{"id":7352,"date":"2021-04-07T12:12:29","date_gmt":"2021-04-07T10:12:29","guid":{"rendered":"http:\/\/bernstein.mylapo.de\/bernstein-conference-2020\/"},"modified":"2026-03-05T15:34:51","modified_gmt":"2026-03-05T14:34:51","slug":"bernstein-conference-2020","status":"publish","type":"page","link":"https:\/\/bernstein-network.de\/en\/bernstein-conference\/past-future-bernstein-conferences\/bernstein-conference-2020\/","title":{"rendered":"Bernstein Conference 2020"},"content":{"rendered":"<div id='av_section_1'  class='avia-section av-b4ovel-06213fab716bb7bdfbbdc021fdd14c9b main_color avia-section-default avia-no-border-styling  avia-builder-el-0  el_before_av_section  avia-builder-el-first  avia-bg-style-scroll container_wrap fullsize'  ><div class='container av-section-cont-open' ><main  class='template-page content  av-content-full alpha units'><div class='post-entry post-entry-type-page post-entry-7352'><div class='entry-content-wrapper clearfix'>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-9286rx-1689bf803501c4a123fe3a9ff3202e98\">\n.flex_column.av-9286rx-1689bf803501c4a123fe3a9ff3202e98{\nborder-radius:0px 0px 0px 0px;\npadding:0px 0px 0px 0px;\n}\n<\/style>\n<div  class='flex_column av-9286rx-1689bf803501c4a123fe3a9ff3202e98 av_one_full  avia-builder-el-1  avia-builder-el-no-sibling  first flex_column_div av-zero-column-padding  '     ><p>\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-3opgp1-f282727d3db8ecb1ad631fbbbad563cb\">\n#top .av-special-heading.av-3opgp1-f282727d3db8ecb1ad631fbbbad563cb{\npadding-bottom:10px;\n}\nbody .av-special-heading.av-3opgp1-f282727d3db8ecb1ad631fbbbad563cb .av-special-heading-tag .heading-char{\nfont-size:25px;\n}\n.av-special-heading.av-3opgp1-f282727d3db8ecb1ad631fbbbad563cb .av-subheading{\nfont-size:15px;\n}\n<\/style>\n<div  class='av-special-heading av-3opgp1-f282727d3db8ecb1ad631fbbbad563cb av-special-heading-h1 blockquote modern-quote  avia-builder-el-2  el_before_av_image  avia-builder-el-first '><h1 class='av-special-heading-tag '  >Bernstein Conference 2020<\/h1><div class=\"special-heading-border\"><div class=\"special-heading-inner-border\"><\/div><\/div><\/div><br \/>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-gramt-a60d3f487af30a9ffbe5b346bfff9a2c\">\n.avia-image-container.av-gramt-a60d3f487af30a9ffbe5b346bfff9a2c img.avia_image{\nbox-shadow:none;\n}\n.avia-image-container.av-gramt-a60d3f487af30a9ffbe5b346bfff9a2c .av-image-caption-overlay-center{\ncolor:#ffffff;\n}\n<\/style>\n<div  class='avia-image-container av-gramt-a60d3f487af30a9ffbe5b346bfff9a2c av-styling-no-styling avia-align-center  avia-builder-el-3  el_after_av_heading  avia-builder-el-last '  ><div class=\"avia-image-container-inner\"><div class=\"avia-image-overlay-wrap\"><img decoding=\"async\" fetchpriority=\"high\" class='wp-image-10094 avia-img-lazy-loading-not-10094 avia_image ' src=\"https:\/\/bernstein-network.de\/wp-content\/uploads\/2021\/06\/BC20-1-728x1030.jpg\" alt='' title='BC20'  height=\"1030\" width=\"728\" srcset=\"https:\/\/bernstein-network.de\/wp-content\/uploads\/2021\/06\/BC20-1-728x1030.jpg 728w, https:\/\/bernstein-network.de\/wp-content\/uploads\/2021\/06\/BC20-1-212x300.jpg 212w, https:\/\/bernstein-network.de\/wp-content\/uploads\/2021\/06\/BC20-1-768x1086.jpg 768w, https:\/\/bernstein-network.de\/wp-content\/uploads\/2021\/06\/BC20-1-499x705.jpg 499w, https:\/\/bernstein-network.de\/wp-content\/uploads\/2021\/06\/BC20-1.jpg 850w\" sizes=\"(max-width: 728px) 100vw, 728px\" \/><\/div><\/div><\/div><\/p><\/div>\n\n<\/div><\/div><\/main><!-- close content main element --><\/div><\/div>\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-27i0jy-cf09d2d6f81b87422a4cec92229a0caf\">\n.avia-section.av-27i0jy-cf09d2d6f81b87422a4cec92229a0caf{\nbackground-color:#f5f7fa;\nbackground-image:unset;\n}\n<\/style>\n<div id='conferenceiconbox'  class='avia-section av-27i0jy-cf09d2d6f81b87422a4cec92229a0caf main_color avia-section-large avia-no-border-styling  avia-builder-el-4  el_after_av_section  el_before_av_section  avia-bg-style-scroll av-minimum-height av-minimum-height-25 av-height-25  container_wrap fullsize'   data-av_minimum_height_pc='25' data-av_min_height_opt='25'><div class='container av-section-cont-open' ><div class='template-page content  av-content-full alpha units'><div class='post-entry post-entry-type-page post-entry-7352'><div class='entry-content-wrapper clearfix'>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-5dt4eq-c445819d45749bf7f4effb421acb348e\">\n.flex_column.av-5dt4eq-c445819d45749bf7f4effb421acb348e{\nborder-radius:0px 0px 0px 0px;\npadding:0px 0px 0px 0px;\n}\n<\/style>\n<div  class='flex_column av-5dt4eq-c445819d45749bf7f4effb421acb348e av_one_third  avia-builder-el-5  el_before_av_one_third  avia-builder-el-first  first flex_column_div av-zero-column-padding  '     ><p>\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-kn64gdx5-a2d7f3078262234f13ba648fe01a42bd\">\n.iconbox.av-kn64gdx5-a2d7f3078262234f13ba648fe01a42bd .iconbox_icon{\nbackground-color:#f5f7fa;\nborder:1px solid #f5f7fa;\ncolor:#004c93;\n}\n.iconbox.av-kn64gdx5-a2d7f3078262234f13ba648fe01a42bd .iconbox_icon.avia-svg-icon svg:first-child{\nfill:#004c93;\nstroke:#004c93;\n}\n<\/style>\n<article  class='iconbox iconbox_top av-kn64gdx5-a2d7f3078262234f13ba648fe01a42bd av-no-box  avia-builder-el-6  el_before_av_textblock  avia-builder-el-first ' ><div class=\"iconbox_content\"><header class=\"entry-content-header\" aria-label=\"Icon: Location\"><div class='iconbox_icon heading-color avia-iconfont avia-font-entypo-fontello' data-av_icon='\ue842' data-av_iconfont='entypo-fontello'  ><\/div><h3 class='iconbox_content_title ' >Location<\/h3><\/header><div class='iconbox_content_container ' ><\/div><\/div><footer class=\"entry-footer\"><\/footer><\/article><br \/>\n<section  class='av_textblock_section av-lvaqsq9r-a4d53a93037ed5ca6c10bbd7b90dd590 '  ><div class='avia_textblock' ><p style=\"text-align: center;\">Online<\/p>\n<\/div><\/section><\/p><\/div>\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-3hkf1u-a829b70166e31c1577401c6d67bfe860\">\n.flex_column.av-3hkf1u-a829b70166e31c1577401c6d67bfe860{\nborder-radius:0px 0px 0px 0px;\npadding:0px 0px 0px 0px;\n}\n<\/style>\n<div  class='flex_column av-3hkf1u-a829b70166e31c1577401c6d67bfe860 av_one_third  avia-builder-el-8  el_after_av_one_third  el_before_av_one_third  flex_column_div av-zero-column-padding  '     ><p>\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-kn64gdx5-29-6414119ecc681457aa8724147d4efaf4\">\n.iconbox.av-kn64gdx5-29-6414119ecc681457aa8724147d4efaf4 .iconbox_icon{\nbackground-color:#f5f7fa;\nborder:1px solid #f5f7fa;\ncolor:#004c93;\n}\n.iconbox.av-kn64gdx5-29-6414119ecc681457aa8724147d4efaf4 .iconbox_icon.avia-svg-icon svg:first-child{\nfill:#004c93;\nstroke:#004c93;\n}\n<\/style>\n<article  class='iconbox iconbox_top av-kn64gdx5-29-6414119ecc681457aa8724147d4efaf4 av-no-box  avia-builder-el-9  el_before_av_textblock  avia-builder-el-first ' ><div class=\"iconbox_content\"><header class=\"entry-content-header\" aria-label=\"Icon: Date\"><div class='iconbox_icon heading-color avia-iconfont avia-font-entypo-fontello' data-av_icon='\ue85b' data-av_iconfont='entypo-fontello'  ><\/div><h3 class='iconbox_content_title ' >Date<\/h3><\/header><div class='iconbox_content_container ' ><\/div><\/div><footer class=\"entry-footer\"><\/footer><\/article><br \/>\n<section  class='av_textblock_section av-lvaqteo4-be24b514d55759d81a913f6cc8125421 '  ><div class='avia_textblock' ><p style=\"text-align: center;\">Sep 29 \u2013 Oct 1<\/p>\n<\/div><\/section><\/p><\/div>\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-20pc8y-be6060b1a255d21109f14c85d4e7ea2f\">\n.flex_column.av-20pc8y-be6060b1a255d21109f14c85d4e7ea2f{\nborder-radius:0px 0px 0px 0px;\npadding:0px 0px 0px 0px;\n}\n<\/style>\n<div  class='flex_column av-20pc8y-be6060b1a255d21109f14c85d4e7ea2f av_one_third  avia-builder-el-11  el_after_av_one_third  avia-builder-el-last  flex_column_div av-zero-column-padding  '     ><p>\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-kn64gdx5-28-cf4d00fa022318ba8b772c9ad248c954\">\n.iconbox.av-kn64gdx5-28-cf4d00fa022318ba8b772c9ad248c954 .iconbox_icon{\nbackground-color:#f5f7fa;\nborder:1px solid #f5f7fa;\ncolor:#004c93;\n}\n.iconbox.av-kn64gdx5-28-cf4d00fa022318ba8b772c9ad248c954 .iconbox_icon.avia-svg-icon svg:first-child{\nfill:#004c93;\nstroke:#004c93;\n}\n<\/style>\n<article  class='iconbox iconbox_top av-kn64gdx5-28-cf4d00fa022318ba8b772c9ad248c954 av-no-box  avia-builder-el-12  el_before_av_button  avia-builder-el-first ' ><div class=\"iconbox_content\"><header class=\"entry-content-header\" aria-label=\"Icon: Abstracts\"><div class='iconbox_icon heading-color avia-iconfont avia-font-entypo-fontello' data-av_icon='\ue84d' data-av_iconfont='entypo-fontello'  ><\/div><h3 class='iconbox_content_title ' >Abstracts<\/h3><\/header><div class='iconbox_content_container ' ><\/div><\/div><footer class=\"entry-footer\"><\/footer><\/article><br \/>\n<div  class='avia-button-wrap av-lvaqu7cj-2208aa07da1a804cc9b6e14466a09376-wrap avia-button-center  avia-builder-el-13  el_after_av_icon_box  avia-builder-el-last '><a href='https:\/\/abstracts.g-node.org\/conference\/BC20\/abstracts#'  class='avia-button av-lvaqu7cj-2208aa07da1a804cc9b6e14466a09376 av-link-btn avia-icon_select-no avia-size-large avia-position-center avia-color-theme-color'  target=\"_blank\"  rel=\"noopener noreferrer\"  aria-label=\"Repository\"><span