{"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/efficient-and-accurate-extraction-of-in-vivo","title":"Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data","arxiv_id":"1605.07266","date":"2016-05-24","proceeding":null,"authors":["Pengcheng Zhou","Shanna L. Resendez","Jose Rodriguez-Romaguera","Jessica C. Jimenez","Shay Q. Neufeld","Garret D. Stuber","Rene Hen","Mazen A. Kheirbek","Bernardo L. Sabatini","Robert E. Kass","Liam Paninski"],"abstract":"In vivo calcium imaging through microscopes has enabled deep brain imaging of\npreviously inaccessible neuronal populations within the brains of freely moving\nsubjects. However, microendoscopic data suffer from high levels of background\nfluorescence as well as an increased potential for overlapping neuronal\nsignals. Previous methods fail in identifying neurons and demixing their\ntemporal activity because the cellular signals are often submerged in the large\nfluctuating background. Here we develop an efficient method to extract cellular\nsignals with minimal influence from the background. We model the background\nwith two realistic components: (1) one models the constant baseline and slow\ntrends of each pixel, and (2) the other models the fast fluctuations from\nout-of-focus signals and is therefore constrained to have low spatial-frequency\nstructure. This decomposition avoids cellular signals being absorbed into the\nbackground term. After subtracting the background approximated with this model,\nwe use Constrained Nonnegative Matrix Factorization (CNMF, Pnevmatikakis et al.\n(2016)) to better demix neural signals and get their denoised and deconvolved\ntemporal activity. We validate our method on simulated and experimental data,\nwhere it shows fast, reliable, and high quality signal extraction under a wide\nvariety of imaging parameters.","url_abs":"http://arxiv.org/abs/1605.07266v2","url_pdf":"http://arxiv.org/pdf/1605.07266v2.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":"efficient-and-accurate-extraction-of-in-vivo","repo_url":"https://github.com/zhoupc/CNMF_E","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null},{"paper_slug":"efficient-and-accurate-extraction-of-in-vivo","repo_url":"https://github.com/Rack95/Caiman_edit","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"efficient-and-accurate-extraction-of-in-vivo","repo_url":"https://github.com/flatironinstitute/CaImAn","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"efficient-and-accurate-extraction-of-in-vivo","repo_url":"https://github.com/jw3132/p_CNMF_E","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"efficient-and-accurate-extraction-of-in-vivo","repo_url":"https://github.com/marburyvthesea/caiman_miniscope_analysis","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"efficient-and-accurate-extraction-of-in-vivo","repo_url":"https://github.com/marburyvthesea/caiman_quest","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"efficient-and-accurate-extraction-of-in-vivo","repo_url":"https://github.com/sebastiantiesmeyer/CaImAn","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"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}