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data-dom-id="Pill-react-component-2c0cbcf7-4dce-4211-94b4-327efc88fe24"></div> <div id="Pill-react-component-2c0cbcf7-4dce-4211-94b4-327efc88fe24"></div> </a><a data-click-track="profile-user-info-expand-research-interests" data-has-card-for-ri-list="38884898" href="https://www.academia.edu/Documents/in/Neuromodulation_Devices"><div class="js-react-on-rails-component" style="display:none" data-component-name="Pill" data-props="{"color":"gray","children":["Neuromodulation Devices"]}" data-trace="false" data-dom-id="Pill-react-component-e7591b53-aaa9-4458-ade9-0520940c1553"></div> <div id="Pill-react-component-e7591b53-aaa9-4458-ade9-0520940c1553"></div> </a></div></div></div></div><div class="right-panel-container"><div class="user-content-wrapper"><div class="uploads-container" id="social-redesign-work-container"><div class="upload-header"><h2 class="ds2-5-heading-sans-serif-xs">Uploads</h2></div><div class="documents-container backbone-social-profile-documents" style="width: 100%;"><div class="u-taCenter"></div><div class="profile--tab_content_container js-tab-pane tab-pane active" id="all"><div class="profile--tab_heading_container js-section-heading" data-section="Papers" id="Papers"><h3 class="profile--tab_heading_container">Papers by Ranu Jung</h3></div><div class="js-work-strip profile--work_container" data-work-id="123485771"><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/123485771/Peripheral_Nerve_Interface_Applications_EMG_ENG"><img alt="Research paper thumbnail of Peripheral Nerve Interface Applications, EMG/ENG" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/123485771/Peripheral_Nerve_Interface_Applications_EMG_ENG">Peripheral Nerve Interface Applications, EMG/ENG</a></div><div class="wp-workCard_item"><span>Springer eBooks</span><span>, 2022</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="123485771"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="123485771"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 123485771; 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src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/123485770/Dynamic_behavior_of_a_neural_network_model_of_locomotor_control_in_the_lamprey">Dynamic behavior of a neural network model of locomotor control in the lamprey</a></div><div class="wp-workCard_item"><span>Journal of Neurophysiology</span><span>, Mar 1, 1996</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">1. Experimental studies have shown that a central pattern generator in the spinal cord of the lam...</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">1. Experimental studies have shown that a central pattern generator in the spinal cord of the lamprey can produce the basic rhythm for locomotion. This pattern generator interacts with the reticular neurons forming a spinoreticulospinal loop. To better understand and investigate the mechanisms for locomotor pattern generation in the lamprey, we examine the dynamic behavior of a simplified neural network model representing a unit spinal pattern generator (uPG) and its interaction with the reticular system. We use the techniques of bifurcation analysis and specifically examine the effects on the dynamic behavior of the system of 1) changing tonic drives to the different neurons of the uPG; 2) altering inhibitory and excitatory interconnection strengths among the uPG neurons; and 3) feedforward-feedback interactions between the uPG and the reticular neurons. 2. The model analyzed is a qualitative left-right symmetric network based on proposed functional architecture with one class of phasic reticular neurons and three classes of uPG neurons: excitatory (E), lateral (L), and crossed (C) interneurons. In the model each class is represented by one left and one right neuron. Each neuron has basic passive properties akin to biophysical neurons and receives tonic synaptic drive and weighted synaptic input from other connecting neurons. The neuron&#39;s output as a function of voltage is given by a nonlinear function with a strict threshold and saturation. 3. With an appropriate set of parameter values, the voltage of each neuron can oscillate periodically with phase relationships among the different neurons that are qualitatively similar to those observed experimentally. The uPG alone can also oscillate, as observed experimentally in isolated lamprey spinal cords. Varying the parameters can, however, profoundly change the state of the system via different kinds of bifurcations. Change in a single parameter can move the system from nonoscillatory to oscillatory states via different kinds of bifurcations. For some parameter values the system can also exhibit multistable behavior (e.g., an oscillatory state and a nonoscillatory state). The analysis also shows us how the amplitudes of the oscillations vary and the periods of limit cycles change as different bifurcation points are approached. 4. Altering tonic drive to just one class of uPG neurons (without altering the interconnections) can change the state of the system by altering the stability of fixed points, converting fixed points to oscillations, single oscillations to two stable oscillations, etc. Two-parameter bifurcation diagrams show the critical regions in which a balance between the tonic drives is necessary to maintain stable oscillations. A minimum tonic drive is necessary to obtain stable oscillatory output. With appropriate changes in the tonic drives to the L and C neurons, stable oscillatory output can be obtained even after eliminating the E neurons. Indeed, the presence of active E neurons in the biological system does not prove they play a functional role in the system, because tonic drive from other sources can substitute for them. On the other hand, very high excitation of any one class of neurons can terminate oscillations. Appropriate balance of tonic drives to different neuron classes can help sustain stable oscillations for larger tonic drives. Published experimental results concerning changes in amplitude and swimming frequency with increased tonic drives are mimicked by the model&#39;s responses to increased tonic drive. 5. Interconnectivity among the neurons plays a crucial role. The analysis indicates that the C and L classes of neurons are essential components of the model network. Sufficient inhibition from the L to C neurons as well as mutual inhibition between the left and right halves is necessary to obtain stable oscillatory output. When the E neurons are present in the model network, they must receive appropriate tonic drive and provide appropriate excitation</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="123485770"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="123485770"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 123485770; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=123485770]").text(description); $(".js-view-count[data-work-id=123485770]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 123485770; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='123485770']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 123485770, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=123485770]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":123485770,"title":"Dynamic behavior of a neural network model of locomotor control in the lamprey","translated_title":"","metadata":{"abstract":"1. Experimental studies have shown that a central pattern generator in the spinal cord of the lamprey can produce the basic rhythm for locomotion. This pattern generator interacts with the reticular neurons forming a spinoreticulospinal loop. To better understand and investigate the mechanisms for locomotor pattern generation in the lamprey, we examine the dynamic behavior of a simplified neural network model representing a unit spinal pattern generator (uPG) and its interaction with the reticular system. We use the techniques of bifurcation analysis and specifically examine the effects on the dynamic behavior of the system of 1) changing tonic drives to the different neurons of the uPG; 2) altering inhibitory and excitatory interconnection strengths among the uPG neurons; and 3) feedforward-feedback interactions between the uPG and the reticular neurons. 2. The model analyzed is a qualitative left-right symmetric network based on proposed functional architecture with one class of phasic reticular neurons and three classes of uPG neurons: excitatory (E), lateral (L), and crossed (C) interneurons. In the model each class is represented by one left and one right neuron. Each neuron has basic passive properties akin to biophysical neurons and receives tonic synaptic drive and weighted synaptic input from other connecting neurons. The neuron\u0026#39;s output as a function of voltage is given by a nonlinear function with a strict threshold and saturation. 3. With an appropriate set of parameter values, the voltage of each neuron can oscillate periodically with phase relationships among the different neurons that are qualitatively similar to those observed experimentally. The uPG alone can also oscillate, as observed experimentally in isolated lamprey spinal cords. Varying the parameters can, however, profoundly change the state of the system via different kinds of bifurcations. Change in a single parameter can move the system from nonoscillatory to oscillatory states via different kinds of bifurcations. For some parameter values the system can also exhibit multistable behavior (e.g., an oscillatory state and a nonoscillatory state). The analysis also shows us how the amplitudes of the oscillations vary and the periods of limit cycles change as different bifurcation points are approached. 4. Altering tonic drive to just one class of uPG neurons (without altering the interconnections) can change the state of the system by altering the stability of fixed points, converting fixed points to oscillations, single oscillations to two stable oscillations, etc. Two-parameter bifurcation diagrams show the critical regions in which a balance between the tonic drives is necessary to maintain stable oscillations. A minimum tonic drive is necessary to obtain stable oscillatory output. With appropriate changes in the tonic drives to the L and C neurons, stable oscillatory output can be obtained even after eliminating the E neurons. Indeed, the presence of active E neurons in the biological system does not prove they play a functional role in the system, because tonic drive from other sources can substitute for them. On the other hand, very high excitation of any one class of neurons can terminate oscillations. Appropriate balance of tonic drives to different neuron classes can help sustain stable oscillations for larger tonic drives. Published experimental results concerning changes in amplitude and swimming frequency with increased tonic drives are mimicked by the model\u0026#39;s responses to increased tonic drive. 5. Interconnectivity among the neurons plays a crucial role. The analysis indicates that the C and L classes of neurons are essential components of the model network. Sufficient inhibition from the L to C neurons as well as mutual inhibition between the left and right halves is necessary to obtain stable oscillatory output. When the E neurons are present in the model network, they must receive appropriate tonic drive and provide appropriate excitation","publisher":"American Physiological Society","publication_date":{"day":1,"month":3,"year":1996,"errors":{}},"publication_name":"Journal of Neurophysiology"},"translated_abstract":"1. Experimental studies have shown that a central pattern generator in the spinal cord of the lamprey can produce the basic rhythm for locomotion. This pattern generator interacts with the reticular neurons forming a spinoreticulospinal loop. To better understand and investigate the mechanisms for locomotor pattern generation in the lamprey, we examine the dynamic behavior of a simplified neural network model representing a unit spinal pattern generator (uPG) and its interaction with the reticular system. We use the techniques of bifurcation analysis and specifically examine the effects on the dynamic behavior of the system of 1) changing tonic drives to the different neurons of the uPG; 2) altering inhibitory and excitatory interconnection strengths among the uPG neurons; and 3) feedforward-feedback interactions between the uPG and the reticular neurons. 