PT  - JOURNAL ARTICLE
AU  - Shreya Saxena
AU  - Ian Kinsella
AU  - Simon Musall
AU  - Sharon H. Kim
AU  - Jozsef Meszaros
AU  - David N. Thibodeaux
AU  - Carla Kim
AU  - John Cunningham
AU  - Elizabeth Hillman
AU  - Anne Churchland
AU  - Liam Paninski
TI  - Localized semi-nonnegative matrix factorization (LocaNMF) of widefield calcium imaging data
AID  - 10.1101/650093
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 650093
4099  - http://biorxiv.org/content/early/2019/05/25/650093.short
4100  - http://biorxiv.org/content/early/2019/05/25/650093.full
AB  - 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 helpful 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), 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.