class='avia_iconbox_title' >Repository<\/span><\/a><\/div><\/p><\/div>\n\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='av_section_3'  class='avia-section av-6bh0nx-d282bfbd0edf21892c9a9a222289b804 main_color avia-section-default avia-no-border-styling  avia-builder-el-14  el_after_av_section  el_before_av_section  avia-bg-style-scroll container_wrap fullsize'  ><div class='container av-section-cont-open' ><div class='template-page content  av-content-full alpha units'><div class='post-entry post-entry-type-page post-entry-7352'><div class='entry-content-wrapper clearfix'>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-ctlxp-6e17afa75c0f372244aff424e0878c4e\">\n.flex_column.av-ctlxp-6e17afa75c0f372244aff424e0878c4e{\nborder-radius:0px 0px 0px 0px;\npadding:0px 0px 0px 0px;\n}\n<\/style>\n<div  class='flex_column av-ctlxp-6e17afa75c0f372244aff424e0878c4e av_one_full  avia-builder-el-15  el_before_av_one_half  avia-builder-el-first  first flex_column_div av-zero-column-padding  '     ><style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-kpmgyc8o-fcf2cbe30d979ca2e3f679a18d86fde9\">\n#top .av-special-heading.av-kpmgyc8o-fcf2cbe30d979ca2e3f679a18d86fde9{\npadding-bottom:10px;\n}\nbody .av-special-heading.av-kpmgyc8o-fcf2cbe30d979ca2e3f679a18d86fde9 .av-special-heading-tag .heading-char{\nfont-size:25px;\n}\n.av-special-heading.av-kpmgyc8o-fcf2cbe30d979ca2e3f679a18d86fde9 .av-subheading{\nfont-size:15px;\n}\n<\/style>\n<div  class='av-special-heading av-kpmgyc8o-fcf2cbe30d979ca2e3f679a18d86fde9 av-special-heading-h2 blockquote modern-quote  avia-builder-el-16  avia-builder-el-no-sibling '><h2 class='av-special-heading-tag '  >Invited Lectures<\/h2><div class=\"special-heading-border\"><div class=\"special-heading-inner-border\"><\/div><\/div><\/div><\/div>\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-ctlxp-26-d871defa8736a9c0f66c5946df5d0d2d\">\n.flex_column.av-ctlxp-26-d871defa8736a9c0f66c5946df5d0d2d{\nborder-radius:0px 0px 0px 0px;\npadding:0px 0px 0px 0px;\n}\n<\/style>\n<div  class='flex_column av-ctlxp-26-d871defa8736a9c0f66c5946df5d0d2d av_one_half  avia-builder-el-17  el_after_av_one_full  el_before_av_one_half  first flex_column_div av-zero-column-padding  column-top-margin'     ><p><section  class='av_textblock_section av-kn7alib6-146530f79059173e17fd83877639027d '  ><div class='avia_textblock' ><p><strong>William Bialek<\/strong> | Princeton University, USA<br \/>\n<em>Searching for simplicity<\/em><\/p>\n<\/div><\/section><br \/>\n<section  class='av_textblock_section av-kn7alib6-24-d190a3eea519404ea4c5ad166553f474 '  ><div class='avia_textblock' ><p><strong>Michael Brecht<\/strong> | HU Berlin, Germany<br \/>\n<em>Isomorphic mapping and computation in cortical circuits<\/em><\/p>\n<\/div><\/section><br \/>\n<section  class='av_textblock_section av-kn7alib6-23-764bc53e2fea0a3267b1d2317b9fe82e '  ><div class='avia_textblock' ><p><strong>Laura Busse<\/strong> | LMU Munich, Germany<br \/>\n<em>Effects of cortico-thalamic feedback on responses in mouse dLGN<\/em><\/p>\n<\/div><\/section><br \/>\n<section  class='av_textblock_section av-kn7alib6-22-62bd3a5374a5b382cc928140c4c23f57 '  ><div class='avia_textblock' ><p><strong>Megan Carey<\/strong> | Champalimaud Center for the Unknown, Lisbon, Portugal<br \/>\n<em>Understanding the complex behaviors of the &#8216;simple&#8217; cerebellar circuit<\/em><\/p>\n<\/div><\/section><br \/>\n<section  class='av_textblock_section av-kn7alib6-21-0bf40cdc1552e1e79133302643d79cbf '  ><div class='avia_textblock' ><p><strong>Rosa Cossart<\/strong> | Institut de neurobiologie de la m\u00e9diterran\u00e9e, Marseille, France<br \/>\n<em>Development and function of cortical hub neurons<\/em><\/p>\n<\/div><\/section><br \/>\n<section  class='av_textblock_section av-kn7alib6-20-5f34b085114cbd97abdb6a3e5f671573 '  ><div class='avia_textblock' ><p><strong>Ann Hermundstad<\/strong> | Janelia Research Campus, Ashburn, USA<br \/>\n<em>Adaptive control of behavioral variability through the flexible use of an internal representation<\/em><\/p>\n<\/div><\/section><\/p><\/div>\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-ctlxp-25-6679de956ec9a55c85837d14b988e54b\">\n.flex_column.av-ctlxp-25-6679de956ec9a55c85837d14b988e54b{\nborder-radius:0px 0px 0px 0px;\npadding:0px 0px 0px 0px;\n}\n<\/style>\n<div  class='flex_column av-ctlxp-25-6679de956ec9a55c85837d14b988e54b av_one_half  avia-builder-el-24  el_after_av_one_half  avia-builder-el-last  flex_column_div av-zero-column-padding  column-top-margin'     ><p><section  class='av_textblock_section av-kn7alib6-19-852fbcecaa04ac6efa2bff753107eee7 '  ><div class='avia_textblock' ><p><strong>Roozbeh Kiani<\/strong> | New York University, USA<br \/>\n<em>The geometry of the representation of decision variable and stimulus difficulty in the parietal cortex<\/em><\/p>\n<\/div><\/section><br \/>\n<section  class='av_textblock_section av-kn7alib6-17-0860a70794f29208a37495e40ee1fcac '  ><div class='avia_textblock' ><p><strong>Vanessa Ruta<\/strong> | The Rockefeller University, New York City, USA<br \/>\n<em>Themes and variations: the circuitry of mate selection and pursuit in Drosophila<\/em><\/p>\n<\/div><\/section><br \/>\n<section  class='av_textblock_section av-kn7alib6-16-14e2c66e22c0a2ba753ed4239e3de4c8 '  ><div class='avia_textblock' ><p><strong>David Sussillo<\/strong> | Google AI, Mountain View, USA<br \/>\n<em>Universality\u202fand individuality in neural dynamics across large populations of recurrent networks<\/em><\/p>\n<\/div><\/section><br \/>\n<section  class='av_textblock_section av-kn7alib6-15-a415abbcbc2c179168d8fd7dbbcc7973 '  ><div class='avia_textblock' ><p><strong>Srdjan Ostojic<\/strong> | L&#8217;\u00c9cole normale sup\u00e9rieure, Paris, France<br \/>\n<em>Complementary roles of dimensionality and population structure in neural computations<\/em><\/p>\n<\/div><\/section><br \/>\n<section  class='av_textblock_section av-kn7alib6-14-8592f134f698fbfdc260196599f61aad '  ><div class='avia_textblock' ><p><strong>Fred Wolf<\/strong> | MPI for Dynamics and Self-Organization, G\u00f6ttingen, Germany<br \/>\n<em>Evolutionary Transitions in Visual Cortex Design<\/em><\/p>\n<\/div><\/section><\/p><\/div>\n\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='av_section_4'  class='avia-section av-6bh0nx-27-bb1c6c2cb76530a744218508e0f328bb main_color avia-section-default avia-no-border-styling  avia-builder-el-30  el_after_av_section  el_before_av_one_fourth  avia-bg-style-scroll container_wrap fullsize'  ><div class='container av-section-cont-open' ><div class='template-page content  av-content-full alpha units'><div class='post-entry post-entry-type-page post-entry-7352'><div class='entry-content-wrapper clearfix'>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-ctlxp-18-29bf7adf2ca5e94e913bf33999450872\">\n.flex_column.av-ctlxp-18-29bf7adf2ca5e94e913bf33999450872{\nborder-radius:0px 0px 0px 0px;\npadding:0px 0px 0px 0px;\n}\n<\/style>\n<div  class='flex_column av-ctlxp-18-29bf7adf2ca5e94e913bf33999450872 av_one_full  avia-builder-el-31  el_before_av_one_half  avia-builder-el-first  first flex_column_div av-zero-column-padding  '     ><style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-2n6305-a75d451f2c00dad7a318165582d9d812\">\n#top .av-special-heading.av-2n6305-a75d451f2c00dad7a318165582d9d812{\npadding-bottom:10px;\n}\nbody .av-special-heading.av-2n6305-a75d451f2c00dad7a318165582d9d812 .av-special-heading-tag .heading-char{\nfont-size:25px;\n}\n.av-special-heading.av-2n6305-a75d451f2c00dad7a318165582d9d812 .av-subheading{\nfont-size:15px;\n}\n<\/style>\n<div  class='av-special-heading av-2n6305-a75d451f2c00dad7a318165582d9d812 av-special-heading-h2 blockquote modern-quote  avia-builder-el-32  avia-builder-el-no-sibling '><h2 class='av-special-heading-tag '  >Contributed Talks<\/h2><div class=\"special-heading-border\"><div class=\"special-heading-inner-border\"><\/div><\/div><\/div><\/div>\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-ctlxp-11-0c4191d27826caea0eb10fd5ca86eac9\">\n.flex_column.av-ctlxp-11-0c4191d27826caea0eb10fd5ca86eac9{\nborder-radius:0px 0px 0px 0px;\npadding:0px 0px 0px 0px;\n}\n<\/style>\n<div  class='flex_column av-ctlxp-11-0c4191d27826caea0eb10fd5ca86eac9 av_one_half  avia-builder-el-33  el_after_av_one_full  el_before_av_one_half  first flex_column_div av-zero-column-padding  column-top-margin'     ><p><section  class='av_textblock_section av-kn7alib6-13-bbf63f6202649b4ea5c0df04b31e1f75 '  ><div class='avia_textblock' ><p><strong>Kristopher T. Jensen<\/strong> | University of Cambridge, UK<br \/>\n<em>Manifold GPLVMs for discovering non-Euclidean latent structure in neural data<\/em><\/p>\n<\/div><\/section><br \/>\n<section  class='av_textblock_section av-kn7alib6-9-c67d25e0887245d0383e57b25153960b '  ><div class='avia_textblock' ><p><strong>Dmitry Kobak<\/strong> | University of T\u00fcbingen, Germany<br \/>\n<em>Phenotypic variation within and across transcriptomic cell types in mouse motor cortex<\/em><\/p>\n<\/div><\/section><br \/>\n<section  class='av_textblock_section av-kn7alib6-8-63d292f96adf50f4493cadd3169fe62e '  ><div class='avia_textblock' ><p><strong>Felipe Yaroslav Kalle Kossio<\/strong> | University of Bonn, Germany<br \/>\n<em>Drifting assemblies for persistent memory<\/em><\/p>\n<\/div><\/section><br \/>\n<section  class='av_textblock_section av-kn7alib6-7-68a290e6f11702f24080a6e83717ab68 '  ><div class='avia_textblock' ><p><strong>Subhadra Mokashe<\/strong> | Brandeis University &amp; Duke University, USA<br \/>\n<em>Learning sequences of correlated