2. The model analyzed is a qualitative left-right symmetric network based on proposed functional architecture with one class of phasic reticular neurons and three classes of uPG neurons: excitatory (E), lateral (L), and crossed (C) interneurons. In the model each class is represented by one left and one right neuron. Each neuron has basic passive properties akin to biophysical neurons and receives tonic synaptic drive and weighted synaptic input from other connecting neurons. The neuron\u0026#39;s output as a function of voltage is given by a nonlinear function with a strict threshold and saturation. 3. With an appropriate set of parameter values, the voltage of each neuron can oscillate periodically with phase relationships among the different neurons that are qualitatively similar to those observed experimentally. The uPG alone can also oscillate, as observed experimentally in isolated lamprey spinal cords. Varying the parameters can, however, profoundly change the state of the system via different kinds of bifurcations. Change in a single parameter can move the system from nonoscillatory to oscillatory states via different kinds of bifurcations. For some parameter values the system can also exhibit multistable behavior (e.g., an oscillatory state and a nonoscillatory state). The analysis also shows us how the amplitudes of the oscillations vary and the periods of limit cycles change as different bifurcation points are approached. 4. Altering tonic drive to just one class of uPG neurons (without altering the interconnections) can change the state of the system by altering the stability of fixed points, converting fixed points to oscillations, single oscillations to two stable oscillations, etc. Two-parameter bifurcation diagrams show the critical regions in which a balance between the tonic drives is necessary to maintain stable oscillations. A minimum tonic drive is necessary to obtain stable oscillatory output. With appropriate changes in the tonic drives to the L and C neurons, stable oscillatory output can be obtained even after eliminating the E neurons. Indeed, the presence of active E neurons in the biological system does not prove they play a functional role in the system, because tonic drive from other sources can substitute for them. On the other hand, very high excitation of any one class of neurons can terminate oscillations. 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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="123485763"><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/123485763/Novel_Neurostimulation_Based_Haptic_Feedback_Platform_for_Grasp_Interactions_With_Virtual_Objects"><img alt="Research paper thumbnail of Novel Neurostimulation-Based Haptic Feedback Platform for Grasp Interactions With Virtual Objects" class="work-thumbnail" src="https://attachments.academia-assets.com/117905756/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/123485763/Novel_Neurostimulation_Based_Haptic_Feedback_Platform_for_Grasp_Interactions_With_Virtual_Objects">Novel Neurostimulation-Based Haptic Feedback Platform for Grasp Interactions With Virtual Objects</a></div><div class="wp-workCard_item"><span>Frontiers in Virtual Reality</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Haptic perception is a vital part of the human experience that enriches our engagement with the w...</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">Haptic perception is a vital part of the human experience that enriches our engagement with the world, but the ability to provide haptic information in virtual reality (VR) environments is limited. Neurostimulation-based sensory feedback has the potential to enhance the immersive experience within VR environments by supplying relevant and intuitive haptic feedback related to interactions with virtual objects. Such feedback may contribute to an increase in the sense of presence and realism in VR and may contribute to the improvement of virtual reality simulations for future VR applications. This work developed and evaluated xTouch, a neuro-haptic platform that extends the sense of touch to virtual environments. xTouch is capable of tracking a user’s grasp and manipulation interactions with virtual objects and delivering haptic feedback based on the resulting grasp forces. Seven study participants received haptic feedback delivered via multi-channel transcutaneous electrical stimulati...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="2cbc93393a9988ca1bc94215c4dc355c" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":117905756,"asset_id":123485763,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/117905756/download_file?st=MTczMjc4Nzk1Myw4LjIyMi4yMDguMTQ2&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="123485763"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="123485763"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 123485763; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=123485763]").text(description); $(".js-view-count[data-work-id=123485763]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 123485763; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='123485763']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 123485763, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "2cbc93393a9988ca1bc94215c4dc355c" } } $('.js-work-strip[data-work-id=123485763]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":123485763,"title":"Novel Neurostimulation-Based Haptic Feedback Platform for Grasp Interactions With Virtual Objects","translated_title":"","metadata":{"abstract":"Haptic perception is a vital part of the human experience that enriches our engagement with the world, but the ability to provide haptic information in virtual reality (VR) environments is limited. 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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="123485761"><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/123485761/Sensitivity_analysis_of_a_hybrid_neural_network_for_locomotor_control_in_the_lamprey"><img alt="Research paper thumbnail of Sensitivity analysis of a hybrid neural network for locomotor control in the lamprey" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/123485761/Sensitivity_analysis_of_a_hybrid_neural_network_for_locomotor_control_in_the_lamprey">Sensitivity analysis of a hybrid neural network for locomotor control in the lamprey</a></div><div class="wp-workCard_item"><span>Proceedings of the 1997 16 Southern Biomedical Engineering Conference</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Neural circuitry within the spinal cord of the lamprey forms a central pattern generator (CPG) fo...</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">Neural circuitry within the spinal cord of the lamprey forms a central pattern generator (CPG) for locomotor control, which interacts with particular neurons in a reticulo-spino-reticular (RSR) loop. Some of the CPG neurons have pacemaker properties. We have used mathematical models to examine the role of N-methyl-D-aspartate (NMDA) and calcium dependent potassium (KCa channel currents in generating oscillatory outputs in:</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="123485761"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="123485761"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 123485761; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=123485761]").text(description); $(".js-view-count[data-work-id=123485761]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 123485761; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='123485761']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 123485761, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=123485761]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":123485761,"title":"Sensitivity analysis of a hybrid neural network for locomotor control in the lamprey","translated_title":"","metadata":{"abstract":"Neural circuitry within the spinal cord of the lamprey forms a central pattern generator (CPG) for locomotor control, which interacts with particular neurons in a reticulo-spino-reticular (RSR) loop. 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Lack of sensation from a hand or prosthesis can result in substantial functional defic...</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">Objective. Lack of sensation from a hand or prosthesis can result in substantial functional deficits. Surface electrical stimulation of the peripheral nerves is a promising non-invasive approach to restore lost sensory function. However, the utility of standard surface stimulation methods has been hampered by localized discomfort caused by unintended activation of afferents near the electrodes and limited ability to specifically target underlying neural tissue. The objectives of this work were to develop and evaluate a novel channel-hopping interleaved pulse scheduling (CHIPS) strategy for surface stimulation that is designed to activate deep nerves while reducing activation of fibers near the electrodes. Approach. The median nerve of able-bodied subjects was activated by up to two surface stimulating electrode pairs placed around their right wrist. Subjects received biphasic current pulses either from one electrode pair at a time (single-channel), or interleaved between two electro...</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="123485760"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="123485760"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 123485760; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=123485760]").text(description); $(".js-view-count[data-work-id=123485760]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 123485760; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='123485760']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 123485760, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=123485760]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":123485760,"title":"Channel-hopping during surface electrical neurostimulation elicits selective, comfortable, distally referred sensations","translated_title":"","metadata":{"abstract":"Objective. 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The objectives of this work were to develop and evaluate a novel channel-hopping interleaved pulse scheduling (CHIPS) strategy for surface stimulation that is designed to activate deep nerves while reducing activation of fibers near the electrodes. Approach. The median nerve of able-bodied subjects was activated by up to two surface stimulating electrode pairs placed around their right wrist. Subjects received biphasic current pulses either from one electrode pair at a time (single-channel), or interleaved between two electro...","internal_url":"https://www.academia.edu/123485760/Channel_hopping_during_surface_electrical_neurostimulation_elicits_selective_comfortable_distally_referred_sensations","translated_internal_url":"","created_at":"2024-09-02T09:37:46.108-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":38884898,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Channel_hopping_during_surface_electrical_neurostimulation_elicits_selective_comfortable_distally_referred_sensations","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":38884898,"first_name":"Ranu","middle_initials":null,"last_name":"Jung","page_name":"RanuJung","domain_name":"fiu","created_at":"2015-11-22T06:50:19.728-08:00","display_name":"Ranu Jung","url":"https://fiu.academia.edu/RanuJung"},"attachments":[],"research_interests":[{"id":498,"name":"Physics","url":"https://www.academia.edu/Documents/in/Physics"},{"id":1131,"name":"Biomedical Engineering","url":"https://www.academia.edu/Documents/in/Biomedical_Engineering"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":48050,"name":"Neural Prosthesis","url":"https://www.academia.edu/Documents/in/Neural_Prosthesis"},{"id":48051,"name":"Neural Engineering","url":"https://www.academia.edu/Documents/in/Neural_Engineering"},{"id":82660,"name":"Sensation","url":"https://www.academia.edu/Documents/in/Sensation"},{"id":244814,"name":"Clinical Sciences","url":"https://www.academia.edu/Documents/in/Clinical_Sciences"},{"id":480873,"name":"Neurostimulation","url":"https://www.academia.edu/Documents/in/Neurostimulation"},{"id":541937,"name":"Stimulation","url":"https://www.academia.edu/Documents/in/Stimulation"},{"id":1239755,"name":"Neurosciences","url":"https://www.academia.edu/Documents/in/Neurosciences"}],"urls":[{"id":44419626,"url":"https://iopscience.iop.org/article/10.1088/1741-2552/abf28c/pdf"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="123485759"><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/123485759/Site_specific_variability_in_spinal_motor_output"><img alt="Research paper thumbnail of Site specific variability in spinal motor output" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/123485759/Site_specific_variability_in_spinal_motor_output">Site specific variability in spinal motor output</a></div><div class="wp-workCard_item"><span>Proceedings of the First Joint BMES/EMBS Conference. 