare, was created several years ago. Objective: To investigate the prevalence and the expression of pediatric ILDs within a national cohort in France. Methods: Children presenting with ILD from 1995 to 2010 were identified through the RespiRare network. Clinical, radiological, functional, pathological, biological and genetical longitudinal data were collected by the physicians in charge of ILDs patients using a unique national biomedical database. Results: Data were available for 197 children presenting with ILD. The mean incidence was 26/year. Median age at diagnosis was 20 months [0-16 years], and the sex ratio was 0.87 male/female. Investigations including thoracic high resolution computed tomography scan (n=197), broncho-alveolar lavages (n=97), lung biopsies (n=30) and ana...</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="115596007"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115596007"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115596007; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115596007]").text(description); $(".js-view-count[data-work-id=115596007]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115596007; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115596007']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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" } } $('.js-work-strip[data-work-id=115596007]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115596007,"title":"Interstitial lung diseases in children: The French national cohort study","internal_url":"https://www.academia.edu/115596007/Interstitial_lung_diseases_in_children_The_French_national_cohort_study","owner_id":35579672,"coauthors_can_edit":true,"owner":{"id":35579672,"first_name":"Jean-françois","middle_initials":null,"last_name":"Vibert","page_name":"JeanfrançoisVibert","domain_name":"independent","created_at":"2015-10-03T05:13:49.746-07:00","display_name":"Jean-françois Vibert","url":"https://independent.academia.edu/Jeanfran%C3%A7oisVibert"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="115596006"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/115596006/A_Method_for_Estimation_of_the_Number_of_Normal_Subpopulations_in_Heterogeneous_Experimental_Samples_Application_to_Neurobiology"><img alt="Research paper thumbnail of A Method for Estimation of the Number of Normal Subpopulations in Heterogeneous Experimental Samples. Application to Neurobiology" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/115596006/A_Method_for_Estimation_of_the_Number_of_Normal_Subpopulations_in_Heterogeneous_Experimental_Samples_Application_to_Neurobiology">A Method for Estimation of the Number of Normal Subpopulations in Heterogeneous Experimental Samples. Application to Neurobiology</a></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="115596006"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115596006"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115596006; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115596006]").text(description); $(".js-view-count[data-work-id=115596006]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115596006; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115596006']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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" } } $('.js-work-strip[data-work-id=115596006]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115596006,"title":"A Method for Estimation of the Number of Normal Subpopulations in Heterogeneous Experimental Samples. Application to Neurobiology","internal_url":"https://www.academia.edu/115596006/A_Method_for_Estimation_of_the_Number_of_Normal_Subpopulations_in_Heterogeneous_Experimental_Samples_Application_to_Neurobiology","owner_id":35579672,"coauthors_can_edit":true,"owner":{"id":35579672,"first_name":"Jean-françois","middle_initials":null,"last_name":"Vibert","page_name":"JeanfrançoisVibert","domain_name":"independent","created_at":"2015-10-03T05:13:49.746-07:00","display_name":"Jean-françois Vibert","url":"https://independent.academia.edu/Jeanfran%C3%A7oisVibert"},"attachments":[]}, 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="115596005"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/115596005/A_stereologic_model_of_pneumotaxic_oscillator_based_on_spatial_and_temporal_distributions_of_neuronal_bursts"><img alt="Research paper thumbnail of A stereologic model of pneumotaxic oscillator based on spatial and temporal distributions of neuronal bursts" 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" rel="nofollow" href="https://www.academia.edu/115596005/A_stereologic_model_of_pneumotaxic_oscillator_based_on_spatial_and_temporal_distributions_of_neuronal_bursts">A stereologic model of pneumotaxic oscillator based on spatial and temporal distributions of neuronal bursts</a></div><div class="wp-workCard_item"><span>Journal of Neurophysiology</span><span>, 1974</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">ABSTRACT</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="115596005"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115596005"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115596005; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115596005]").text(description); $(".js-view-count[data-work-id=115596005]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115596005; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115596005']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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); 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</script> <div class="js-work-strip profile--work_container" data-work-id="115596004"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/115596004/Is_Respiratory_Period_Spectrum_Characteristic_of_State_Individual_Sex_and_Species"><img alt="Research paper thumbnail of Is Respiratory Period Spectrum Characteristic of State, Individual, Sex and Species?" 