patterns in recurrent networks<\/em><\/p>\n<\/div><\/section><\/p><\/div>\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-ctlxp-10-5f41200c2cb3c06f26a5db46e3dd3b72\">\n.flex_column.av-ctlxp-10-5f41200c2cb3c06f26a5db46e3dd3b72{\nborder-radius:0px 0px 0px 0px;\npadding:0px 0px 0px 0px;\n}\n<\/style>\n<div  class='flex_column av-ctlxp-10-5f41200c2cb3c06f26a5db46e3dd3b72 av_one_half  avia-builder-el-38  el_after_av_one_half  avia-builder-el-last  flex_column_div av-zero-column-padding  column-top-margin'     ><p><section  class='av_textblock_section av-kn7alib6-6-c09e7e6e667731a936f1831f81eed479 '  ><div class='avia_textblock' ><p><strong>Eleonora Russo<\/strong> | Central Institute of Mental Health, Mannheim, Germany<br \/>\n<em>Coordinated prefrontal state transition leads extinction of reward-seeking behaviors<\/em><\/p>\n<\/div><\/section><br \/>\n<section  class='av_textblock_section av-kn7alib6-4-6ae4d35008f36814712d24d46fd4c2de '  ><div class='avia_textblock' ><p><strong>Sarah Starosta<\/strong> | Washington University, St. Louis, USA<br \/>\n<em>Dopamine and the algorithmic basis of foraging decisions<\/em><\/p>\n<\/div><\/section><br \/>\n<section  class='av_textblock_section av-kn7alib6-3-852ec7059895438ac83de8f0a08efdad '  ><div class='avia_textblock' ><p><strong>Bal\u00e1zs B. Ujfalussy<\/strong> | Institute of Experimental Medicine, Budapest, Hungary<br \/>\n<em>Sampling-like representations of prospective locations during hippocampal theta sequences<\/em><\/p>\n<\/div><\/section><br \/>\n<section  class='av_textblock_section av-kn7alib6-2-aa3d20edb49093f60a73a0447d77c147 '  ><div class='avia_textblock' ><p><strong>Oleg Vinogradov<\/strong> | University of T\u00fcbingen, Germany<br \/>\n<em>Neuronal cultures self-organize towards excitation\/inhibition balance<\/em><\/p>\n<\/div><\/section><\/p><\/div>\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='after_section_4'  class='main_color av_default_container_wrap container_wrap fullsize'  ><div class='container av-section-cont-open' ><div class='template-page content  av-content-full alpha units'><div class='post-entry post-entry-type-page post-entry-7352'><div class='entry-content-wrapper clearfix'>\n<div class='flex_column_table av-kn64mb3z-879f9855e78c83554b8009bfa639258d sc-av_one_fourth av-equal-height-column-flextable'>\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-kn64mb3z-879f9855e78c83554b8009bfa639258d\">\n.flex_column.av-kn64mb3z-879f9855e78c83554b8009bfa639258d{\nborder-radius:0px 0px 0px 0px;\npadding:34px 20px 14px 25px;\nbackground-color:#f5f7fa;\n}\n<\/style>\n<div  class='flex_column av-kn64mb3z-879f9855e78c83554b8009bfa639258d av_one_fourth  avia-builder-el-43  el_after_av_section  el_before_av_one_half  avia-builder-el-first  first flex_column_table_cell av-equal-height-column av-align-middle avia-link-column av-column-link  '    data-link-column-url=\"https:\/\/vimeo.com\/channels\/bernsteinconference\"  data-link-column-target=\"_blank\"   ><a class=\"av-screen-reader-only\" href=https:\/\/vimeo.com\/channels\/bernsteinconference  target=\"_blank\" >Follow a manual added link<\/a><style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-kzfl0veh-c9e3b8ed4519fd68bc9aa0a7188b1670\">\n#top .av-special-heading.av-kzfl0veh-c9e3b8ed4519fd68bc9aa0a7188b1670{\npadding-bottom:0;\n}\nbody .av-special-heading.av-kzfl0veh-c9e3b8ed4519fd68bc9aa0a7188b1670 .av-special-heading-tag .heading-char{\nfont-size:25px;\n}\n.av-special-heading.av-kzfl0veh-c9e3b8ed4519fd68bc9aa0a7188b1670 .av-subheading{\nfont-size:15px;\n}\n<\/style>\n<div  class='av-special-heading av-kzfl0veh-c9e3b8ed4519fd68bc9aa0a7188b1670 av-special-heading-h4 blockquote modern-quote  avia-builder-el-44  avia-builder-el-no-sibling '><h4 class='av-special-heading-tag '  >Talk Collection 2020<\/h4><div class='av-subheading av-subheading_below'><p>Here you&#8217;ll find invited and contributed talks from the Bernstein Conference 2020 online.<\/p>\n<\/div><div class=\"special-heading-border\"><div class=\"special-heading-inner-border\"><\/div><\/div><\/div><\/div>\n<div class='av-flex-placeholder'><\/div>\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-4d7e4y-8a1f40fb150122fddb108d264cb800b1\">\n.flex_column.av-4d7e4y-8a1f40fb150122fddb108d264cb800b1{\nborder-radius:0px 0px 0px 0px;\npadding:0px 0px 0px 0px;\n}\n<\/style>\n<div  class='flex_column av-4d7e4y-8a1f40fb150122fddb108d264cb800b1 av_one_half  avia-builder-el-45  el_after_av_one_fourth  el_before_av_section  avia-builder-el-last  flex_column_table_cell av-equal-height-column av-align-middle av-zero-column-padding  '     ><div  class='avia-video av-ktsdrou5-dc41154960b855149c6fc62e980bc9ac avia-video-16-9 av-no-preview-image avia-video-load-always av-lazyload-immediate av-lazyload-video-embed'  data-original_url='https:\/\/vimeo.com\/464125880'><script type='text\/html' class='av-video-tmpl'><div class='avia-iframe-wrap'><iframe loading=\"lazy\" src=\"https:\/\/player.vimeo.com\/video\/464125880?h=fb763a272a&amp;dnt=1&amp;app_id=122963&autoplay=0&loop=0&controls=1&muted=0\" width=\"1500\" height=\"844\" frameborder=\"0\" allow=\"autoplay; fullscreen; picture-in-picture\" allowfullscreen><\/iframe><\/div><\/script><div class='av-click-to-play-overlay'><div class=\"avia_playpause_icon\"><\/div><\/div><\/div><\/div><\/div><!--close column table wrapper. Autoclose: 1 -->\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='av_section_5'  class='avia-section av-6bh0nx-12-1a8e90d65b42e2016ee1a6928f20f047 main_color avia-section-default avia-no-border-styling  avia-builder-el-47  el_after_av_one_half  el_before_av_submenu  avia-bg-style-scroll container_wrap fullsize'  ><div class='container av-section-cont-open' ><div class='template-page content  av-content-full alpha units'><div class='post-entry post-entry-type-page post-entry-7352'><div class='entry-content-wrapper clearfix'>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-ctlxp-5-d2e0eb6695bd963e2eea0c05fd98bfd8\">\n.flex_column.av-ctlxp-5-d2e0eb6695bd963e2eea0c05fd98bfd8{\nborder-radius:0px 0px 0px 0px;\npadding:0px 0px 0px 0px;\n}\n<\/style>\n<div  class='flex_column av-ctlxp-5-d2e0eb6695bd963e2eea0c05fd98bfd8 av_one_full  avia-builder-el-48  el_before_av_one_full  avia-builder-el-first  first flex_column_div av-zero-column-padding  '     ><style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-2hugut-ae6bb84fc17381509ee2e5125647e625\">\n#top .av-special-heading.av-2hugut-ae6bb84fc17381509ee2e5125647e625{\npadding-bottom:10px;\n}\nbody .av-special-heading.av-2hugut-ae6bb84fc17381509ee2e5125647e625 .av-special-heading-tag .heading-char{\nfont-size:25px;\n}\n.av-special-heading.av-2hugut-ae6bb84fc17381509ee2e5125647e625 .av-subheading{\nfont-size:15px;\n}\n<\/style>\n<div  class='av-special-heading av-2hugut-ae6bb84fc17381509ee2e5125647e625 av-special-heading-h2 blockquote modern-quote  avia-builder-el-49  avia-builder-el-no-sibling '><h2 class='av-special-heading-tag '  >Satellite Workshops<\/h2><div class=\"special-heading-border\"><div class=\"special-heading-inner-border\"><\/div><\/div><\/div><\/div>\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-ctlxp-1-a11808ce1732335eb7afde3d09c5d763\">\n.flex_column.av-ctlxp-1-a11808ce1732335eb7afde3d09c5d763{\nborder-radius:0px 0px 0px 0px;\npadding:0px 0px 0px 0px;\n}\n<\/style>\n<div  class='flex_column av-ctlxp-1-a11808ce1732335eb7afde3d09c5d763 av_one_full  avia-builder-el-50  el_after_av_one_full  avia-builder-el-last  first flex_column_div av-zero-column-padding  column-top-margin'     ><style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-kd4m4nu0-627f9b87a879b2f4ce68ddf2fcc9123d\">\n#top .togglecontainer.av-kd4m4nu0-627f9b87a879b2f4ce68ddf2fcc9123d p.toggler{\nborder-color:#ebebeb;\n}\n#top .togglecontainer.av-kd4m4nu0-627f9b87a879b2f4ce68ddf2fcc9123d .toggle_wrap .toggle_content{\nborder-color:#ebebeb;\n}\n<\/style>\n<div  class='togglecontainer av-kd4m4nu0-627f9b87a879b2f4ce68ddf2fcc9123d av-elegant-toggle  avia-builder-el-51  avia-builder-el-no-sibling ' >\n<section class='av_toggle_section av-1sootx-705be91b29663dba3d94604dc3b1417f' ><div role=\"tablist\" class=\"single_toggle\" data-tags=\"{All} \"  ><p id='toggle-crossing-scales-understanding-collective-neural-activity' data-fake-id='#crossing-scales-understanding-collective-neural-activity' class='toggler  av-title-above av-inherit-border-color'  role='tab' tabindex='0' aria-controls='crossing-scales-understanding-collective-neural-activity' data-slide-speed=\"200\" data-title=\"Crossing scales: understanding collective neural activity&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Anna Levina, Roxana Zeraati&lt;\/span&gt;\" data-title-open=\"\" data-aria_collapsed=\"Click to expand: Crossing scales: understanding collective neural activity&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Anna Levina, Roxana Zeraati&lt;\/span&gt;\" data-aria_expanded=\"Click to collapse: Crossing scales: understanding collective neural activity&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Anna Levina, Roxana Zeraati&lt;\/span&gt;\">Crossing scales: understanding collective neural activity<br \/>\n<span class=\"workshop-subtitle\"><strong>Organizers:<\/strong> Anna Levina, Roxana Zeraati<\/span><span class=\"toggle_icon\"><span class=\"vert_icon\"><\/span><span class=\"hor_icon\"><\/span><\/span><\/p><div id='crossing-scales-understanding-collective-neural-activity' aria-labelledby='toggle-crossing-scales-understanding-collective-neural-activity' role='region' class='toggle_wrap  av-title-above'  ><div class='toggle_content invers-color av-inherit-border-color' ><p><strong>Description:<\/strong><\/p>\n<p class=\"p1\">Growing evidence suggests that to fully understand how the brain operates, we need to study neural activity\u00a0on the population level. The collective neural activity can manifest across different scales: from localncircuits within a single brain area to activity distributed across the whole brain. Recent advances innexperimental techniques have enabled us to record simultaneously from a large group of neurons (e.g., neuropixel recordings or calcium imaging) or run multimodal recordings across different scales (e.g. NeuralnEvent Triggered fMRI recordings). Thus, we have an unprecedented amount of data to develop and verifyntheories explaining and quantifying collective neuronal activity. The current workshop aims at reviewing what\u00a0we have learned so far and building bridges between different approaches.