{"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/estimation-of-neuronal-interaction-graph-from","title":"Estimation of neuronal interaction graph from spike train data","arxiv_id":"1612.05226","date":"2017-10-11","proceeding":null,"authors":[],"abstract":"One of the main current issues in Neurobiology concerns the understanding of\ninterrelated spiking activity among multineuronal ensembles and differences\nbetween stimulus-driven and spontaneous activity in neurophysiological\nexperiments. Multi electrode array recordings that are now commonly used\nmonitor neuronal activity in the form of spike trains from many well identified\nneurons. A basic question when analyzing such data is the identification of the\ndirected graph describing \"synaptic coupling\" between neurons. In this article\nwe deal with this matter working with a high quality multielectrode array\nrecording dataset (Pouzat et al., 2015) from the first olfactory relay of the\nlocust, $Schistocerca$ $americana$. From a mathematical point of view this\npaper presents two novelties. First we propose a procedure allowing to deal\nwith the small sample sizes met in actual datasets. Moreover we address the\nsensitive case of partially observed networks. Our starting point is the\nprocedure introduced in Duarte et al. (2016). We evaluate the performance of\nboth original and improved procedures through simulation studies, which are\nalso used for parameter tuning and for exploring the effect of recording only a\nsmall subset of the neurons of a network.","url_abs":"http://arxiv.org/abs/1612.05226v2","url_pdf":"http://arxiv.org/pdf/1612.05226v2.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":"estimation-of-neuronal-interaction-graph-from","repo_url":"https://github.com/lbrochini/Graph-Estimation","is_official":1,"mentioned_in_paper":1,"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}