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Annual Fall Meeting of the Biomedical Engineering Society (Cat. No.99CH37015)</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">In several vertebrates spinal neural networks are capable of generating motor output. In studies ...</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 several vertebrates spinal neural networks are capable of generating motor output. In studies on isolated brain-spinal cord preparations of a lower vertebrate, the lamprey, we show that dynamic brain-spinal cord interactions alter the locomotor rhythm that is generated by the distributed spinal pattern generators. Our analyses, which utilize wavelet and novel time-varying covariance methods, indicate that brain-spinal cord interactions have an inhibitory influence on the frequency of the rhythm. However, they contribute to higher variability in motor output. Variability is assessed from the coefficient of variance (CV) and decay in autocovariance. We find that neural activity recorded from rostral segments closer to the brain shows higher variability, i.e. variability is site specific. Since the rostral to caudal gradient persists after suppression of brain-spinal cord communication, it may reflect asymmetries within the spinal neural organization.</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="123485759"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="123485759"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 123485759; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=123485759]").text(description); $(".js-view-count[data-work-id=123485759]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 123485759; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='123485759']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 123485759, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=123485759]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":123485759,"title":"Site specific variability in spinal motor output","translated_title":"","metadata":{"abstract":"In several vertebrates spinal neural networks are capable of generating motor output. In studies on isolated brain-spinal cord preparations of a lower vertebrate, the lamprey, we show that dynamic brain-spinal cord interactions alter the locomotor rhythm that is generated by the distributed spinal pattern generators. Our analyses, which utilize wavelet and novel time-varying covariance methods, indicate that brain-spinal cord interactions have an inhibitory influence on the frequency of the rhythm. However, they contribute to higher variability in motor output. Variability is assessed from the coefficient of variance (CV) and decay in autocovariance. We find that neural activity recorded from rostral segments closer to the brain shows higher variability, i.e. variability is site specific. 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However, they contribute to higher variability in motor output. Variability is assessed from the coefficient of variance (CV) and decay in autocovariance. We find that neural activity recorded from rostral segments closer to the brain shows higher variability, i.e. variability is site specific. 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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="123485749"><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/123485749/Response_to_Perturbations_of_a_Neural_Network_Model_of_Locomotor_Control_in_the_Lamprey"><img alt="Research paper thumbnail of Response to Perturbations of a Neural Network Model of Locomotor Control in the Lamprey" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/123485749/Response_to_Perturbations_of_a_Neural_Network_Model_of_Locomotor_Control_in_the_Lamprey">Response to Perturbations of a Neural Network Model of Locomotor Control in the Lamprey</a></div><div class="wp-workCard_item"><span>Computational Neuroscience</span><span>, 1998</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">In several vertebrates, stable rhythmic locomotor activity can be obtained from neural networks i...</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 several vertebrates, stable rhythmic locomotor activity can be obtained from neural networks in the spinal cord without external periodic forcing. In an active animal, the spinal central pattern generator (CPG) is dynamically affected by descending input from the brain as well as afferent sensory inputs.1 While certain aspects of spinal CPG mechanisms for locomotor control have been well investigated, 3,8 the interactions of the CPG with the descending supraspinal inputs and sensory inputs are not well understood. Changes in the topology of the system caused by modifying the supraspinal-spinal CPG interactions are likely to influence the response of the system to external perturbations.</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="123485749"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="123485749"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 123485749; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=123485749]").text(description); $(".js-view-count[data-work-id=123485749]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 123485749; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='123485749']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 123485749, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=123485749]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":123485749,"title":"Response to Perturbations of a Neural Network Model of Locomotor Control in the Lamprey","translated_title":"","metadata":{"abstract":"In several vertebrates, stable rhythmic locomotor activity can be obtained from neural networks in the spinal cord without external periodic forcing. 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Changes in the topology of the system caused by modifying the supraspinal-spinal CPG interactions are likely to influence the response of the system to external perturbations.","internal_url":"https://www.academia.edu/123485749/Response_to_Perturbations_of_a_Neural_Network_Model_of_Locomotor_Control_in_the_Lamprey","translated_internal_url":"","created_at":"2024-09-02T09:37:44.131-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":38884898,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Response_to_Perturbations_of_a_Neural_Network_Model_of_Locomotor_Control_in_the_Lamprey","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":38884898,"first_name":"Ranu","middle_initials":null,"last_name":"Jung","page_name":"RanuJung","domain_name":"fiu","created_at":"2015-11-22T06:50:19.728-08:00","display_name":"Ranu Jung","url":"https://fiu.academia.edu/RanuJung"},"attachments":[],"research_interests":[{"id":161,"name":"Neuroscience","url":"https://www.academia.edu/Documents/in/Neuroscience"},{"id":5451,"name":"Computational Neuroscience","url":"https://www.academia.edu/Documents/in/Computational_Neuroscience"},{"id":7710,"name":"Biology","url":"https://www.academia.edu/Documents/in/Biology"},{"id":99421,"name":"Spinal Cord","url":"https://www.academia.edu/Documents/in/Spinal_Cord"},{"id":383830,"name":"Lamprey","url":"https://www.academia.edu/Documents/in/Lamprey"},{"id":3647879,"name":"Springer Ebooks","url":"https://www.academia.edu/Documents/in/Springer_Ebooks"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="123485748"><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/123485748/Simulation_of_the_Spinal_Circuits_Controlling_Swimming_Movements_in_Fish"><img alt="Research paper thumbnail of Simulation of the Spinal Circuits Controlling Swimming Movements in Fish" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/123485748/Simulation_of_the_Spinal_Circuits_Controlling_Swimming_Movements_in_Fish">Simulation of the Spinal Circuits Controlling Swimming Movements in Fish</a></div><div class="wp-workCard_item"><span>Biomechanics and Neural Control of Posture and Movement</span><span>, 2000</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Limb movements in humans and other higher vertebrates are generated through a complex interplay b...</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">Limb movements in humans and other higher vertebrates are generated through a complex interplay between the mechanical apparatus and the central nervous system. Understanding of this neuromechanical system entails more than just a knowledge of its constituent parts. It is necessary to find ways of combining our knowledge of the mechanical system with that of the controlling neuronal circuitry. Both parts by themselves are far from trivial and computer simulation has emerged as an indispensable tool in the task of understanding how they cooperate.</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="123485748"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="123485748"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 123485748; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=123485748]").text(description); $(".js-view-count[data-work-id=123485748]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 123485748; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='123485748']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 123485748, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=123485748]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":123485748,"title":"Simulation of the Spinal Circuits Controlling Swimming Movements in Fish","translated_title":"","metadata":{"abstract":"Limb movements in humans and other higher vertebrates are generated through a complex interplay between the mechanical apparatus and the central nervous system. Understanding of this neuromechanical system entails more than just a knowledge of its constituent parts. It is necessary to find ways of combining our knowledge of the mechanical system with that of the controlling neuronal circuitry. Both parts by themselves are far from trivial and computer simulation has emerged as an indispensable tool in the task of understanding how they cooperate.","publication_date":{"day":null,"month":null,"year":2000,"errors":{}},"publication_name":"Biomechanics and Neural Control of Posture and Movement"},"translated_abstract":"Limb movements in humans and other higher vertebrates are generated through a complex interplay between the mechanical apparatus and the central nervous system. Understanding of this neuromechanical system entails more than just a knowledge of its constituent parts. It is necessary to find ways of combining our knowledge of the mechanical system with that of the controlling neuronal circuitry. Both parts by themselves