<\/p>\n<p class=\"p1\">There are many different ways to describe the collective behavior of neuronal populations and analyze the high-dimensional data. One option is to use the statistical physics point of view and study the features ofnsnapshots of the activity. This approach can uncover complex scaling behavior and lead to more universal theories of neuronal dynamics. From a different point of view, we can use large-scale computational models and the dynamical systems approach to describe circuits or even the whole-brain dynamics. Validation of such models in the data requires advanced methods to characterize activity in large-scale neuronal recordings. To this end, novel dimensionality reduction techniques (e.g., finding underlying manifolds of high-dimensional\u00a0neural activity) can help us to understand the population code better. In this workshop, we aim at bringing together the different views on how the collective neural activity can be characterized and modeled. We invite speakers using different approaches and experimental paradigms to discuss their experimental findings, models, and data analysis tools, and uncover which type of questions they can answer.<\/p>\n<p><strong>Speakers:<\/strong><\/p>\n<ul>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" aria-setsize=\"-1\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">Gustavo Deco<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" aria-setsize=\"-1\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"auto\">Demian Battaglia<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" aria-setsize=\"-1\" data-aria-posinset=\"3\" data-aria-level=\"1\"><span data-contrast=\"auto\">Viola Priesemann<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" aria-setsize=\"-1\" data-aria-posinset=\"4\" data-aria-level=\"1\"><span data-contrast=\"auto\">Mauro Copelli<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" aria-setsize=\"-1\" data-aria-posinset=\"5\" data-aria-level=\"1\"><span data-contrast=\"auto\">Ga\u0161per\u202fTka\u010dik<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" aria-setsize=\"-1\" data-aria-posinset=\"6\" data-aria-level=\"1\"><span data-contrast=\"auto\">Leenoy Meshulam<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" aria-setsize=\"-1\" data-aria-posinset=\"7\" data-aria-level=\"1\"><span data-contrast=\"auto\">Jakob Macke<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" aria-setsize=\"-1\" data-aria-posinset=\"8\" data-aria-level=\"1\"><span data-contrast=\"auto\">Francesca Mastrogiuseppe<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" aria-setsize=\"-1\" data-aria-posinset=\"9\" data-aria-level=\"1\"><span data-contrast=\"auto\">Stephanie Palmer<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" aria-setsize=\"-1\" data-aria-posinset=\"10\" data-aria-level=\"1\"><span data-contrast=\"auto\">Sara Solla<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" aria-setsize=\"-1\" data-aria-posinset=\"11\" data-aria-level=\"1\"><span data-contrast=\"auto\">Barbara Feulner<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"2\" aria-setsize=\"-1\" data-aria-posinset=\"12\" data-aria-level=\"1\"><span data-contrast=\"auto\">Gal Mishne<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<\/ul>\n<\/div><\/div><\/div><\/section>\n<section class='av_toggle_section av-f90lqd-2a8cffcf3b43b744a5a8b01e69185e33' ><div role=\"tablist\" class=\"single_toggle\" data-tags=\"{All} \"  ><p id='toggle-dynamic-probabilistic-inference-in-the-brain' data-fake-id='#dynamic-probabilistic-inference-in-the-brain' class='toggler  av-title-above av-inherit-border-color'  role='tab' tabindex='0' aria-controls='dynamic-probabilistic-inference-in-the-brain' data-slide-speed=\"200\" data-title=\"Dynamic probabilistic inference in the brain&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Anna Kutschireiter, Jan Drugowitsch&lt;\/span&gt;\" data-title-open=\"\" data-aria_collapsed=\"Click to expand: Dynamic probabilistic inference in the brain&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Anna Kutschireiter, Jan Drugowitsch&lt;\/span&gt;\" data-aria_expanded=\"Click to collapse: Dynamic probabilistic inference in the brain&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Anna Kutschireiter, Jan Drugowitsch&lt;\/span&gt;\">Dynamic probabilistic inference in the brain<br \/>\n<span class=\"workshop-subtitle\"><strong>Organizers:<\/strong> Anna Kutschireiter, Jan Drugowitsch<\/span><span class=\"toggle_icon\"><span class=\"vert_icon\"><\/span><span class=\"hor_icon\"><\/span><\/span><\/p><div id='dynamic-probabilistic-inference-in-the-brain' aria-labelledby='toggle-dynamic-probabilistic-inference-in-the-brain' role='region' class='toggle_wrap  av-title-above'  ><div class='toggle_content invers-color av-inherit-border-color' ><p><strong>Description:<\/strong><\/p>\n<p class=\"p1\">Every day, our brain needs to make sense of the rich, dynamic stream of sensory inputs and combine them with prior knowledge about its environment. Ample behavioral evidence suggests that the brain\u2019s processing of information conforms to the rules of probabilistic inference. Most of this evidence came from static trial-by-trial experiments that do not reflect the dynamic nature of our environment, leading to simplified and rather restricted models of how our brains perform such inference. The aim of this workshop is to look beyond such simplified, static models of inference and ask how the brain could perform the continuous-time dynamic inference required to operate in natural environments. Such inference needs to span the range of synapses learning environmental regularities, over the efficient and effective processing of dynamic and continuously changing sensory inputs, to applying continuous-time control in order to act upon the world\u2019s inferred state. Recent experiments have started moving towards more natural behaviors and, as such, provide the ideal benchmark to test the emerging models against.<\/p>\n<p class=\"p1\">We will bring together researchers working on models of dynamical inference in the brain, ranging from inference and learning on the level of synapses, single neurons, and neuronal networks to predictions of optimal strategies and behavior, as well as on experiments to test these predictions. More precisely, the goal is to provide a forum to discuss recent developments on all these levels and consider the implications of adding a dynamic component to the usually static inference. By spanning a wide range of research areas, the workshop should appeal to the broad audience attending the main conference.<\/p>\n<p><strong>Speakers:<\/strong><\/p>\n<ul>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"3\" aria-setsize=\"-1\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">Cristina Savin<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"3\" aria-setsize=\"-1\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"auto\">Eszter V\u00e9rtes<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"3\" aria-setsize=\"-1\" data-aria-posinset=\"3\" data-aria-level=\"1\"><span data-contrast=\"auto\">M\u00e1t\u00e9 Lengyel<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"3\" aria-setsize=\"-1\" data-aria-posinset=\"4\" data-aria-level=\"1\"><span data-contrast=\"auto\">Robert Legenstein<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"3\" aria-setsize=\"-1\" data-aria-posinset=\"5\" data-aria-level=\"1\"><span data-contrast=\"auto\">Jannes Jegminat<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"3\" aria-setsize=\"-1\" data-aria-posinset=\"6\" data-aria-level=\"1\"><span data-contrast=\"auto\">Joseph Makin<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"3\" aria-setsize=\"-1\" data-aria-posinset=\"7\" data-aria-level=\"1\"><span data-contrast=\"auto\">Dimitrije Markovi\u0107<\/span><strong><span data-contrast=\"auto\">\u00a0<\/span><\/strong><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"3\" aria-setsize=\"-1\" data-aria-posinset=\"8\" data-aria-level=\"1\"><span data-contrast=\"auto\">Zachary Kilpatrick<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"3\" aria-setsize=\"-1\" data-aria-posinset=\"9\" data-aria-level=\"1\"><span data-contrast=\"auto\">Anja Zai<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"3\" aria-setsize=\"-1\" data-aria-posinset=\"10\" data-aria-level=\"1\"><span data-contrast=\"auto\">Ralf Haefner<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"3\" aria-setsize=\"-1\" data-aria-posinset=\"11\" data-aria-level=\"1\"><span data-contrast=\"auto\">Ann