{"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/a-restaurant-process-mixture-model-for","title":"A Restaurant Process Mixture Model for Connectivity Based Parcellation of the Cortex","arxiv_id":"1703.00981","date":"2017-03-02","proceeding":null,"authors":["Daniel Moyer","Boris A. Gutman","Neda Jahanshad","Paul M. Thompson"],"abstract":"One of the primary objectives of human brain mapping is the division of the\ncortical surface into functionally distinct regions, i.e. parcellation. While\nit is generally agreed that at macro-scale different regions of the cortex have\ndifferent functions, the exact number and configuration of these regions is not\nknown. Methods for the discovery of these regions are thus important,\nparticularly as the volume of available information grows. Towards this end, we\npresent a parcellation method based on a Bayesian non-parametric mixture model\nof cortical connectivity.","url_abs":"http://arxiv.org/abs/1703.00981v1","url_pdf":"http://arxiv.org/pdf/1703.00981v1.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":"a-restaurant-process-mixture-model-for","repo_url":"https://github.com/kristianeschenburg/ddCRP","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}