are far from trivial and computer simulation has emerged as an indispensable tool in the task of understanding how they cooperate.","internal_url":"https://www.academia.edu/123485748/Simulation_of_the_Spinal_Circuits_Controlling_Swimming_Movements_in_Fish","translated_internal_url":"","created_at":"2024-09-02T09:37:43.958-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":38884898,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Simulation_of_the_Spinal_Circuits_Controlling_Swimming_Movements_in_Fish","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":38884898,"first_name":"Ranu","middle_initials":null,"last_name":"Jung","page_name":"RanuJung","domain_name":"fiu","created_at":"2015-11-22T06:50:19.728-08:00","display_name":"Ranu Jung","url":"https://fiu.academia.edu/RanuJung"},"attachments":[],"research_interests":[{"id":161,"name":"Neuroscience","url":"https://www.academia.edu/Documents/in/Neuroscience"},{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science"},{"id":472,"name":"Human Computer Interaction","url":"https://www.academia.edu/Documents/in/Human_Computer_Interaction"},{"id":3647879,"name":"Springer Ebooks","url":"https://www.academia.edu/Documents/in/Springer_Ebooks"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="123485747"><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/123485747/Specific_Overground_Walking_Kinematic_Measures_are_Related_to_Degree_of_Spinal_Injury_in_the_Rat"><img alt="Research paper thumbnail of Specific Overground Walking Kinematic Measures are Related to Degree of Spinal Injury in the Rat" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/123485747/Specific_Overground_Walking_Kinematic_Measures_are_Related_to_Degree_of_Spinal_Injury_in_the_Rat">Specific Overground Walking Kinematic Measures are Related to Degree of Spinal Injury in the Rat</a></div><div class="wp-workCard_item"><span>2013 29th Southern Biomedical Engineering Conference</span><span>, 2013</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">ABSTRACT After incomplete spinal cord thoracic injury (iSCI) rodents retain locomotor capability....</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">ABSTRACT After incomplete spinal cord thoracic injury (iSCI) rodents retain locomotor capability. We tested the hypothesis that the degree of retained function would be related to the sparing of spinal tissue. Hindlimb stance width, hindfoot rotation, stride length, and velocity during overground walking and qualitative Basso, Beattie, and Bresnahan (BBB) locomotor scores were obtained in 5 rats with mild-moderate iSCI (T10 injury caused by 10 gm, 2 mm New York University impactor probe dropped from 12.5 mm). The extent of injury was estimated from histological sections stained for myelin by calculating percent volumes of gray matter (%GM) and white matter (%WM) spared for a 9 mm cord section. The white and grey matter volumes were 19.6+/-3.9 (mean+/-SD) and 4.5+/-1.8 cubic mm respectively. This resulted in 47.6+/-6.5 %WM and 10.9+/-4.0 %GM being spared. Kinematic measures of stance width and hindfoot limb rotation showed a significant negative correlation with %WM spared (r=-0.924 and -0.87 8). All other measures did not show significant correlation. BBB showed a significant positive correlation with %WM spared (r=0.93). None of the measures showed significant correlations with %GM spared. The data indicate that impairment of specific features of overground walking is related to the loss of axonal connections after iSCI.</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="123485747"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="123485747"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 123485747; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=123485747]").text(description); $(".js-view-count[data-work-id=123485747]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 123485747; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='123485747']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 123485747, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=123485747]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":123485747,"title":"Specific Overground Walking Kinematic Measures are Related to Degree of Spinal Injury in the Rat","translated_title":"","metadata":{"abstract":"ABSTRACT After incomplete spinal cord thoracic injury (iSCI) rodents retain locomotor capability. We tested the hypothesis that the degree of retained function would be related to the sparing of spinal tissue. Hindlimb stance width, hindfoot rotation, stride length, and velocity during overground walking and qualitative Basso, Beattie, and Bresnahan (BBB) locomotor scores were obtained in 5 rats with mild-moderate iSCI (T10 injury caused by 10 gm, 2 mm New York University impactor probe dropped from 12.5 mm). The extent of injury was estimated from histological sections stained for myelin by calculating percent volumes of gray matter (%GM) and white matter (%WM) spared for a 9 mm cord section. The white and grey matter volumes were 19.6+/-3.9 (mean+/-SD) and 4.5+/-1.8 cubic mm respectively. This resulted in 47.6+/-6.5 %WM and 10.9+/-4.0 %GM being spared. Kinematic measures of stance width and hindfoot limb rotation showed a significant negative correlation with %WM spared (r=-0.924 and -0.87 8). All other measures did not show significant correlation. BBB showed a significant positive correlation with %WM spared (r=0.93). None of the measures showed significant correlations with %GM spared. The data indicate that impairment of specific features of overground walking is related to the loss of axonal connections after iSCI.","publisher":"IEEE","publication_date":{"day":null,"month":null,"year":2013,"errors":{}},"publication_name":"2013 29th Southern Biomedical Engineering Conference"},"translated_abstract":"ABSTRACT After incomplete spinal cord thoracic injury (iSCI) rodents retain locomotor capability. We tested the hypothesis that the degree of retained function would be related to the sparing of spinal tissue. Hindlimb stance width, hindfoot rotation, stride length, and velocity during overground walking and qualitative Basso, Beattie, and Bresnahan (BBB) locomotor scores were obtained in 5 rats with mild-moderate iSCI (T10 injury caused by 10 gm, 2 mm New York University impactor probe dropped from 12.5 mm). The extent of injury was estimated from histological sections stained for myelin by calculating percent volumes of gray matter (%GM) and white matter (%WM) spared for a 9 mm cord section. The white and grey matter volumes were 19.6+/-3.9 (mean+/-SD) and 4.5+/-1.8 cubic mm respectively. This resulted in 47.6+/-6.5 %WM and 10.9+/-4.0 %GM being spared. Kinematic measures of stance width and hindfoot limb rotation showed a significant negative correlation with %WM spared (r=-0.924 and -0.87 8). All other measures did not show significant correlation. BBB showed a significant positive correlation with %WM spared (r=0.93). None of the measures showed significant correlations with %GM spared. The data indicate that impairment of specific features of overground walking is related to the loss of axonal connections after iSCI.","internal_url":"https://www.academia.edu/123485747/Specific_Overground_Walking_Kinematic_Measures_are_Related_to_Degree_of_Spinal_Injury_in_the_Rat","translated_internal_url":"","created_at":"2024-09-02T09:37:43.764-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":38884898,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Specific_Overground_Walking_Kinematic_Measures_are_Related_to_Degree_of_Spinal_Injury_in_the_Rat","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":38884898,"first_name":"Ranu","middle_initials":null,"last_name":"Jung","page_name":"RanuJung","domain_name":"fiu","created_at":"2015-11-22T06:50:19.728-08:00","display_name":"Ranu Jung","url":"https://fiu.academia.edu/RanuJung"},"attachments":[],"research_interests":[{"id":22824,"name":"Spinal Cord Injury","url":"https://www.academia.edu/Documents/in/Spinal_Cord_Injury"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":99421,"name":"Spinal Cord","url":"https://www.academia.edu/Documents/in/Spinal_Cord"},{"id":362036,"name":"White matter","url":"https://www.academia.edu/Documents/in/White_matter"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="123485746"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/123485746/Merging_Technology_with_Biology"><img alt="Research paper thumbnail of Merging Technology with Biology" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/123485746/Merging_Technology_with_Biology">Merging Technology with Biology</a></div><div class="wp-workCard_item"><span>Nerves, Interfaces, and Machines</span><span>, 2011</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="123485746"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="123485746"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 123485746; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> </div><div class="profile--tab_content_container js-tab-pane tab-pane" data-section-id="4105700" id="papers"><div class="js-work-strip profile--work_container" data-work-id="123485771"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/123485771/Peripheral_Nerve_Interface_Applications_EMG_ENG"><img alt="Research paper thumbnail of Peripheral Nerve Interface Applications, EMG/ENG" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/123485771/Peripheral_Nerve_Interface_Applications_EMG_ENG">Peripheral Nerve Interface Applications, EMG/ENG</a></div><div class="wp-workCard_item"><span>Springer eBooks</span><span>, 2022</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="123485771"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="123485771"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 123485771; 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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="123485770"><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/123485770/Dynamic_behavior_of_a_neural_network_model_of_locomotor_control_in_the_lamprey"><img alt="Research paper thumbnail of Dynamic behavior of a neural network model of locomotor control in the lamprey" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/123485770/Dynamic_behavior_of_a_neural_network_model_of_locomotor_control_in_the_lamprey">Dynamic behavior of a neural network model of locomotor control in the lamprey</a></div><div class="wp-workCard_item"><span>Journal of Neurophysiology</span><span>, Mar 1, 1996</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">1. Experimental studies have shown that a central pattern generator in the spinal cord of the lam...</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">1. Experimental studies have shown that a central pattern generator in the spinal cord of the lamprey can produce the basic rhythm for locomotion. This pattern generator interacts with the reticular neurons forming a spinoreticulospinal loop. To better understand and investigate the mechanisms for locomotor pattern generation in the lamprey, we examine the dynamic behavior of a simplified neural network model representing a unit spinal pattern generator (uPG) and its interaction with the reticular system. We use the techniques of bifurcation analysis and specifically examine the effects on the dynamic behavior of the system of 1) changing tonic drives to the different neurons of the uPG; 2) altering inhibitory and excitatory interconnection strengths among the uPG neurons; and 3) feedforward-feedback interactions between the uPG and the reticular neurons. 2. The model analyzed is a qualitative left-right symmetric network based on proposed functional architecture with one class of phasic reticular neurons and three classes of uPG neurons: excitatory (E), lateral (L), and crossed (C) interneurons. In the model each class is represented by one left and one right neuron. Each neuron has basic passive properties akin to biophysical neurons and receives tonic synaptic drive and weighted synaptic input from other connecting neurons. The neuron&#39;s output as a function of voltage is given by a nonlinear function with a strict threshold and saturation. 