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Elife DOI:10.7554/eLife.28728

Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data.

Publication TypeJournal Article
Year of Publication2018
AuthorsZhou, P, Resendez, SL, Rodriguez-Romaguera, J, Jimenez, JC, Neufeld, SQ, Giovannucci, A, Friedrich, J, Pnevmatikakis, EA, Stuber, GD, Hen, R, Kheirbek, MA, Sabatini, BL, Kass, RE, Paninski, L
Date Published2018 02 22

In vivo calcium imaging through microendoscopic lenses enables imaging of previously inaccessible neuronal populations deep within the brains of freely moving animals. However, it is computationally challenging to extract single-neuronal activity from microendoscopic data, because of the very large background fluctuations and high spatial overlaps intrinsic to this recording modality. Here, we describe a new constrained matrix factorization approach to accurately separate the background and then demix and denoise the neuronal signals of interest. We compared the proposed method against previous independent components analysis and constrained nonnegative matrix factorization approaches. On both simulated and experimental data recorded from mice, our method substantially improved the quality of extracted cellular signals and detected more well-isolated neural signals, especially in noisy data regimes. These advances can in turn significantly enhance the statistical power of downstream analyses, and ultimately improve scientific conclusions derived from microendoscopic data.


Alternate JournalElife
PubMed ID29469809
PubMed Central IDPMC5871355
Grant ListR01 EB022913 / EB / NIBIB NIH HHS / United States
R01 MH064537 / MH / NIMH NIH HHS / United States
R01 MH108623 / MH / NIMH NIH HHS / United States
R01 MH111754 / MH / NIMH NIH HHS / United States
/ HHMI / Howard Hughes Medical Institute / United States
/ / CIHR / Canada