{"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/quantifying-the-behavioral-dynamics-of-c","title":"Quantifying the behavioral dynamics of C. elegans with autoregressive hidden Markov models","arxiv_id":null,"date":"2017-12-01","proceeding":null,"authors":["E. Kelly Buchanan","Akiva Lipshitz","Scott Linderman","Liam Paninski"],"abstract":"In order to fully understand the neural activity of Caenorhabditis elegans, we need a rich, quantitative description of the behavioral outputs it gives rise to. To this end, we quantify the behavioral dynamics of the worm with autoregressive\r\nhidden Markov models (AR-HMMs), a class of models that has recently yielded some insight into mouse behavior [1]. These models explicitly encode three hypotheses: (i) while the instantaneous posture of the worm is represented as a high-dimensional vector of points along the body, the first four principal components, or eigenworms, capture a significant fraction of the postural variance; (ii) within this four dimensional space, the postural dynamics are well-approximated with linear autoregressive models; and (iii) the linear autoregressive model switches over time as the worm transitions between different discrete behaviors, like forward crawling, reverse crawling, pausing, and turning. We show how AR-HMMs segment recordings of freely crawling C. elegans into meaningful discrete behaviors, providing a quantitative description of postural dynamics and a rigorous framework\r\nfor assessing, comparing, and simulating worm behavior.","url_abs":"https://docs.google.com/viewer?a=v&pid=sites&srcid=ZGVmYXVsdGRvbWFpbnx3d25pcDIwMTd8Z3g6NzI5M2EyMTZjZDEzZTE2Mw","url_pdf":"https://docs.google.com/viewer?a=v&pid=sites&srcid=ZGVmYXVsdGRvbWFpbnx3d25pcDIwMTd8Z3g6NzI5M2EyMTZjZDEzZTE2Mw","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":"quantifying-the-behavioral-dynamics-of-c","repo_url":"https://github.com/ekellbuch/arhmm-celegans","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"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}