3. With an appropriate set of parameter values, the voltage of each neuron can oscillate periodically with phase relationships among the different neurons that are qualitatively similar to those observed experimentally. The uPG alone can also oscillate, as observed experimentally in isolated lamprey spinal cords. Varying the parameters can, however, profoundly change the state of the system via different kinds of bifurcations. Change in a single parameter can move the system from nonoscillatory to oscillatory states via different kinds of bifurcations. For some parameter values the system can also exhibit multistable behavior (e.g., an oscillatory state and a nonoscillatory state). The analysis also shows us how the amplitudes of the oscillations vary and the periods of limit cycles change as different bifurcation points are approached. 4. Altering tonic drive to just one class of uPG neurons (without altering the interconnections) can change the state of the system by altering the stability of fixed points, converting fixed points to oscillations, single oscillations to two stable oscillations, etc. Two-parameter bifurcation diagrams show the critical regions in which a balance between the tonic drives is necessary to maintain stable oscillations. A minimum tonic drive is necessary to obtain stable oscillatory output. With appropriate changes in the tonic drives to the L and C neurons, stable oscillatory output can be obtained even after eliminating the E neurons. Indeed, the presence of active E neurons in the biological system does not prove they play a functional role in the system, because tonic drive from other sources can substitute for them. On the other hand, very high excitation of any one class of neurons can terminate oscillations. Appropriate balance of tonic drives to different neuron classes can help sustain stable oscillations for larger tonic drives. Published experimental results concerning changes in amplitude and swimming frequency with increased tonic drives are mimicked by the model&#39;s responses to increased tonic drive. 5. Interconnectivity among the neurons plays a crucial role. The analysis indicates that the C and L classes of neurons are essential components of the model network. Sufficient inhibition from the L to C neurons as well as mutual inhibition between the left and right halves is necessary to obtain stable oscillatory output. When the E neurons are present in the model network, they must receive appropriate tonic drive and provide appropriate excitation</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="123485770"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="123485770"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 123485770; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=123485770]").text(description); $(".js-view-count[data-work-id=123485770]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 123485770; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='123485770']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 123485770, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=123485770]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":123485770,"title":"Dynamic behavior of a neural network model of locomotor control in the lamprey","translated_title":"","metadata":{"abstract":"1. Experimental studies have shown that a central pattern generator in the spinal cord of the lamprey can produce the basic rhythm for locomotion. This pattern generator interacts with the reticular neurons forming a spinoreticulospinal loop. To better understand and investigate the mechanisms for locomotor pattern generation in the lamprey, we examine the dynamic behavior of a simplified neural network model representing a unit spinal pattern generator (uPG) and its interaction with the reticular system. We use the techniques of bifurcation analysis and specifically examine the effects on the dynamic behavior of the system of 1) changing tonic drives to the different neurons of the uPG; 2) altering inhibitory and excitatory interconnection strengths among the uPG neurons; and 3) feedforward-feedback interactions between the uPG and the reticular neurons. 2. The model analyzed is a qualitative left-right symmetric network based on proposed functional architecture with one class of phasic reticular neurons and three classes of uPG neurons: excitatory (E), lateral (L), and crossed (C) interneurons. In the model each class is represented by one left and one right neuron. Each neuron has basic passive properties akin to biophysical neurons and receives tonic synaptic drive and weighted synaptic input from other connecting neurons. The neuron\u0026#39;s output as a function of voltage is given by a nonlinear function with a strict threshold and saturation. 3. With an appropriate set of parameter values, the voltage of each neuron can oscillate periodically with phase relationships among the different neurons that are qualitatively similar to those observed experimentally. The uPG alone can also oscillate, as observed experimentally in isolated lamprey spinal cords. Varying the parameters can, however, profoundly change the state of the system via different kinds of bifurcations. Change in a single parameter can move the system from nonoscillatory to oscillatory states via different kinds of bifurcations. For some parameter values the system can also exhibit multistable behavior (e.g., an oscillatory state and a nonoscillatory state). The analysis also shows us how the amplitudes of the oscillations vary and the periods of limit cycles change as different bifurcation points are approached. 4. Altering tonic drive to just one class of uPG neurons (without altering the interconnections) can change the state of the system by altering the stability of fixed points, converting fixed points to oscillations, single oscillations to two stable oscillations, etc. Two-parameter bifurcation diagrams show the critical regions in which a balance between the tonic drives is necessary to maintain stable oscillations. A minimum tonic drive is necessary to obtain stable oscillatory output. With appropriate changes in the tonic drives to the L and C neurons, stable oscillatory output can be obtained even after eliminating the E neurons. Indeed, the presence of active E neurons in the biological system does not prove they play a functional role in the system, because tonic drive from other sources can substitute for them. On the other hand, very high excitation of any one class of neurons can terminate oscillations. Appropriate balance of tonic drives to different neuron classes can help sustain stable oscillations for larger tonic drives. Published experimental results concerning changes in amplitude and swimming frequency with increased tonic drives are mimicked by the model\u0026#39;s responses to increased tonic drive. 5. Interconnectivity among the neurons plays a crucial role. The analysis indicates that the C and L classes of neurons are essential components of the model network. Sufficient inhibition from the L to C neurons as well as mutual inhibition between the left and right halves is necessary to obtain stable oscillatory output. When the E neurons are present in the model network, they must receive appropriate tonic drive and provide appropriate excitation","publisher":"American Physiological Society","publication_date":{"day":1,"month":3,"year":1996,"errors":{}},"publication_name":"Journal of Neurophysiology"},"translated_abstract":"1. Experimental studies have shown that a central pattern generator in the spinal cord of the lamprey can produce the basic rhythm for locomotion. This pattern generator interacts with the reticular neurons forming a spinoreticulospinal loop. To better understand and investigate the mechanisms for locomotor pattern generation in the lamprey, we examine the dynamic behavior of a simplified neural network model representing a unit spinal pattern generator (uPG) and its interaction with the reticular system. We use the techniques of bifurcation analysis and specifically examine the effects on the dynamic behavior of the system of 1) changing tonic drives to the different neurons of the uPG; 2) altering inhibitory and excitatory interconnection strengths among the uPG neurons; and 3) feedforward-feedback interactions between the uPG and the reticular neurons. 2. The model analyzed is a qualitative left-right symmetric network based on proposed functional architecture with one class of phasic reticular neurons and three classes of uPG neurons: excitatory (E), lateral (L), and crossed (C) interneurons. In the model each class is represented by one left and one right neuron. Each neuron has basic passive properties akin to biophysical neurons and receives tonic synaptic drive and weighted synaptic input from other connecting neurons. The neuron\u0026#39;s output as a function of voltage is given by a nonlinear function with a strict threshold and saturation. 3. With an appropriate set of parameter values, the voltage of each neuron can oscillate periodically with phase relationships among the different neurons that are qualitatively similar to those observed experimentally. The uPG alone can also oscillate, as observed experimentally in isolated lamprey spinal cords. Varying the parameters can, however, profoundly change the state of the system via different kinds of bifurcations. Change in a single parameter can move the system from nonoscillatory to oscillatory states via different kinds of bifurcations. For some parameter values the system can also exhibit multistable behavior (e.g., an oscillatory state and a nonoscillatory state). The analysis also shows us how the amplitudes of the oscillations vary and the periods of limit cycles change as different bifurcation points are approached. 4. Altering tonic drive to just one class of uPG neurons (without altering the interconnections) can change the state of the system by altering the stability of fixed points, converting fixed points to oscillations, single oscillations to two stable oscillations, etc. Two-parameter bifurcation diagrams show the critical regions in which a balance between the tonic drives is necessary to maintain stable oscillations. A minimum tonic drive is necessary to obtain stable oscillatory output. With appropriate changes in the tonic drives to the L and C neurons, stable oscillatory output can be obtained even after eliminating the E neurons. Indeed, the presence of active E neurons in the biological system does not prove they play a functional role in the system, because tonic drive from other sources can substitute for them. On the other hand, very high excitation of any one class of neurons can terminate oscillations. Appropriate balance of tonic drives to different neuron classes can help sustain stable oscillations for larger tonic drives. Published experimental results concerning changes in amplitude and swimming frequency with increased tonic drives are mimicked by the model\u0026#39;s responses to increased tonic drive. 