{"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/clique-topology-reveals-intrinsic-geometric","title":"Clique topology reveals intrinsic geometric structure in neural correlations","arxiv_id":"1502.06172","date":"2015-02-22","proceeding":null,"authors":[],"abstract":"Detecting meaningful structure in neural activity and connectivity data is\nchallenging in the presence of hidden nonlinearities, where traditional\neigenvalue-based methods may be misleading. We introduce a novel approach to\nmatrix analysis, called clique topology, that extracts features of the data\ninvariant under nonlinear monotone transformations. These features can be used\nto detect both random and geometric structure, and depend only on the relative\nordering of matrix entries. We then analyzed the activity of pyramidal neurons\nin rat hippocampus, recorded while the animal was exploring a two-dimensional\nenvironment, and confirmed that our method is able to detect geometric\norganization using only the intrinsic pattern of neural correlations.\nRemarkably, we found similar results during non-spatial behaviors such as wheel\nrunning and REM sleep. This suggests that the geometric structure of\ncorrelations is shaped by the underlying hippocampal circuits, and is not\nmerely a consequence of position coding. We propose that clique topology is a\npowerful new tool for matrix analysis in biological settings, where the\nrelationship of observed quantities to more meaningful variables is often\nnonlinear and unknown.","url_abs":"http://arxiv.org/abs/1502.06172v1","url_pdf":"http://arxiv.org/pdf/1502.06172v1.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":"clique-topology-reveals-intrinsic-geometric","repo_url":"https://github.com/nebneuron/clique-top","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":null,"task_name":"Hippocampus"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1502.06172","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}