Localized Semi-Nonnegative Matrix Factorization (LocaNMF) of Widefield Calcium Imaging Data

Saxena, S., Kinsella, I., Musall, S., Kim, S.H., Meszaros, J., Thibodeaux, D.N., Kim, C., Cunningham, J., Hillman, E.M.C., Churchland, A., Paninski, L. (April 2020) Localized Semi-Nonnegative Matrix Factorization (LocaNMF) of Widefield Calcium Imaging Data. PLoS Comput Biol, 16 (4). e1007791. ISSN 1553-734x

URL: https://pubmed.ncbi.nlm.nih.gov/32282806
DOI: 10.1371/journal.pcbi.1007791


Widefield calcium imaging enables recording of large-scale neural activity across the mouse dorsal cortex. In order to examine the relationship of these neural signals to the resulting behavior, it is critical to demix the recordings into meaningful spatial and temporal components that can be mapped onto well-defined brain regions. However, no current tools satisfactorily extract the activity of the different brain regions in individual mice in a data-driven manner, while taking into account mouse-specific and preparation-specific differences. Here, we introduce Localized semi-Nonnegative Matrix Factorization (LocaNMF), a method that efficiently decomposes widefield video data and allows us to directly compare activity across multiple mice by outputting mouse-specific localized functional regions that are significantly more interpretable than more traditional decomposition techniques. Moreover, it provides a natural subspace to directly compare correlation maps and neural dynamics across different behaviors, mice, and experimental conditions, and enables identification of task- and movement-related brain regions.

Item Type: Paper
Subjects: organism description > animal behavior
organism description > animal behavior > decision making
Investigative techniques and equipment > imaging
CSHL Authors:
Communities: CSHL labs > Churchland lab
Depositing User: Adrian Gomez
Date: 13 April 2020
Date Deposited: 16 Apr 2020 18:26
Last Modified: 15 Sep 2020 20:00
PMCID: PMC7179949
Related URLs:
URI: https://repository.cshl.edu/id/eprint/39238

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