5. Interconnectivity among the neurons plays a crucial role. The analysis indicates that the C and L classes of neurons are essential components of the model network. Sufficient inhibition from the L to C neurons as well as mutual inhibition between the left and right halves is necessary to obtain stable oscillatory output. When the E neurons are present in the model network, they must receive appropriate tonic drive and provide appropriate excitation","internal_url":"https://www.academia.edu/123485770/Dynamic_behavior_of_a_neural_network_model_of_locomotor_control_in_the_lamprey","translated_internal_url":"","created_at":"2024-09-02T09:37:48.514-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":38884898,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Dynamic_behavior_of_a_neural_network_model_of_locomotor_control_in_the_lamprey","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":38884898,"first_name":"Ranu","middle_initials":null,"last_name":"Jung","page_name":"RanuJung","domain_name":"fiu","created_at":"2015-11-22T06:50:19.728-08:00","display_name":"Ranu 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data-click-track="profile-work-strip-title" href="https://www.academia.edu/123485769/Excitation_inhibition_and_coordination_of_cortical_neurones">Excitation, inhibition and coordination of cortical neurones</a></div><div class="wp-workCard_item"><span>PubMed</span><span>, 1958</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="123485769"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="123485769"><i class="fa fa-spinner 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href="https://www.academia.edu/123485763/Novel_Neurostimulation_Based_Haptic_Feedback_Platform_for_Grasp_Interactions_With_Virtual_Objects"><img alt="Research paper thumbnail of Novel Neurostimulation-Based Haptic Feedback Platform for Grasp Interactions With Virtual Objects" class="work-thumbnail" src="https://attachments.academia-assets.com/117905756/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/123485763/Novel_Neurostimulation_Based_Haptic_Feedback_Platform_for_Grasp_Interactions_With_Virtual_Objects">Novel Neurostimulation-Based Haptic Feedback Platform for Grasp Interactions With Virtual Objects</a></div><div class="wp-workCard_item"><span>Frontiers in Virtual Reality</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Haptic perception is a vital part of the human experience that enriches our engagement with the w...</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">Haptic perception is a vital part of the human experience that enriches our engagement with the world, but the ability to provide haptic information in virtual reality (VR) environments is limited. Neurostimulation-based sensory feedback has the potential to enhance the immersive experience within VR environments by supplying relevant and intuitive haptic feedback related to interactions with virtual objects. Such feedback may contribute to an increase in the sense of presence and realism in VR and may contribute to the improvement of virtual reality simulations for future VR applications. This work developed and evaluated xTouch, a neuro-haptic platform that extends the sense of touch to virtual environments. xTouch is capable of tracking a user’s grasp and manipulation interactions with virtual objects and delivering haptic feedback based on the resulting grasp forces. Seven study participants received haptic feedback delivered via multi-channel transcutaneous electrical stimulati...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="2cbc93393a9988ca1bc94215c4dc355c" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":117905756,"asset_id":123485763,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/117905756/download_file?st=MTczMjc4Nzk1NCw4LjIyMi4yMDguMTQ2&st=MTczMjc4Nzk1Myw4LjIyMi4yMDguMTQ2&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="123485763"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="123485763"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 123485763; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=123485763]").text(description); $(".js-view-count[data-work-id=123485763]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 123485763; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='123485763']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 123485763, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "2cbc93393a9988ca1bc94215c4dc355c" } } $('.js-work-strip[data-work-id=123485763]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":123485763,"title":"Novel Neurostimulation-Based Haptic Feedback Platform for Grasp Interactions With Virtual Objects","translated_title":"","metadata":{"abstract":"Haptic perception is a vital part of the human experience that enriches our engagement with the world, but the ability to provide haptic information in virtual reality (VR) environments is limited. 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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="123485761"><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/123485761/Sensitivity_analysis_of_a_hybrid_neural_network_for_locomotor_control_in_the_lamprey"><img alt="Research paper thumbnail of Sensitivity analysis of a hybrid neural network for locomotor control in the lamprey" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/123485761/Sensitivity_analysis_of_a_hybrid_neural_network_for_locomotor_control_in_the_lamprey">Sensitivity analysis of a hybrid neural network for locomotor control in the lamprey</a></div><div class="wp-workCard_item"><span>Proceedings of the 1997 16 Southern Biomedical Engineering Conference</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Neural circuitry within the spinal cord of the lamprey forms a central pattern generator (CPG) fo...</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">Neural circuitry within the spinal cord of the lamprey forms a central pattern generator (CPG) for locomotor control, which interacts with particular neurons in a reticulo-spino-reticular (RSR) loop. 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We have used mathematical models to examine the role of N-methyl-D-aspartate (NMDA) and calcium dependent potassium (KCa channel currents in generating oscillatory outputs in:</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="123485761"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="123485761"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 123485761; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=123485761]").text(description); $(".js-view-count[data-work-id=123485761]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 123485761; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='123485761']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 123485761, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=123485761]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":123485761,"title":"Sensitivity analysis of a hybrid neural network for locomotor control in the lamprey","translated_title":"","metadata":{"abstract":"Neural circuitry within the spinal cord of the lamprey forms a central pattern generator (CPG) for locomotor control, which interacts with particular neurons in a reticulo-spino-reticular (RSR) loop. 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Lack of sensation from a hand or prosthesis can result in substantial functional defic...</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">Objective. Lack of sensation from a hand or prosthesis can result in substantial functional deficits. Surface electrical stimulation of the peripheral nerves is a promising non-invasive approach to restore lost sensory function. However, the utility of standard surface stimulation methods has been hampered by localized discomfort caused by unintended activation of afferents near the electrodes and limited ability to specifically target underlying neural tissue. The objectives of this work were to develop and evaluate a novel channel-hopping interleaved pulse scheduling (CHIPS) strategy for surface stimulation that is designed to activate deep nerves while reducing activation of fibers near the electrodes. Approach. The median nerve of able-bodied subjects was activated by up to two surface stimulating electrode pairs placed around their right wrist. Subjects received biphasic current pulses either from one electrode pair at a time (single-channel), or interleaved between two electro...</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="123485760"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="123485760"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 123485760; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=123485760]").text(description); $(".js-view-count[data-work-id=123485760]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 123485760; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='123485760']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 123485760, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=123485760]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":123485760,"title":"Channel-hopping during surface electrical neurostimulation elicits selective, comfortable, distally referred sensations","translated_title":"","metadata":{"abstract":"Objective. Lack of sensation from a hand or prosthesis can result in substantial functional deficits. Surface electrical stimulation of the peripheral nerves is a promising non-invasive approach to restore lost sensory function. However, the utility of standard surface stimulation methods has been hampered by localized discomfort caused by unintended activation of afferents near the electrodes and limited ability to specifically target underlying neural tissue. The objectives of this work were to develop and evaluate a novel channel-hopping interleaved pulse scheduling (CHIPS) strategy for surface stimulation that is designed to activate deep nerves while reducing activation of fibers near the electrodes. Approach. The median nerve of able-bodied subjects was activated by up to two surface stimulating electrode pairs placed around their right wrist. Subjects received biphasic current pulses either from one electrode pair at a time (single-channel), or interleaved between two electro...","publisher":"IOP Publishing","publication_date":{"day":null,"month":null,"year":2021,"errors":{}},"publication_name":"Journal of Neural Engineering"},"translated_abstract":"Objective. Lack of sensation from a hand or prosthesis can result in substantial functional deficits. Surface electrical stimulation of the peripheral nerves is a promising non-invasive approach to restore lost sensory function. However, the utility of standard surface stimulation methods has been hampered by localized discomfort caused by unintended activation of afferents near the electrodes and limited ability to specifically target underlying neural tissue. The objectives of this work were to develop and evaluate a novel channel-hopping interleaved pulse scheduling (CHIPS) strategy for surface stimulation that is designed to activate deep nerves while reducing activation of fibers near the electrodes. Approach. The median nerve of able-bodied subjects was activated by up to two surface stimulating electrode pairs placed around their right wrist. Subjects received biphasic current pulses either from one electrode pair at a time (single-channel), or interleaved between two electro...","internal_url":"https://www.academia.edu/123485760/Channel_hopping_during_surface_electrical_neurostimulation_elicits_selective_comfortable_distally_referred_sensations","translated_internal_url":"","created_at":"2024-09-02T09:37:46.108-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":38884898,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Channel_hopping_during_surface_electrical_neurostimulation_elicits_selective_comfortable_distally_referred_sensations","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":38884898,"first_name":"Ranu","middle_initials":null,"last_name":"Jung","page_name":"RanuJung","domain_name":"fiu","created_at":"2015-11-22T06:50:19.728-08:00","display_name":"Ranu Jung","url":"https://fiu.academia.edu/RanuJung"},"attachments":[],"research_interests":[{"id":498,"name":"Physics","url":"https://www.academia.edu/Documents/in/Physics"},{"id":1131,"name":"Biomedical Engineering","url":"https://www.academia.edu/Documents/in/Biomedical_Engineering"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":48050,"name":"Neural Prosthesis","url":"https://www.academia.edu/Documents/in/Neural_Prosthesis"},{"id":48051,"name":"Neural Engineering","url":"https://www.academia.edu/Documents/in/Neural_Engineering"},{"id":82660,"name":"Sensation","url":"https://www.academia.edu/Documents/in/Sensation"},{"id":244814,"name":"Clinical Sciences","url":"https://www.academia.edu/Documents/in/Clinical_Sciences"},{"id":480873,"name":"Neurostimulation","url":"https://www.academia.edu/Documents/in/Neurostimulation"},{"id":541937,"name":"Stimulation","url":"https://www.academia.edu/Documents/in/Stimulation"},{"id":1239755,"name":"Neurosciences","url":"https://www.academia.edu/Documents/in/Neurosciences"}],"urls":[{"id":44419626,"url":"https://iopscience.iop.org/article/10.1088/1741-2552/abf28c/pdf"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="123485759"><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/123485759/Site_specific_variability_in_spinal_motor_output"><img alt="Research paper thumbnail of Site specific variability in spinal motor output" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/123485759/Site_specific_variability_in_spinal_motor_output">Site specific variability in spinal motor output</a></div><div class="wp-workCard_item"><span>Proceedings of the First Joint BMES/EMBS Conference. 