Alessandro T. Gifford, Maya A. Jastrzębowska, Johannes J. D. Singer, Radoslaw M. Cichy
{"title":"视觉皮层表征关系的计算机发现","authors":"Alessandro T. Gifford, Maya A. Jastrzębowska, Johannes J. D. Singer, Radoslaw M. Cichy","doi":"10.1038/s41562-025-02252-z","DOIUrl":null,"url":null,"abstract":"<p>Human vision is mediated by a complex interconnected network of cortical brain areas that jointly represent visual information. Although these areas are increasingly understood in isolation, their representational relationships remain unclear. Here we developed relational neural control and used it to investigate the representational relationships for univariate and multivariate functional magnetic resonance imaging (fMRI) responses of areas across the visual cortex. Through relational neural control, we generated and explored in silico fMRI responses for large numbers of images, discovering controlling images that align or disentangle responses across areas, thus indicating their shared or unique representational content. This revealed a typical network-level configuration of representational relationships in which shared or unique representational content varied on the basis of cortical distance, categorical selectivity and position within the visual hierarchy. Closing the empirical cycle, we validated the in silico discoveries on in vivo fMRI responses from independent participants. Together, this reveals how visual areas jointly represent the world as an interconnected network.</p>","PeriodicalId":19074,"journal":{"name":"Nature Human Behaviour","volume":"90 1","pages":""},"PeriodicalIF":21.4000,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"In silico discovery of representational relationships across visual cortex\",\"authors\":\"Alessandro T. Gifford, Maya A. Jastrzębowska, Johannes J. D. Singer, Radoslaw M. Cichy\",\"doi\":\"10.1038/s41562-025-02252-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Human vision is mediated by a complex interconnected network of cortical brain areas that jointly represent visual information. Although these areas are increasingly understood in isolation, their representational relationships remain unclear. Here we developed relational neural control and used it to investigate the representational relationships for univariate and multivariate functional magnetic resonance imaging (fMRI) responses of areas across the visual cortex. Through relational neural control, we generated and explored in silico fMRI responses for large numbers of images, discovering controlling images that align or disentangle responses across areas, thus indicating their shared or unique representational content. This revealed a typical network-level configuration of representational relationships in which shared or unique representational content varied on the basis of cortical distance, categorical selectivity and position within the visual hierarchy. Closing the empirical cycle, we validated the in silico discoveries on in vivo fMRI responses from independent participants. Together, this reveals how visual areas jointly represent the world as an interconnected network.</p>\",\"PeriodicalId\":19074,\"journal\":{\"name\":\"Nature Human Behaviour\",\"volume\":\"90 1\",\"pages\":\"\"},\"PeriodicalIF\":21.4000,\"publicationDate\":\"2025-06-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature Human Behaviour\",\"FirstCategoryId\":\"102\",\"ListUrlMain\":\"https://doi.org/10.1038/s41562-025-02252-z\",\"RegionNum\":1,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Human Behaviour","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1038/s41562-025-02252-z","RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
In silico discovery of representational relationships across visual cortex
Human vision is mediated by a complex interconnected network of cortical brain areas that jointly represent visual information. Although these areas are increasingly understood in isolation, their representational relationships remain unclear. Here we developed relational neural control and used it to investigate the representational relationships for univariate and multivariate functional magnetic resonance imaging (fMRI) responses of areas across the visual cortex. Through relational neural control, we generated and explored in silico fMRI responses for large numbers of images, discovering controlling images that align or disentangle responses across areas, thus indicating their shared or unique representational content. This revealed a typical network-level configuration of representational relationships in which shared or unique representational content varied on the basis of cortical distance, categorical selectivity and position within the visual hierarchy. Closing the empirical cycle, we validated the in silico discoveries on in vivo fMRI responses from independent participants. Together, this reveals how visual areas jointly represent the world as an interconnected network.
期刊介绍:
Nature Human Behaviour is a journal that focuses on publishing research of outstanding significance into any aspect of human behavior.The research can cover various areas such as psychological, biological, and social bases of human behavior.It also includes the study of origins, development, and disorders related to human behavior.The primary aim of the journal is to increase the visibility of research in the field and enhance its societal reach and impact.