{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/fundamental-principles-of-cortical","title":"Fundamental principles of cortical computation: unsupervised learning with prediction, compression and feedback","arxiv_id":"1608.06277","date":"2016-08-19","proceeding":null,"authors":["Micah Richert","Dimitry Fisher","Filip Piekniewski","Eugene M. Izhikevich","Todd L. Hylton"],"abstract":"There has been great progress in understanding of anatomical and functional\nmicrocircuitry of the primate cortex. However, the fundamental principles of\ncortical computation - the principles that allow the visual cortex to bind\nretinal spikes into representations of objects, scenes and scenarios - have so\nfar remained elusive. In an attempt to come closer to understanding the\nfundamental principles of cortical computation, here we present a functional,\nphenomenological model of the primate visual cortex. The core part of the model\ndescribes four hierarchical cortical areas with feedforward, lateral, and\nrecurrent connections. The three main principles implemented in the model are\ninformation compression, unsupervised learning by prediction, and use of\nlateral and top-down context. We show that the model reproduces key aspects of\nthe primate ventral stream of visual processing including Simple and Complex\ncells in V1, increasingly complicated feature encoding, and increased\nseparability of object representations in higher cortical areas. The model\nlearns representations of the visual environment that allow for accurate\nclassification and state-of-the-art visual tracking performance on novel\nobjects.","url_abs":"http://arxiv.org/abs/1608.06277v1","url_pdf":"http://arxiv.org/pdf/1608.06277v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"fundamental-principles-of-cortical","repo_url":"https://github.com/braincorp/ASC","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"visual-tracking","task_name":"Visual Tracking"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}