Representational Geometries of Perception and Working Memory

Representational Geometries Across Visual Working Memory Encoding and Maintenance | bioRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var j=j||B.errorTimeout,l=b.createElement(a),o=0,r=0,u={t:d,s:c,e:f,a:i,x:j};1===y[c]&&(r=1,y[c]=[]),"object"==a?l.data=c:(l.src=c,l.type=a),l.width=l.height="0",l.onerror=l.onload=l.onreadystatechange=function(){k.call(this,r)},p.splice(e,0,u),"img"!=a&&(r||2===y[c]?(t.insertBefore(l,s?null:n),m(k,j)):y[c].push(l))}function j(a,b,c,d,f){return q=0,b=b||"j",e(a)?i("c"==b?v:u,a,b,this.i++,c,d,f):(p.splice(this.i++,0,a),1==p.length&&h()),this}function k(){var a=B;return a.loader={load:j,i:0},a}var l=b.documentElement,m=a.setTimeout,n=b.getElementsByTagName("script")[0],o={}.toString,p=[],q=0,r="MozAppearance"in l.style,s=r&&!!b.createRange().compareNode,t=s?l:n.parentNode,l=a.opera&&"[object Opera]"==o.call(a.opera),l=!!b.attachEvent&&!l,u=r?"object":l?"script":"img",v=l?"script":u,w=Array.isArray||function(a){return"[object Array]"==o.call(a)},x=[],y={},z={timeout:function(a,b){return b.length&&(a.timeout=b[0]),a}},A,B;B=function(a){function b(a){var a=a.split("!"),b=x.length,c=a.pop(),d=a.length,c={url:c,origUrl:c,prefixes:a},e,f,g;for(f=0;f<d;f++)g=a[f].split("="),(e=z[g.shift()])&&(c=e(c,g));for(f=0;f<b;f++)c=x[f](c);return c}function g(a,e,f,g,h){var i=b(a),j=i.autoCallback;i.url.split(".").pop().split("?").shift(),i.bypass||(e&&(e=d(e)?e:e[a]||e[g]||e[a.split("/").pop().split("?")[0]]),i.instead?i.instead(a,e,f,g,h):(y[i.url]?i.noexec=!0:y[i.url]=1,f.load(i.url,i.forceCSS||!i.forceJS&&"css"==i.url.split(".").pop().split("?").shift()?"c":c,i.noexec,i.attrs,i.timeout),(d(e)||d(j))&&f.load(function(){k(),e&&e(i.origUrl,h,g),j&&j(i.origUrl,h,g),y[i.url]=2})))}function h(a,b){function c(a,c){if(a){if(e(a))c||(j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}),g(a,j,b,0,h);else if(Object(a)===a)for(n in m=function(){var b=0,c;for(c in a)a.hasOwnProperty(c)&&b++;return b}(),a)a.hasOwnProperty(n)&&(!c&&!--m&&(d(j)?j=function(){var a=[].slice.call(arguments);k.apply(this,a),l()}:j[n]=function(a){return function(){var b=[].slice.call(arguments);a&&a.apply(this,b),l()}}(k[n])),g(a[n],j,b,n,h))}else!c&&l()}var h=!!a.test,i=a.load||a.both,j=a.callback||f,k=j,l=a.complete||f,m,n;c(h?a.yep:a.nope,!!i),i&&c(i)}var i,j,l=this.yepnope.loader;if(e(a))g(a,0,l,0);else if(w(a))for(i=0;i (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0];var j=d.createElement(s);var dl=l!='dataLayer'?'&l='+l:'';j.src='//www.googletagmanager.com/gtm.js?id='+i+dl;j.type='text/javascript';j.async=true;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-M677548'); Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Representational Geometries Across Visual Working Memory Encoding and Maintenance View ORCID Profile Tomoya Nakamura , View ORCID Profile Seng Bum Michael Yoo , View ORCID Profile Kendrick Kay , View ORCID Profile Hakwan Lau , View ORCID Profile Ali Moharramipour doi: https://doi.org/10.1101/2025.09.07.674590 Tomoya Nakamura 1 RIKEN; Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Tomoya Nakamura For correspondence: tomoya.nakamura{at}riken.jp Seng Bum Michael Yoo 2 Center for Neuroscience Imaging Research, Institute for Basic Science; Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Seng Bum Michael Yoo Kendrick Kay 3 Department of Radiology, University of Minnesota; Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Kendrick Kay Hakwan Lau 2 Center for Neuroscience Imaging Research, Institute for Basic Science; Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Hakwan Lau Ali Moharramipour 4 Center for Brain Science, RIKEN Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Ali Moharramipour Abstract Info/History Metrics Supplementary material Preview PDF Abstract This study examined the representational geometry of visual working memory using human 7T fMRI. Observers viewed a facescene blended sample, attended to either the face or scene, and judged whether the attended aspect matched a subsequent test image. We found that the coding dimension distinguishing faces and scenes rotated between encoding and maintenance phases, in both visual and association areas. In these regions, exclusive combinations (i.e., encoded face and maintained scene vs. encoded scene and maintained face) were linearly decodable, indicating encoding and maintenance phases represent visual information using distinct subspaces. Such high-dimensional, flexible geometry can, in principle, protect maintained visual information from incoming input. At the same time, robust crossdecoding was observed across phases, reflecting the stability and generalizability of the represented contents. The balance between representational flexibility and stability varied along the cortical hierarchy: early sensory regions emphasized flexibility, whereas transmodal regions showed greater stability. Competing Interest Statement The authors have declared no competing interest. Footnotes In this revision, we changed the conceptual framing of the manuscript from a perception-versus-working-memory comparison to an investigation of representational differences between the encoding and maintenance phases of working memory. Funder Information Declared Japan Society for the Promotion of Science , 24KJ0233 , 25K18957 , 25K00896 Institute for Basic Science , IBS-R015-D2 Copyright The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license . View the discussion thread. Back to top Previous Next Posted May 25, 2026. 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Share Representational Geometries Across Visual Working Memory Encoding and Maintenance Tomoya Nakamura , Seng Bum Michael Yoo , Kendrick Kay , Hakwan Lau , Ali Moharramipour bioRxiv 2025.09.07.674590; doi: https://doi.org/10.1101/2025.09.07.674590 Share This Article: Copy Citation Tools Representational Geometries Across Visual Working Memory Encoding and Maintenance Tomoya Nakamura , Seng Bum Michael Yoo , Kendrick Kay , Hakwan Lau , Ali Moharramipour bioRxiv 2025.09.07.674590; doi: https://doi.org/10.1101/2025.09.07.674590 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Neuroscience Subject Areas All Articles Animal Behavior and Cognition (7643) Biochemistry (17717) Bioengineering (13910) Bioinformatics (42015) Biophysics (21477) Cancer Biology (18626) Cell Biology (25536) Clinical Trials (138) Developmental Biology (13392) Ecology (19935) Epidemiology (2067) Evolutionary Biology (24356) Genetics (15617) Genomics (22530) Immunology (17755) Microbiology (40437) Molecular Biology (17200) Neuroscience (88703) Paleontology (667) Pathology (2840) Pharmacology and Toxicology (4832) Physiology (7657) Plant Biology (15171) Scientific Communication and Education (2046) Synthetic Biology (4304) Systems Biology (9828) Zoology (2272)