Localized semi-nonnegative matrix factorization (LocaNMF) of widefield calcium imaging data

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...

Full description

Saved in:
Bibliographic Details
Published in:PLoS computational biology 2020-04, Vol.16 (4), p.e1007791-e1007791
Main Authors: Saxena, Shreya, Kinsella, Ian, Musall, Simon, Kim, Sharon H, Meszaros, Jozsef, Thibodeaux, David N, Kim, Carla, Cunningham, John, Hillman, Elizabeth M C, Churchland, Anne, Paninski, Liam
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Animals
Biology and Life Sciences
Biomedical engineering
Brain
Brain mapping
Brain Mapping - methods
Calcium
Calcium - chemistry
Calcium - metabolism
Calcium imaging
Cerebral cortex
Cortex (temporal)
Datasets
Decomposition
Engineering
Factorization
Funding
Image Processing, Computer-Assisted - methods
Laboratories
Medicine and Health Sciences
Methods
Mice
Neural circuitry
Neuroimaging
Neurons
Neurosciences
Physical Sciences
Physiological aspects
Prefrontal Cortex - chemistry
Prefrontal Cortex - diagnostic imaging
Social Sciences
Software
Supervision
Video data
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.1007791