{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T13:42:51Z","timestamp":1792762971803,"version":"4.5.0"},"reference-count":0,"publisher":"MIT Press","funder":[{"name":"Natural Science Foundation of China","award":["82472061"],"award-info":[{"award-number":["82472061"]}]},{"name":"Chongqing Science and Health Joint Medical Research Key\n                                Project","award":["2025GGXM005"],"award-info":[{"award-number":["2025GGXM005"]}]},{"name":"Yantai \u201cDouble Hundred Plan\u201d","award":["Talent Grant"],"award-info":[{"award-number":["Talent Grant"]}]},{"name":"STI2030-Major Projects","award":["2021ZD0200200"],"award-info":[{"award-number":["2021ZD0200200"]}]},{"name":"Beijing Natural Science Foundation","award":["7262231"],"award-info":[{"award-number":["7262231"]}]}],"content-domain":{"domain":["direct.mit.edu"],"crossmark-restriction":true},"short-container-title":[],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Object representations in the human higher visual cortex (HVC) support complex recognition behaviors early in development, yet the principles linking continuous dimensional representations and discrete category-selective areas in the HVC remain incompletely understood. Here, we propose a \u201cproperty\u2013cluster\u2013category\u201d organization that bridges object conceptual dimensions and discrete category areas in the HVC. Using a large-scale naturalistic stimulus data set and voxel-wise encoding methods, we analyzed the encoding patterns of a low-dimensional abstract property space and identified distinct brain clusters with shared cortical property profiles. These clusters broadly aligned with category-selective areas, suggesting that category regions can be understood as local peaks within a continuous property topology. We further tested whether this visual organization could emerge in a visual-only Topographic Deep Artificial Neural Network trained without semantic supervision. The model recapitulated property tuning for physical and biological dimensions but showed weaker affective tuning, suggesting that affective dimensions may require embodied or nonvisual experience. Finally, model-based lesion and stimulation analyses showed that Topographic Deep Artificial Neural Network units aligned with brain clusters contributed selectively to object classification. Together, these results provide a framework for understanding how the continuous property topology and discrete category selectivity are jointly organized in the human HVC, and suggest that abstract visual properties\u2014which shape this topological organization\u2014can be learned in part from statistical regularities in visual input.<\/jats:p>","DOI":"10.1162\/jocn.a.2720","type":"journal-article","created":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T17:29:55Z","timestamp":1789579795000},"page":"1-18","update-policy":"https:\/\/doi.org\/10.1162\/mitpressjournals.corrections.policy","source":"Crossref","is-referenced-by-count":0,"title":["Abstract Property-selective Clusters Link Continuous Property\n                    Representations to Discrete Category-selective Regions in Human Higher Visual\n                    Cortex"],"prefix":"10.1162","author":[{"given":"Qiande","family":"Zhao","sequence":"first","affiliation":[{"name":"Beijing Key Laboratory of Brainnetome and Brain-Computer Interface, Institute of Automation, Chinese Academy of Sciences"},{"name":"Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China"},{"name":"University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junhai","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Deying","family":"Li","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory of Brainnetome and Brain-Computer Interface, Institute of Automation, Chinese Academy of Sciences"},{"name":"Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China"},{"name":"University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xia","family":"Wu","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory of Brainnetome and Brain-Computer Interface, Institute of Automation, Chinese Academy of Sciences"},{"name":"Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China"},{"name":"University of Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kang","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Life and Health Sciences, University of Health and Rehabilitation Sciences, Qingdao, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Congying","family":"Chu","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory of Brainnetome and Brain-Computer Interface, Institute of Automation, Chinese Academy of Sciences"},{"name":"Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4813-621X","authenticated-orcid":true,"given":"Lingzhong","family":"Fan","sequence":"additional","affiliation":[{"name":"Beijing Key Laboratory of Brainnetome and Brain-Computer Interface, Institute of Automation, Chinese Academy of Sciences"},{"name":"Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China"},{"name":"University of Chinese Academy of Sciences, Beijing, China"},{"name":"School of Life and Health Sciences, University of Health and Rehabilitation Sciences, Qingdao, China"},{"name":"Shandong Key Lab of Complex Medical Intelligence and Aging, Shandong Medical And Pharmaceutical University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"281","published-online":{"date-parts":[[2026,10,23]]},"container-title":["Journal of Cognitive Neuroscience"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/direct.mit.edu\/jocn\/article-pdf\/doi\/10.1162\/JOCN.a.2720\/2628842\/jocn.a.2720.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/direct.mit.edu\/jocn\/article-pdf\/doi\/10.1162\/JOCN.a.2720\/2628842\/jocn.a.2720.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T13:31:26Z","timestamp":1792762286000},"score":1,"resource":{"primary":{"URL":"https:\/\/direct.mit.edu\/jocn\/article\/doi\/10.1162\/JOCN.a.2720\/139022\/Abstract-Property-selective-Clusters-Link"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10,23]]},"references-count":0,"URL":"https:\/\/doi.org\/10.1162\/jocn.a.2720","relation":{},"ISSN":["0898-929X","1530-8898"],"issn-type":[{"value":"0898-929X","type":"print"},{"value":"1530-8898","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10,23]]}}}