Hermundstad<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<\/ul>\n<\/div><\/div><\/div><\/section>\n<section class='av_toggle_section av-djtggl-dc298e8816806495923b8c2482a71cef' ><div role=\"tablist\" class=\"single_toggle\" data-tags=\"{All} \"  ><p id='toggle-frontiers-in-the-evolution-of-neuronal-computation' data-fake-id='#frontiers-in-the-evolution-of-neuronal-computation' class='toggler  av-title-above av-inherit-border-color'  role='tab' tabindex='0' aria-controls='frontiers-in-the-evolution-of-neuronal-computation' data-slide-speed=\"200\" data-title=\"Frontiers in the Evolution of Neuronal Computation&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Fred Wolf&lt;\/span&gt;\" data-title-open=\"\" data-aria_collapsed=\"Click to expand: Frontiers in the Evolution of Neuronal Computation&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Fred Wolf&lt;\/span&gt;\" data-aria_expanded=\"Click to collapse: Frontiers in the Evolution of Neuronal Computation&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Fred Wolf&lt;\/span&gt;\">Frontiers in the Evolution of Neuronal Computation<br \/>\n<span class=\"workshop-subtitle\"><strong>Organizers:<\/strong> Fred Wolf<\/span><span class=\"toggle_icon\"><span class=\"vert_icon\"><\/span><span class=\"hor_icon\"><\/span><\/span><\/p><div id='frontiers-in-the-evolution-of-neuronal-computation' aria-labelledby='toggle-frontiers-in-the-evolution-of-neuronal-computation' role='region' class='toggle_wrap  av-title-above'  ><div class='toggle_content invers-color av-inherit-border-color' ><p><strong>Description:<\/strong><\/p>\n<p class=\"p1\">Nervous systems are not designed by smart engineers but are products of the long and winding, branching roads of animal evolution stretching back to the emergence of the first animals about 800 million years ago. In this process, neural cells and circuits have been tuned molecularly for improved performance, optimized for energy efficiency, and restructured by disruptive innovations in neural information processing. A long-standing objective of computational neuroscience is to identify, model, and explain the information processing principles underlying the evolutionary optimization of neural systems design. Recent experimental progress has opened new and stringent perspectives on the evolution of central nervous system structure, information processing, and development. The maturation of powerful computational optimization theories for neuronal circuits has undergone a parallel revolutionary change. Together, these developments are setting the stage to take a novel approach and directly address information processing challenges, the mechanisms of nervous system modification, and the resulting remodeling of neuronal information processing from an evolutionary perspective.<\/p>\n<p class=\"p1\">The workshop \u201cFrontiers in the Evolution of Neuronal Computation\u201d will present, in three topical sessions, selected lines of research at the frontier of computational neuroscience and evolutionary biology. Session \u201cEmergence and Design of the First Nervous Systems\u201d will focus on recent work opening novel perspectives on the original evolutionary invention of nerve cells, synapses, and the first neural circuits controlling animal behavior. Session \u201cInvariance, Universality and Optimization in the Evolution of Sensory Systems\u201d will present research that aims to identify evolutionary invariants of sensory information processing and the mechanisms underlying its developmental and evolutionary optimization. Finally, the session \u201cPrinciples of Cortical Circuit Evolution\u201d will focus on work that strives to decipher the principles and processes underlying fundamental transformations of the circuit structure of the cerebral cortical learning machine in the evolution of modern mammals. Overall, the research presented at the workshop is chosen to foster discussion, refining, and advancing research questions on frontier topics in evolutionary neuroscience and to highlight the novel opportunities and challenges for computational neuroscience they offer. Each session will conclude with a group discussion to mark common ground and to identify overarching research goals and unsolved problems from a computational and theoretical perspective.<\/p>\n<p><strong>Speakers:<\/strong><\/p>\n<ul>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"4\" aria-setsize=\"-1\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">Pawel Burkhard<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"4\" aria-setsize=\"-1\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"auto\">Raoul-Martin Memmesheimer<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"4\" aria-setsize=\"-1\" data-aria-posinset=\"3\" data-aria-level=\"1\"><span data-contrast=\"auto\">Veronica Eggers | Silke Sachse<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"4\" aria-setsize=\"-1\" data-aria-posinset=\"4\" data-aria-level=\"1\"><span data-contrast=\"auto\">Marion Silies<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"4\" aria-setsize=\"-1\" data-aria-posinset=\"5\" data-aria-level=\"1\"><span data-contrast=\"auto\">Jan Clemens\u00a0<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"4\" aria-setsize=\"-1\" data-aria-posinset=\"6\" data-aria-level=\"1\"><span data-contrast=\"auto\">Mathias F. Wernet | Katja Nowick<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"4\" aria-setsize=\"-1\" data-aria-posinset=\"7\" data-aria-level=\"1\"><span data-contrast=\"auto\">Stephanie E. Palmer<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"4\" aria-setsize=\"-1\" data-aria-posinset=\"8\" data-aria-level=\"1\"><span data-contrast=\"auto\">Daniel Huber<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"4\" aria-setsize=\"-1\" data-aria-posinset=\"9\" data-aria-level=\"1\"><span data-contrast=\"auto\">Julijana Gjorgjieva<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"4\" aria-setsize=\"-1\" data-aria-posinset=\"10\" data-aria-level=\"1\"><span data-contrast=\"auto\">Viola Priesemann | Michael Wibral<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"4\" aria-setsize=\"-1\" data-aria-posinset=\"11\" data-aria-level=\"1\"><span data-contrast=\"auto\">Manuel Schottdorf<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<\/ul>\n<\/div><\/div><\/div><\/section>\n<section class='av_toggle_section av-cmmr79-69f198b2d79da29bb7aa22d42552c543' ><div role=\"tablist\" class=\"single_toggle\" data-tags=\"{All} \"  ><p id='toggle-inferring-and-testing-optimality-in-perception-and-neurons' data-fake-id='#inferring-and-testing-optimality-in-perception-and-neurons' class='toggler  av-title-above av-inherit-border-color'  role='tab' tabindex='0' aria-controls='inferring-and-testing-optimality-in-perception-and-neurons' data-slide-speed=\"200\" data-title=\"Inferring and testing optimality in perception and neurons&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Matthew Chalk, Wiktor M\u0142ynarski&lt;\/span&gt;\" data-title-open=\"\" data-aria_collapsed=\"Click to expand: Inferring and testing optimality in perception and neurons&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Matthew Chalk, Wiktor M\u0142ynarski&lt;\/span&gt;\" data-aria_expanded=\"Click to collapse: Inferring and testing optimality in perception and neurons&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Matthew Chalk, Wiktor M\u0142ynarski&lt;\/span&gt;\">Inferring and testing optimality in perception and neurons<br \/>\n<span class=\"workshop-subtitle\"><strong>Organizers:<\/strong> Matthew Chalk, Wiktor M\u0142ynarski<\/span><span class=\"toggle_icon\"><span class=\"vert_icon\"><\/span><span class=\"hor_icon\"><\/span><\/span><\/p><div id='inferring-and-testing-optimality-in-perception-and-neurons' aria-labelledby='toggle-inferring-and-testing-optimality-in-perception-and-neurons' role='region' class='toggle_wrap  av-title-above'  ><div class='toggle_content invers-color av-inherit-border-color' ><p><strong>Description:<\/strong><\/p>\n<p class=\"p1\">Many influential theories of neural computation are based on the idea that the brain has evolved to perform certain computations near-optimally. Prominent examples of theoretical frameworks grounded in the notion of optimality include efficient encoding, decision making, and reinforcement learning. Despite their conceptual importance, these theories are often difficult to test and\/or falsify on real neural data. This is primarily because currently we lack statistical tools to rigorously define and quantify the degree of optimality of a given neural system. Further, it is unclear how such optimality theories can be applied to neural data when we don\u2019t know a priori what computation is being performed by the system in question.<\/p>\n<p class=\"p1\">Recently, a number of approaches aimed at rigorously testing and inferring optimal computations in neural systems and behaviour have emerged. In this workshop, we will bring together neural theorists and cognitive scientists to discuss these recent developments. We will examine the overlap and similarities between seemingly disparate domains by asking when and how it could be possible to infer signatures of optimality in animals and neurons. We will also ask how approaches based on notions of optimality could be complemented by traditional, bottom-up statistical models of neural coding and behaviour.