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" rel="nofollow" href="https://www.academia.edu/115596004/Is_Respiratory_Period_Spectrum_Characteristic_of_State_Individual_Sex_and_Species">Is Respiratory Period Spectrum Characteristic of State, Individual, Sex and Species?</a></div><div class="wp-workCard_item"><span>Respiratory Control</span><span>, 1989</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">In a preceding work9 5 we observed that in motionless subjects, the distribution of respiratory p...</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 a preceding work9 5 we observed that in motionless subjects, the distribution of respiratory period (RP) was currently non-gaussian and in 24 % of cases clearly polymodal. Some preferential RP were observed to be constant in the same subject, regardless of physiological and behavioral states. The aim of the present work was to ascertain whether, in subjects leading a normal life, RP spectrum could be considered characteristic of state, individual, or sex.</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="115596004"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115596004"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115596004; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115596004]").text(description); $(".js-view-count[data-work-id=115596004]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115596004; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115596004']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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" } } $('.js-work-strip[data-work-id=115596004]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115596004,"title":"Is Respiratory Period Spectrum Characteristic of State, Individual, Sex and Species?","internal_url":"https://www.academia.edu/115596004/Is_Respiratory_Period_Spectrum_Characteristic_of_State_Individual_Sex_and_Species","owner_id":35579672,"coauthors_can_edit":true,"owner":{"id":35579672,"first_name":"Jean-françois","middle_initials":null,"last_name":"Vibert","page_name":"JeanfrançoisVibert","domain_name":"independent","created_at":"2015-10-03T05:13:49.746-07:00","display_name":"Jean-françois Vibert","url":"https://independent.academia.edu/Jeanfran%C3%A7oisVibert"},"attachments":[]}, 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="115596003"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/115596003/Apneusis_and_apnea_after_parabrachial_or_K%C3%B6lliker_Fuse_N_Lesion_Influence_of_wakefulness"><img alt="Research paper thumbnail of Apneusis and apnea after parabrachial or Kölliker-Fuse N. Lesion; Influence of wakefulness" 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" rel="nofollow" href="https://www.academia.edu/115596003/Apneusis_and_apnea_after_parabrachial_or_K%C3%B6lliker_Fuse_N_Lesion_Influence_of_wakefulness">Apneusis and apnea after parabrachial or Kölliker-Fuse N. Lesion; Influence of wakefulness</a></div><div class="wp-workCard_item"><span>Respiration Physiology</span><span>, 1981</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Comparisons were made between the effects of bilateral lesions of either the nucleus parabrachial...</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">Comparisons were made between the effects of bilateral lesions of either the nucleus parabrachialis medialis (NPBM) or the Kölliker-Fuse (KF) nuclei in bivagotomized, spinalized and immobilized cats. In a first group animals were electrolytically decerebrated; in a second group animals were locally anaesthetized and atraumatically restrained (semi-chronic encéphale isolé preparation). Lesions resulted in: (1) a marked increase in TI (apneusis); (2) 50--80% decrease in amplitude of the integrated phrenic discharge (IPD); (3) variable lengthening, of TE. Following KF lesion, effects were significantly larger on TE in the decerebrate group, and on TI in the encéphale isolé group. In the encéphale isolé group awakening reduced TE and TI and brought them close to their prelesion values following both NPBM and KF lesion; on the other hand light sleep induced by pentobarbital led to expiratory apnea after KF lesion and reduced IPD amplitude to zero after NPBM lesion. It is proposed that the onset, tonic drive and cut off of the I discharge are normally controlled by three differently weighted influences originating from NPBM, KF and reticular formation respectively.</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="115596003"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="115596003"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 115596003; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=115596003]").text(description); $(".js-view-count[data-work-id=115596003]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 115596003; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='115596003']"); 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></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.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" } } $('.js-work-strip[data-work-id=115596003]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":115596003,"title":"Apneusis and apnea after parabrachial or Kölliker-Fuse N. 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