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Annual Fall Meeting of the Biomedical Engineering Society (Cat. No.99CH37015)</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">In several vertebrates spinal neural networks are capable of generating motor output. In studies ...</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 several vertebrates spinal neural networks are capable of generating motor output. In studies on isolated brain-spinal cord preparations of a lower vertebrate, the lamprey, we show that dynamic brain-spinal cord interactions alter the locomotor rhythm that is generated by the distributed spinal pattern generators. Our analyses, which utilize wavelet and novel time-varying covariance methods, indicate that brain-spinal cord interactions have an inhibitory influence on the frequency of the rhythm. However, they contribute to higher variability in motor output. Variability is assessed from the coefficient of variance (CV) and decay in autocovariance. We find that neural activity recorded from rostral segments closer to the brain shows higher variability, i.e. variability is site specific. Since the rostral to caudal gradient persists after suppression of brain-spinal cord communication, it may reflect asymmetries within the spinal neural organization.</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="123485759"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="123485759"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 123485759; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=123485759]").text(description); $(".js-view-count[data-work-id=123485759]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 123485759; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='123485759']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 123485759, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=123485759]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":123485759,"title":"Site specific variability in spinal motor output","translated_title":"","metadata":{"abstract":"In several vertebrates spinal neural networks are capable of generating motor output. In studies on isolated brain-spinal cord preparations of a lower vertebrate, the lamprey, we show that dynamic brain-spinal cord interactions alter the locomotor rhythm that is generated by the distributed spinal pattern generators. Our analyses, which utilize wavelet and novel time-varying covariance methods, indicate that brain-spinal cord interactions have an inhibitory influence on the frequency of the rhythm. However, they contribute to higher variability in motor output. Variability is assessed from the coefficient of variance (CV) and decay in autocovariance. We find that neural activity recorded from rostral segments closer to the brain shows higher variability, i.e. variability is site specific. Since the rostral to caudal gradient persists after suppression of brain-spinal cord communication, it may reflect asymmetries within the spinal neural organization.","publisher":"IEEE","publication_name":"Proceedings of the First Joint BMES/EMBS Conference. 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Annual Fall Meeting of the Biomedical Engineering Society (Cat. No.99CH37015)"},"translated_abstract":"In several vertebrates spinal neural networks are capable of generating motor output. In studies on isolated brain-spinal cord preparations of a lower vertebrate, the lamprey, we show that dynamic brain-spinal cord interactions alter the locomotor rhythm that is generated by the distributed spinal pattern generators. Our analyses, which utilize wavelet and novel time-varying covariance methods, indicate that brain-spinal cord interactions have an inhibitory influence on the frequency of the rhythm. However, they contribute to higher variability in motor output. Variability is assessed from the coefficient of variance (CV) and decay in autocovariance. We find that neural activity recorded from rostral segments closer to the brain shows higher variability, i.e. variability is site specific. Since the rostral to caudal gradient persists after suppression of brain-spinal cord communication, it may reflect asymmetries within the spinal neural organization.","internal_url":"https://www.academia.edu/123485759/Site_specific_variability_in_spinal_motor_output","translated_internal_url":"","created_at":"2024-09-02T09:37:45.837-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":38884898,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Site_specific_variability_in_spinal_motor_output","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":38884898,"first_name":"Ranu","middle_initials":null,"last_name":"Jung","page_name":"RanuJung","domain_name":"fiu","created_at":"2015-11-22T06:50:19.728-08:00","display_name":"Ranu Jung","url":"https://fiu.academia.edu/RanuJung"},"attachments":[],"research_interests":[{"id":161,"name":"Neuroscience","url":"https://www.academia.edu/Documents/in/Neuroscience"},{"id":1131,"name":"Biomedical Engineering","url":"https://www.academia.edu/Documents/in/Biomedical_Engineering"},{"id":3886,"name":"Rhythm","url":"https://www.academia.edu/Documents/in/Rhythm"},{"id":7710,"name":"Biology","url":"https://www.academia.edu/Documents/in/Biology"},{"id":9534,"name":"Calcium","url":"https://www.academia.edu/Documents/in/Calcium"},{"id":22272,"name":"Neurophysiology","url":"https://www.academia.edu/Documents/in/Neurophysiology"},{"id":26066,"name":"Neural Network","url":"https://www.academia.edu/Documents/in/Neural_Network"},{"id":55276,"name":"Wavelet Analysis","url":"https://www.academia.edu/Documents/in/Wavelet_Analysis"},{"id":99421,"name":"Spinal Cord","url":"https://www.academia.edu/Documents/in/Spinal_Cord"},{"id":144046,"name":"Frequency","url":"https://www.academia.edu/Documents/in/Frequency"},{"id":383830,"name":"Lamprey","url":"https://www.academia.edu/Documents/in/Lamprey"},{"id":729337,"name":"Covariance analysis","url":"https://www.academia.edu/Documents/in/Covariance_analysis"},{"id":1407459,"name":"DT Signal+generators","url":"https://www.academia.edu/Documents/in/DT_Signal_generators"},{"id":3142462,"name":"Neural nets","url":"https://www.academia.edu/Documents/in/Neural_nets"}],"urls":[{"id":44419625,"url":"http://xplorestaging.ieee.org/ielx5/6513/17397/00802493.pdf?arnumber=802493"}]}, dispatcherData: dispatcherData }); 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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="123485749"><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/123485749/Response_to_Perturbations_of_a_Neural_Network_Model_of_Locomotor_Control_in_the_Lamprey"><img alt="Research paper thumbnail of Response to Perturbations of a Neural Network Model of Locomotor Control in the Lamprey" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/123485749/Response_to_Perturbations_of_a_Neural_Network_Model_of_Locomotor_Control_in_the_Lamprey">Response to Perturbations of a Neural Network Model of Locomotor Control in the Lamprey</a></div><div class="wp-workCard_item"><span>Computational Neuroscience</span><span>, 1998</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">In several vertebrates, stable rhythmic locomotor activity can be obtained from neural networks i...</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 several vertebrates, stable rhythmic locomotor activity can be obtained from neural networks in the spinal cord without external periodic forcing. In an active animal, the spinal central pattern generator (CPG) is dynamically affected by descending input from the brain as well as afferent sensory inputs.1 While certain aspects of spinal CPG mechanisms for locomotor control have been well investigated, 3,8 the interactions of the CPG with the descending supraspinal inputs and sensory inputs are not well understood. Changes in the topology of the system caused by modifying the supraspinal-spinal CPG interactions are likely to influence the response of the system to external perturbations.</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="123485749"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="123485749"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 123485749; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=123485749]").text(description); $(".js-view-count[data-work-id=123485749]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 123485749; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='123485749']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 123485749, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=123485749]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":123485749,"title":"Response to Perturbations of a Neural Network Model of Locomotor Control in the Lamprey","translated_title":"","metadata":{"abstract":"In several vertebrates, stable rhythmic locomotor activity can be obtained from neural networks in the spinal cord without external periodic forcing. 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Changes in the topology of the system caused by modifying the supraspinal-spinal CPG interactions are likely to influence the response of the system to external perturbations.","internal_url":"https://www.academia.edu/123485749/Response_to_Perturbations_of_a_Neural_Network_Model_of_Locomotor_Control_in_the_Lamprey","translated_internal_url":"","created_at":"2024-09-02T09:37:44.131-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":38884898,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Response_to_Perturbations_of_a_Neural_Network_Model_of_Locomotor_Control_in_the_Lamprey","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":38884898,"first_name":"Ranu","middle_initials":null,"last_name":"Jung","page_name":"RanuJung","domain_name":"fiu","created_at":"2015-11-22T06:50:19.728-08:00","display_name":"Ranu Jung","url":"https://fiu.academia.edu/RanuJung"},"attachments":[],"research_interests":[{"id":161,"name":"Neuroscience","url":"https://www.academia.edu/Documents/in/Neuroscience"},{"id":5451,"name":"Computational Neuroscience","url":"https://www.academia.edu/Documents/in/Computational_Neuroscience"},{"id":7710,"name":"Biology","url":"https://www.academia.edu/Documents/in/Biology"},{"id":99421,"name":"Spinal Cord","url":"https://www.academia.edu/Documents/in/Spinal_Cord"},{"id":383830,"name":"Lamprey","url":"https://www.academia.edu/Documents/in/Lamprey"},{"id":3647879,"name":"Springer Ebooks","url":"https://www.academia.edu/Documents/in/Springer_Ebooks"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="123485748"><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/123485748/Simulation_of_the_Spinal_Circuits_Controlling_Swimming_Movements_in_Fish"><img alt="Research paper thumbnail of Simulation of the Spinal Circuits Controlling Swimming Movements in Fish" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/123485748/Simulation_of_the_Spinal_Circuits_Controlling_Swimming_Movements_in_Fish">Simulation of the Spinal Circuits Controlling Swimming Movements in Fish</a></div><div class="wp-workCard_item"><span>Biomechanics and Neural Control of Posture and Movement</span><span>, 2000</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Limb movements in humans and other higher vertebrates are generated through a complex interplay b...