<\/p>\n<p><strong>Speakers:<\/strong><\/p>\n<ul>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"5\" aria-setsize=\"-1\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">Gerg\u0151 Orb\u00e1n<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"5\" aria-setsize=\"-1\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"auto\">Constantin Rothkopf<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"5\" aria-setsize=\"-1\" data-aria-posinset=\"3\" data-aria-level=\"1\"><span data-contrast=\"auto\">Ann Hermundstad<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"5\" aria-setsize=\"-1\" data-aria-posinset=\"4\" data-aria-level=\"1\"><span data-contrast=\"auto\">Zhengwei Wu<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"5\" aria-setsize=\"-1\" data-aria-posinset=\"5\" data-aria-level=\"1\"><span data-contrast=\"auto\">Scott Linderman<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"5\" aria-setsize=\"-1\" data-aria-posinset=\"6\" data-aria-level=\"1\"><span data-contrast=\"auto\">Maneesh Sahani<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"5\" aria-setsize=\"-1\" data-aria-posinset=\"7\" data-aria-level=\"1\"><span data-contrast=\"auto\">Sean Bittner<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"5\" aria-setsize=\"-1\" data-aria-posinset=\"8\" data-aria-level=\"1\"><span data-contrast=\"auto\">Wiktor M\u0142ynarski<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<\/ul>\n<\/div><\/div><\/div><\/section>\n<section class='av_toggle_section av-152f9h-1e05f5db1618d74cbb3e0db308ca65d2' ><div role=\"tablist\" class=\"single_toggle\" data-tags=\"{All} \"  ><p id='toggle-leveraging-open-datasets-from-the-allen-brain-observatory-for-computational-neuroscience' data-fake-id='#leveraging-open-datasets-from-the-allen-brain-observatory-for-computational-neuroscience' class='toggler  av-title-above av-inherit-border-color'  role='tab' tabindex='0' aria-controls='leveraging-open-datasets-from-the-allen-brain-observatory-for-computational-neuroscience' data-slide-speed=\"200\" data-title=\"Leveraging Open Datasets from the Allen Brain Observatory for Computational Neuroscience&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Saskia de Vries, Josh Siegle&lt;\/span&gt;\" data-title-open=\"\" data-aria_collapsed=\"Click to expand: Leveraging Open Datasets from the Allen Brain Observatory for Computational Neuroscience&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Saskia de Vries, Josh Siegle&lt;\/span&gt;\" data-aria_expanded=\"Click to collapse: Leveraging Open Datasets from the Allen Brain Observatory for Computational Neuroscience&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Saskia de Vries, Josh Siegle&lt;\/span&gt;\">Leveraging Open Datasets from the Allen Brain Observatory for Computational Neuroscience<br \/>\n<span class=\"workshop-subtitle\"><strong>Organizers:<\/strong> Saskia de Vries, Josh Siegle<\/span><span class=\"toggle_icon\"><span class=\"vert_icon\"><\/span><span class=\"hor_icon\"><\/span><\/span><\/p><div id='leveraging-open-datasets-from-the-allen-brain-observatory-for-computational-neuroscience' aria-labelledby='toggle-leveraging-open-datasets-from-the-allen-brain-observatory-for-computational-neuroscience' role='region' class='toggle_wrap  av-title-above'  ><div class='toggle_content invers-color av-inherit-border-color' ><p><strong>Description:<\/strong><\/p>\n<p class=\"p1\">This program will teach participants how to take advantage of Allen Brain Observatory data, via hands-on tutorials and a showcase of scientific talks. Our publicly available datasets include both 2-photon calcium imaging and dense electrophysiological recordings from the visual cortex of awake mice. The data has been collected under highly standardized conditions using rich visual stimulus sets to facilitate comparisons across experiments and recording modalities. These readily accessible, well-documented datasets can be used by the community to test new analysis methods, evaluate models of neural function, or generate ideas for targeted studies.<\/p>\n<p class=\"p1\">We will begin by introducing participants to the scientific motivation and technical details of the Allen Brain Observatory experiments. We will then demonstrate how to use the AllenSDK, an open-source Python library that provides a convenient interface for data retrieval and analysis. A hands-on tutorial will prepare participants to dive into their own analysis of these neural recordings. In the second half of the workshop, invited speakers from both inside and outside the institute will provide examples of work that has already been carried out with Allen Brain Observatory data.<\/p>\n<p><strong>Speakers:<\/strong><\/p>\n<ul>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"6\" aria-setsize=\"-1\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">Saskia de Vries<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"6\" aria-setsize=\"-1\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"auto\">Josh Siegle<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"6\" aria-setsize=\"-1\" data-aria-posinset=\"3\" data-aria-level=\"1\"><span data-contrast=\"auto\">Michael Buice<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"6\" aria-setsize=\"-1\" data-aria-posinset=\"4\" data-aria-level=\"1\"><span data-contrast=\"auto\">Huijeong Jeong<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"6\" aria-setsize=\"-1\" data-aria-posinset=\"5\" data-aria-level=\"1\"><span data-contrast=\"auto\">Xiaoxuan Jia<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"6\" aria-setsize=\"-1\" data-aria-posinset=\"6\" data-aria-level=\"1\"><span data-contrast=\"auto\">Rob Kass<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"6\" aria-setsize=\"-1\" data-aria-posinset=\"7\" data-aria-level=\"1\"><span data-contrast=\"auto\">Stefan Mihalas<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"6\" aria-setsize=\"-1\" data-aria-posinset=\"8\" data-aria-level=\"1\"><span data-contrast=\"auto\">Yann Sweeney<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"6\" aria-setsize=\"-1\" data-aria-posinset=\"9\" data-aria-level=\"1\"><span data-contrast=\"auto\">Josh Siegle<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<\/ul>\n<\/div><\/div><\/div><\/section>\n<section class='av_toggle_section av-w12at-58567b52a8cdb9e5a92053211bb32d70' ><div role=\"tablist\" class=\"single_toggle\" data-tags=\"{All} \"  ><p id='toggle-neural-computations-learning-and-dynamics-in-recurrent-networks' data-fake-id='#neural-computations-learning-and-dynamics-in-recurrent-networks' class='toggler  av-title-above av-inherit-border-color'  role='tab' tabindex='0' aria-controls='neural-computations-learning-and-dynamics-in-recurrent-networks' data-slide-speed=\"200\" data-title=\" Neural computations: Learning and dynamics in recurrent networks&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Manuel Beiran, Friedrich Schuessler&lt;\/span&gt;\" data-title-open=\"\" data-aria_collapsed=\"Click to expand:  Neural computations: Learning and dynamics in recurrent networks&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Manuel Beiran, Friedrich Schuessler&lt;\/span&gt;\" data-aria_expanded=\"Click to collapse:  Neural computations: Learning and dynamics in recurrent networks&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Manuel Beiran, Friedrich Schuessler&lt;\/span&gt;\"> Neural computations: Learning and dynamics in recurrent networks<br \/>\n<span class=\"workshop-subtitle\"><strong>Organizers:<\/strong> Manuel Beiran, Friedrich Schuessler<\/span><span class=\"toggle_icon\"><span class=\"vert_icon\"><\/span><span class=\"hor_icon\"><\/span><\/span><\/p><div id='neural-computations-learning-and-dynamics-in-recurrent-networks' aria-labelledby='toggle-neural-computations-learning-and-dynamics-in-recurrent-networks' role='region' class='toggle_wrap  av-title-above'  ><div class='toggle_content invers-color av-inherit-border-color' ><p><strong>Description:<\/strong><\/p>\n<p class=\"p1\">Trained recurrent neural networks (RNNs) have become an important tool to understand how biological neural networks perform cognitive tasks. On the one hand, RNNs can help to understand the computations that are needed to solve a task and how these are implemented by the network. On the other hand, learning itself can be studied in RNNs, with the goal of understanding general underlying mechanisms that are also relevant in biology. Both aspects, learning and dynamics, are far from being fully understood, but the last years have brought exciting insights.<\/p>\n<p class=\"p1\">In this workshop, we will hear about recent works from both perspectives. We will see how the activity of trained RNNs can be framed in the language of dynamical systems. This reveals how networks implement computations and multitasking based on low-dimensional activity. We will further hear about the interaction between neural dynamics and learning, and how biological constraints can be incorporated into the learning algorithms. Finally, we will see how trained RNNs can be applied to understand neural recordings and make experimental predictions. The workshop will end with a discussion on how the insights into learning and dynamics together can form a unified perspective on tasks, learning algorithms, and the necessary underlying computations.