{"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/boundary-solution-based-on-rescaling-method","title":"Boundary solution based on rescaling method: recoup the first and second-order statistics of neuron network dynamics","arxiv_id":"2002.02381","date":"2020-01-31","proceeding":null,"authors":[],"abstract":"There is a strong nexus between the network size and the computational\nresources available, which may impede a neuroscience study. In the meantime,\nrescaling the network while maintaining its behavior is not a trivial mission.\nAdditionally, modeling patterns of connections under topographic organization\npresents an extra challenge: to solve the network boundaries or mingled with an\nunwished behavior. This behavior, for example, could be an inset oscillation\ndue to the torus solution; or a blend with/of unbalanced neurons due to a lack\n(or overdose) of connections. We detail the network rescaling method able to\nsustain behavior statistical utilized in Romaro et al. (2018) and present a\nboundary solution method based on the previous statistics recoup idea.","url_abs":"http://arxiv.org/abs/2002.02381v1","url_pdf":"http://arxiv.org/pdf/2002.02381v1.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":"boundary-solution-based-on-rescaling-method","repo_url":"https://github.com/ceciliaromaro/recoup-the-first-and-second-order-statistics-of-neuron-network-dynamics","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"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}