</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">Limb movements in humans and other higher vertebrates are generated through a complex interplay between the mechanical apparatus and the central nervous system. Understanding of this neuromechanical system entails more than just a knowledge of its constituent parts. It is necessary to find ways of combining our knowledge of the mechanical system with that of the controlling neuronal circuitry. Both parts by themselves are far from trivial and computer simulation has emerged as an indispensable tool in the task of understanding how they cooperate.</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="123485748"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="123485748"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 123485748; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=123485748]").text(description); $(".js-view-count[data-work-id=123485748]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 123485748; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='123485748']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 123485748, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=123485748]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":123485748,"title":"Simulation of the Spinal Circuits Controlling Swimming Movements in Fish","translated_title":"","metadata":{"abstract":"Limb movements in humans and other higher vertebrates are generated through a complex interplay between the mechanical apparatus and the central nervous system. Understanding of this neuromechanical system entails more than just a knowledge of its constituent parts. It is necessary to find ways of combining our knowledge of the mechanical system with that of the controlling neuronal circuitry. Both parts by themselves are far from trivial and computer simulation has emerged as an indispensable tool in the task of understanding how they cooperate.","publication_date":{"day":null,"month":null,"year":2000,"errors":{}},"publication_name":"Biomechanics and Neural Control of Posture and Movement"},"translated_abstract":"Limb movements in humans and other higher vertebrates are generated through a complex interplay between the mechanical apparatus and the central nervous system. Understanding of this neuromechanical system entails more than just a knowledge of its constituent parts. It is necessary to find ways of combining our knowledge of the mechanical system with that of the controlling neuronal circuitry. Both parts by themselves are far from trivial and computer simulation has emerged as an indispensable tool in the task of understanding how they cooperate.","internal_url":"https://www.academia.edu/123485748/Simulation_of_the_Spinal_Circuits_Controlling_Swimming_Movements_in_Fish","translated_internal_url":"","created_at":"2024-09-02T09:37:43.958-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":38884898,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Simulation_of_the_Spinal_Circuits_Controlling_Swimming_Movements_in_Fish","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":38884898,"first_name":"Ranu","middle_initials":null,"last_name":"Jung","page_name":"RanuJung","domain_name":"fiu","created_at":"2015-11-22T06:50:19.728-08:00","display_name":"Ranu Jung","url":"https://fiu.academia.edu/RanuJung"},"attachments":[],"research_interests":[{"id":161,"name":"Neuroscience","url":"https://www.academia.edu/Documents/in/Neuroscience"},{"id":422,"name":"Computer Science","url":"https://www.academia.edu/Documents/in/Computer_Science"},{"id":472,"name":"Human Computer Interaction","url":"https://www.academia.edu/Documents/in/Human_Computer_Interaction"},{"id":3647879,"name":"Springer Ebooks","url":"https://www.academia.edu/Documents/in/Springer_Ebooks"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="123485747"><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/123485747/Specific_Overground_Walking_Kinematic_Measures_are_Related_to_Degree_of_Spinal_Injury_in_the_Rat"><img alt="Research paper thumbnail of Specific Overground Walking Kinematic Measures are Related to Degree of Spinal Injury in the Rat" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/123485747/Specific_Overground_Walking_Kinematic_Measures_are_Related_to_Degree_of_Spinal_Injury_in_the_Rat">Specific Overground Walking Kinematic Measures are Related to Degree of Spinal Injury in the Rat</a></div><div class="wp-workCard_item"><span>2013 29th Southern Biomedical Engineering Conference</span><span>, 2013</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">ABSTRACT After incomplete spinal cord thoracic injury (iSCI) rodents retain locomotor capability....</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">ABSTRACT After incomplete spinal cord thoracic injury (iSCI) rodents retain locomotor capability. We tested the hypothesis that the degree of retained function would be related to the sparing of spinal tissue. Hindlimb stance width, hindfoot rotation, stride length, and velocity during overground walking and qualitative Basso, Beattie, and Bresnahan (BBB) locomotor scores were obtained in 5 rats with mild-moderate iSCI (T10 injury caused by 10 gm, 2 mm New York University impactor probe dropped from 12.5 mm). The extent of injury was estimated from histological sections stained for myelin by calculating percent volumes of gray matter (%GM) and white matter (%WM) spared for a 9 mm cord section. The white and grey matter volumes were 19.6+/-3.9 (mean+/-SD) and 4.5+/-1.8 cubic mm respectively. This resulted in 47.6+/-6.5 %WM and 10.9+/-4.0 %GM being spared. Kinematic measures of stance width and hindfoot limb rotation showed a significant negative correlation with %WM spared (r=-0.924 and -0.87 8). All other measures did not show significant correlation. BBB showed a significant positive correlation with %WM spared (r=0.93). None of the measures showed significant correlations with %GM spared. The data indicate that impairment of specific features of overground walking is related to the loss of axonal connections after iSCI.</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="123485747"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="123485747"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 123485747; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=123485747]").text(description); $(".js-view-count[data-work-id=123485747]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 123485747; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='123485747']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span><span><script>$(function() { new Works.PaperRankView({ workId: 123485747, container: "", }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-f77ea15d77ce96025a6048a514272ad8becbad23c641fc2b3bd6e24ca6ff1932.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=123485747]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":123485747,"title":"Specific Overground Walking Kinematic Measures are Related to Degree of Spinal Injury in the Rat","translated_title":"","metadata":{"abstract":"ABSTRACT After incomplete spinal cord thoracic injury (iSCI) rodents retain locomotor capability. We tested the hypothesis that the degree of retained function would be related to the sparing of spinal tissue. Hindlimb stance width, hindfoot rotation, stride length, and velocity during overground walking and qualitative Basso, Beattie, and Bresnahan (BBB) locomotor scores were obtained in 5 rats with mild-moderate iSCI (T10 injury caused by 10 gm, 2 mm New York University impactor probe dropped from 12.5 mm). The extent of injury was estimated from histological sections stained for myelin by calculating percent volumes of gray matter (%GM) and white matter (%WM) spared for a 9 mm cord section. The white and grey matter volumes were 19.6+/-3.9 (mean+/-SD) and 4.5+/-1.8 cubic mm respectively. This resulted in 47.6+/-6.5 %WM and 10.9+/-4.0 %GM being spared. Kinematic measures of stance width and hindfoot limb rotation showed a significant negative correlation with %WM spared (r=-0.924 and -0.87 8). All other measures did not show significant correlation. BBB showed a significant positive correlation with %WM spared (r=0.93). None of the measures showed significant correlations with %GM spared. The data indicate that impairment of specific features of overground walking is related to the loss of axonal connections after iSCI.","publisher":"IEEE","publication_date":{"day":null,"month":null,"year":2013,"errors":{}},"publication_name":"2013 29th Southern Biomedical Engineering Conference"},"translated_abstract":"ABSTRACT After incomplete spinal cord thoracic injury (iSCI) rodents retain locomotor capability. We tested the hypothesis that the degree of retained function would be related to the sparing of spinal tissue. Hindlimb stance width, hindfoot rotation, stride length, and velocity during overground walking and qualitative Basso, Beattie, and Bresnahan (BBB) locomotor scores were obtained in 5 rats with mild-moderate iSCI (T10 injury caused by 10 gm, 2 mm New York University impactor probe dropped from 12.5 mm). The extent of injury was estimated from histological sections stained for myelin by calculating percent volumes of gray matter (%GM) and white matter (%WM) spared for a 9 mm cord section. The white and grey matter volumes were 19.6+/-3.9 (mean+/-SD) and 4.5+/-1.8 cubic mm respectively. This resulted in 47.6+/-6.5 %WM and 10.9+/-4.0 %GM being spared. Kinematic measures of stance width and hindfoot limb rotation showed a significant negative correlation with %WM spared (r=-0.924 and -0.87 8). All other measures did not show significant correlation. BBB showed a significant positive correlation with %WM spared (r=0.93). None of the measures showed significant correlations with %GM spared. The data indicate that impairment of specific features of overground walking is related to the loss of axonal connections after iSCI.","internal_url":"https://www.academia.edu/123485747/Specific_Overground_Walking_Kinematic_Measures_are_Related_to_Degree_of_Spinal_Injury_in_the_Rat","translated_internal_url":"","created_at":"2024-09-02T09:37:43.764-07:00","preview_url":null,"current_user_can_edit":null,"current_user_is_owner":null,"owner_id":38884898,"coauthors_can_edit":true,"document_type":"paper","co_author_tags":[],"downloadable_attachments":[],"slug":"Specific_Overground_Walking_Kinematic_Measures_are_Related_to_Degree_of_Spinal_Injury_in_the_Rat","translated_slug":"","page_count":null,"language":"en","content_type":"Work","owner":{"id":38884898,"first_name":"Ranu","middle_initials":null,"last_name":"Jung","page_name":"RanuJung","domain_name":"fiu","created_at":"2015-11-22T06:50:19.728-08:00","display_name":"Ranu Jung","url":"https://fiu.academia.edu/RanuJung"},"attachments":[],"research_interests":[{"id":22824,"name":"Spinal Cord Injury","url":"https://www.academia.edu/Documents/in/Spinal_Cord_Injury"},{"id":26327,"name":"Medicine","url":"https://www.academia.edu/Documents/in/Medicine"},{"id":99421,"name":"Spinal Cord","url":"https://www.academia.edu/Documents/in/Spinal_Cord"},{"id":362036,"name":"White matter","url":"https://www.academia.edu/Documents/in/White_matter"}],"urls":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="123485746"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/123485746/Merging_Technology_with_Biology"><img alt="Research paper thumbnail of Merging Technology with Biology" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/123485746/Merging_Technology_with_Biology">Merging Technology with Biology</a></div><div class="wp-workCard_item"><span>Nerves, Interfaces, and Machines</span><span>, 2011</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="123485746"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span><span id="work-strip-rankings-button-container"></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="123485746"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 123485746; 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