<\/p>\n<p><strong>Speakers:<\/strong><\/p>\n<ul>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"7\" aria-setsize=\"-1\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">R\u00e9mi Monasson<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"7\" aria-setsize=\"-1\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"auto\">Devika Narain<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"7\" aria-setsize=\"-1\" data-aria-posinset=\"3\" data-aria-level=\"1\"><span data-contrast=\"auto\">Ran Darshan<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"7\" aria-setsize=\"-1\" data-aria-posinset=\"4\" data-aria-level=\"1\"><span data-contrast=\"auto\">Guangyu Robert Yang<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"7\" aria-setsize=\"-1\" data-aria-posinset=\"5\" data-aria-level=\"1\"><span data-contrast=\"auto\">Kanaka Rajan<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"7\" aria-setsize=\"-1\" data-aria-posinset=\"6\" data-aria-level=\"1\"><span data-contrast=\"auto\">Alexis Dubreuil<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"7\" aria-setsize=\"-1\" data-aria-posinset=\"7\" data-aria-level=\"1\"><span data-contrast=\"auto\">Cristina Savin<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<\/ul>\n<\/div><\/div><\/div><\/section>\n<section class='av_toggle_section av-ovv1h-4da00b729f8067fc37a22e813bfebdff' ><div role=\"tablist\" class=\"single_toggle\" data-tags=\"{All} \"  ><p id='toggle-neurons-are-cells-the-role-of-cellular-properties-in-neural-circuit-computations' data-fake-id='#neurons-are-cells-the-role-of-cellular-properties-in-neural-circuit-computations' class='toggler  av-title-above av-inherit-border-color'  role='tab' tabindex='0' aria-controls='neurons-are-cells-the-role-of-cellular-properties-in-neural-circuit-computations' data-slide-speed=\"200\" data-title=\"Neurons are cells: the role of cellular properties in neural circuit computations&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Cian O\u2019Donnell, Philipp Berens&lt;\/span&gt;\" data-title-open=\"\" data-aria_collapsed=\"Click to expand: Neurons are cells: the role of cellular properties in neural circuit computations&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Cian O\u2019Donnell, Philipp Berens&lt;\/span&gt;\" data-aria_expanded=\"Click to collapse: Neurons are cells: the role of cellular properties in neural circuit computations&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Cian O\u2019Donnell, Philipp Berens&lt;\/span&gt;\">Neurons are cells: the role of cellular properties in neural circuit computations<br \/>\n<span class=\"workshop-subtitle\"><strong>Organizers:<\/strong> Cian O\u2019Donnell, Philipp Berens<\/span><span class=\"toggle_icon\"><span class=\"vert_icon\"><\/span><span class=\"hor_icon\"><\/span><\/span><\/p><div id='neurons-are-cells-the-role-of-cellular-properties-in-neural-circuit-computations' aria-labelledby='toggle-neurons-are-cells-the-role-of-cellular-properties-in-neural-circuit-computations' role='region' class='toggle_wrap  av-title-above'  ><div class='toggle_content invers-color av-inherit-border-color' ><p><strong>Description:<\/strong><\/p>\n<p>Neuroscience is challenging because the brain is multi-scaled: computations are performed by molecules, cells, microcircuits, and whole-brain networks, together and in parallel. Systems neuroscientists traditionally focus on the computations performed by neural circuits, while abstracting or ignoring mechanisms of single cells. Single-neuron researchers, on the other hand, have uncovered the complexity of neuronal gene expression, dendritic physiology, and synaptic signalling. But only limited sharing of ideas has occurred between these two fields. There is little role for single-neuron mechanisms in current theories of brain computation. This workshop aims to bridge this divide by bringing together computational and experimental researchers who study single-cell processes and consider their implications for brain circuit function.<\/p>\n<p>The talks will come from three perspectives: experimentalists, data analysts, and theoretical modellers. The workshop will ask all speakers and attendees to jointly address three high-level questions:<\/p>\n<ol>\n<li>What should the future directions for this field be?<\/li>\n<li>What conceptual, sociological, and technical challenges will need to be overcome?<\/li>\n<li>What are the practical next steps needed to make progress?<\/li>\n<\/ol>\n<p><strong>Speakers:<\/strong><\/p>\n<ul>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"8\" aria-setsize=\"-1\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">M\u00e1t\u00e9 Lengyel<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"8\" aria-setsize=\"-1\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"auto\">Yiota Poirazi<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"8\" aria-setsize=\"-1\" data-aria-posinset=\"3\" data-aria-level=\"1\"><span data-contrast=\"auto\">Romain Brette<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"8\" aria-setsize=\"-1\" data-aria-posinset=\"4\" data-aria-level=\"1\"><span data-contrast=\"auto\">Tatjana Tchumatchenko<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"8\" aria-setsize=\"-1\" data-aria-posinset=\"5\" data-aria-level=\"1\"><span data-contrast=\"auto\">Jakob Macke<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"8\" aria-setsize=\"-1\" data-aria-posinset=\"6\" data-aria-level=\"1\"><span data-contrast=\"auto\">Simone Mayer<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"8\" aria-setsize=\"-1\" data-aria-posinset=\"7\" data-aria-level=\"1\"><span data-contrast=\"auto\">Gabe Murphy<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"8\" aria-setsize=\"-1\" data-aria-posinset=\"8\" data-aria-level=\"1\"><span data-contrast=\"auto\">Ken Harris<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<\/ul>\n<\/div><\/div><\/div><\/section>\n<section class='av_toggle_section av-6f9rw5-a8d4e7b63b2637e669f213a431c294a8' ><div role=\"tablist\" class=\"single_toggle\" data-tags=\"{All} \"  ><p id='toggle-the-making-and-breaking-of-ei-balance' data-fake-id='#the-making-and-breaking-of-ei-balance' class='toggler  av-title-above av-inherit-border-color'  role='tab' tabindex='0' aria-controls='the-making-and-breaking-of-ei-balance' data-slide-speed=\"200\" data-title=\"The making and breaking of E\/I balance&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Loreen Hert\u00e4g, Henning Sprekeler&lt;\/span&gt;\" data-title-open=\"\" data-aria_collapsed=\"Click to expand: The making and breaking of E\/I balance&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Loreen Hert\u00e4g, Henning Sprekeler&lt;\/span&gt;\" data-aria_expanded=\"Click to collapse: The making and breaking of E\/I balance&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Loreen Hert\u00e4g, Henning Sprekeler&lt;\/span&gt;\">The making and breaking of E\/I balance<br \/>\n<span class=\"workshop-subtitle\"><strong>Organizers:<\/strong> Loreen Hert\u00e4g, Henning Sprekeler<\/span><span class=\"toggle_icon\"><span class=\"vert_icon\"><\/span><span class=\"hor_icon\"><\/span><\/span><\/p><div id='the-making-and-breaking-of-ei-balance' aria-labelledby='toggle-the-making-and-breaking-of-ei-balance' role='region' class='toggle_wrap  av-title-above'  ><div class='toggle_content invers-color av-inherit-border-color' ><p><strong>Description:<\/strong><\/p>\n<p>The coordinated interplay between excitation (E) and inhibition (I) is the backbone of neuronal activity and cortical computations. New techniques for cell type-specific neural recordings in behaving animals provide an opportunity to revisit the concept of E\/I balance and address long-standing questions. How specific is E\/I balance in space and time? How does its specificity influence cortical computations? How do different types of inhibitory interneurons contribute to the co-activation of excitation and inhibition? What is the function of E\/I balance and disruptions thereof? How does it shape information processing and learning?<\/p>\n<p>Tackling these questions will require a combination of experiment and theory. The goal of this workshop is therefore to bring together theoreticians and experimentalists with different perspectives on the interaction of excitation and inhibition. We hope to facilitate scientific exchange that inspires new ideas about how E\/I balance shapes sensory processing and behavior.<\/p>\n<p><strong>Speakers:<\/strong><\/p>\n<ul>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"9\" aria-setsize=\"-1\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">Sonja Hofer<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"9\" aria-setsize=\"-1\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"auto\">Claudia Clopath<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"9\" aria-setsize=\"-1\" data-aria-posinset=\"3\" data-aria-level=\"1\"><span data-contrast=\"auto\">Rainer Friedrich<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"9\" aria-setsize=\"-1\" data-aria-posinset=\"4\" data-aria-level=\"1\"><span data-contrast=\"auto\">Christian Machens<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"9\" aria-setsize=\"-1\" data-aria-posinset=\"5\" data-aria-level=\"1\"><span data-contrast=\"auto\">Georg Keller<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"9\" aria-setsize=\"-1\" data-aria-posinset=\"6\" data-aria-level=\"1\"><span data-contrast=\"auto\">Loreen Hert\u00e4g<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"9\" aria-setsize=\"-1\" data-aria-posinset=\"7\" data-aria-level=\"1\"><span data-contrast=\"auto\">Anne Churchland<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"9\" aria-setsize=\"-1\" data-aria-posinset=\"8\" data-aria-level=\"1\"><span data-contrast=\"auto\">Yashar Ahmadian<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"9\" aria-setsize=\"-1\" data-aria-posinset=\"9\" data-aria-level=\"1\"><span