Title
Detecting cell assemblies by NMF-based clustering from calcium imaging data
Abstract
A large number of neurons form cell assemblies that process information in the brain. Recent developments in measurement technology, one of which is calcium imaging, have made it possible to study cell assemblies. In this study, we aim to extract cell assemblies from calcium imaging data. We propose a clustering approach based on non-negative matrix factorization (NMF). The proposed approach first obtains a similarity matrix between neurons by NMF and then performs spectral clustering on it. The application of NMF entails the problem of model selection. The number of bases in NMF affects the result considerably, and a suitable selection method is yet to be established. We attempt to resolve this problem by model averaging with a newly defined estimator based on NMF. Experiments on simulated data suggest that the proposed approach is superior to conventional correlation-based clustering methods over a wide range of sampling rates. We also analyzed calcium imaging data of sleeping/waking mice and the results suggest that the size of the cell assembly depends on the degree and spatial extent of slow wave generation in the cerebral cortex.
Year
DOI
Venue
2022
10.1016/j.neunet.2022.01.023
Neural Networks
Keywords
DocType
Volume
Calcium imaging,Clustering,NMF
Journal
149
Issue
ISSN
Citations 
1
0893-6080
0
PageRank 
References 
Authors
0.34
1
8
Name
Order
Citations
PageRank
Mizuo Nagayama100.34
Toshimitsu Aritake200.34
Hideitsu Hino39925.73
Takeshi Kanda400.34
Takehiro Miyazaki500.34
Masashi Yanagisawa600.34
Shotaro Akaho765079.46
Noboru Murata8855170.36