data-contrast=\"auto\">Johannes Letzkus<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"9\" aria-setsize=\"-1\" data-aria-posinset=\"10\" data-aria-level=\"1\"><span data-contrast=\"auto\">Tim Vogels<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<\/ul>\n<\/div><\/div><\/div><\/section>\n<section class='av_toggle_section av-3ntbad-33e0f4abfbe8d9df8ddf2b5fbadea629' ><div role=\"tablist\" class=\"single_toggle\" data-tags=\"{All} \"  ><p id='toggle-understanding-computations-of-basal-nervous-systems-from-paramecium-to-jellyfish' data-fake-id='#understanding-computations-of-basal-nervous-systems-from-paramecium-to-jellyfish' class='toggler  av-title-above av-inherit-border-color'  role='tab' tabindex='0' aria-controls='understanding-computations-of-basal-nervous-systems-from-paramecium-to-jellyfish' data-slide-speed=\"200\" data-title=\"Understanding Computations of Basal Nervous Systems: From Paramecium to Jellyfish&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Fabian Pallasdies, Jan-Hendrik Schleimer, Susanne Schreiber&lt;\/span&gt;\" data-title-open=\"\" data-aria_collapsed=\"Click to expand: Understanding Computations of Basal Nervous Systems: From Paramecium to Jellyfish&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Fabian Pallasdies, Jan-Hendrik Schleimer, Susanne Schreiber&lt;\/span&gt;\" data-aria_expanded=\"Click to collapse: Understanding Computations of Basal Nervous Systems: From Paramecium to Jellyfish&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Fabian Pallasdies, Jan-Hendrik Schleimer, Susanne Schreiber&lt;\/span&gt;\">Understanding Computations of Basal Nervous Systems: From Paramecium to Jellyfish<br \/>\n<span class=\"workshop-subtitle\"><strong>Organizers:<\/strong> Fabian Pallasdies, Jan-Hendrik Schleimer, Susanne Schreiber<\/span><span class=\"toggle_icon\"><span class=\"vert_icon\"><\/span><span class=\"hor_icon\"><\/span><\/span><\/p><div id='understanding-computations-of-basal-nervous-systems-from-paramecium-to-jellyfish' aria-labelledby='toggle-understanding-computations-of-basal-nervous-systems-from-paramecium-to-jellyfish' role='region' class='toggle_wrap  av-title-above'  ><div class='toggle_content invers-color av-inherit-border-color' ><p><strong>Description:<\/strong><\/p>\n<p class=\"p1\">As &#8220;nothing in biology makes sense except in the light of evolution,&#8221; a theory on the origins of nervous systems is crucial for our understanding of how the structure of nerve tissue evolved to satisfy the computational demands of animals at large. This topic has been addressed in many different fields of biology, yet communication across fields is sparse. To shed light on the evolutionary trajectories, however, a more holistic understanding of the systems studied is required, encompassing the macroscopic behavior of simple animals to the electrophysiological details of their nervous systems.<\/p>\n<p class=\"p1\">Our aim is to bring together researchers with expertise across different species from jellyfish and corals to ctenophores and sponges to investigate the evolutionary origins of neurons and information-processing nerve nets. Our focus is to discuss how modelling can aid in the study of early nervous systems and what we can learn from these comparatively simple organisms about the computations performed by the nervous systems of higher animals.<\/p>\n<p><strong>Speakers:<\/strong><\/p>\n<ul>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"10\" aria-setsize=\"-1\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">Romain Brette<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"10\" aria-setsize=\"-1\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"auto\">Kristin Tessmar-Raible<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"10\" aria-setsize=\"-1\" data-aria-posinset=\"3\" data-aria-level=\"1\"><span data-contrast=\"auto\">G\u00e1sp\u00e1r J\u00e9kely<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"10\" aria-setsize=\"-1\" data-aria-posinset=\"4\" data-aria-level=\"1\"><span data-contrast=\"auto\">Fred A. Keijzer<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"10\" aria-setsize=\"-1\" data-aria-posinset=\"5\" data-aria-level=\"1\"><span data-contrast=\"auto\">Sally Leys<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"10\" aria-setsize=\"-1\" data-aria-posinset=\"6\" data-aria-level=\"1\"><span data-contrast=\"auto\">Wilhelm Braun<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"10\" aria-setsize=\"-1\" data-aria-posinset=\"7\" data-aria-level=\"1\"><span data-contrast=\"auto\">Julia E. Samson<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<\/ul>\n<\/div><\/div><\/div><\/section>\n<section class='av_toggle_section av-32bs2d-9a1900001d84c677baf4aad5de86ca37' ><div role=\"tablist\" class=\"single_toggle\" data-tags=\"{All} \"  ><p id='toggle-visuomotor-coordination-from-physiology-to-control-systems' data-fake-id='#visuomotor-coordination-from-physiology-to-control-systems' class='toggler  av-title-above av-inherit-border-color'  role='tab' tabindex='0' aria-controls='visuomotor-coordination-from-physiology-to-control-systems' data-slide-speed=\"200\" data-title=\"Visuomotor coordination: from physiology to control systems&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Egidio d\u2019Angelo, Sacha van Albada&lt;\/span&gt;\" data-title-open=\"\" data-aria_collapsed=\"Click to expand: Visuomotor coordination: from physiology to control systems&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Egidio d\u2019Angelo, Sacha van Albada&lt;\/span&gt;\" data-aria_expanded=\"Click to collapse: Visuomotor coordination: from physiology to control systems&lt;br \/&gt;\n&lt;span class=&quot;workshop-subtitle&quot;&gt;&lt;strong&gt;Organizers:&lt;\/strong&gt; Egidio d\u2019Angelo, Sacha van Albada&lt;\/span&gt;\">Visuomotor coordination: from physiology to control systems<br \/>\n<span class=\"workshop-subtitle\"><strong>Organizers:<\/strong> Egidio d\u2019Angelo, Sacha van Albada<\/span><span class=\"toggle_icon\"><span class=\"vert_icon\"><\/span><span class=\"hor_icon\"><\/span><\/span><\/p><div id='visuomotor-coordination-from-physiology-to-control-systems' aria-labelledby='toggle-visuomotor-coordination-from-physiology-to-control-systems' role='region' class='toggle_wrap  av-title-above'  ><div class='toggle_content invers-color av-inherit-border-color' ><p><strong>Description:<\/strong><\/p>\n<p>Visuomotor coordination involves a highly complex set of brain functions encompassing a large number of brain regions, which interact dynamically not only with each other but also with the environment. Understanding these processes requires expertise from multiple angles, including physiology, systems neuroscience, and control systems. In this workshop, we aim to bring together insights from experimental and computational studies of visuomotor coordination, covering the main brain regions involved (cerebellum, cerebral cortex, basal ganglia), and their interactions. The interpretation of observed brain activity requires knowledge about the information processing it represents, and the motor behavior it results in. Embodiment and interactions with the environment are therefore considered in the context of neurorobotic control systems.<\/p>\n<p><strong>Speakers:<\/strong><\/p>\n<ul>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"11\" aria-setsize=\"-1\" data-aria-posinset=\"1\" data-aria-level=\"1\"><span data-contrast=\"auto\">Junji Ito<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"11\" aria-setsize=\"-1\" data-aria-posinset=\"2\" data-aria-level=\"1\"><span data-contrast=\"auto\">Lawrence Snyder<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"11\" aria-setsize=\"-1\" data-aria-posinset=\"3\" data-aria-level=\"1\"><span data-contrast=\"auto\">Egidio d&#8217;Angelo<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"11\" aria-setsize=\"-1\" data-aria-posinset=\"4\" data-aria-level=\"1\"><span data-contrast=\"auto\">Egidio Falotico\/ Claudia Casellato<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"11\" aria-setsize=\"-1\" data-aria-posinset=\"5\" data-aria-level=\"1\"><span data-contrast=\"auto\">Chris de Zeeuw<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"11\" aria-setsize=\"-1\" data-aria-posinset=\"6\" data-aria-level=\"1\"><span data-contrast=\"auto\">Reza Shadmehr<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<li data-leveltext=\"\uf0b7\" data-font=\"Symbol\" data-listid=\"11\" aria-setsize=\"-1\" data-aria-posinset=\"7\" data-aria-level=\"1\"><span data-contrast=\"auto\">Carol Seger<\/span><span data-ccp-props=\"{\">\u00a0<\/span><\/li>\n<\/ul>\n<\/div><\/div><\/div><\/section>\n<\/div><\/div><\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='sub_menu1'  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class=\"avia-arrow-wrap\"><span class=\"avia-arrow\"><\/span><\/span><\/span><\/a><\/li>\n<\/ul><\/div><\/div><\/p>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":1,"featured_media":0,"parent":6892,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-7352","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.9 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Bernstein Conference 2020 &#8211; Bernstein Network Computational Neuroscience<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/bernstein-network.de\/en\/bernstein-conference\/past-future-bernstein-conferences\/bernstein-conference-2020\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" 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