WormTensor: a clustering method for time-series whole-brain activity data from C. elegans.

ABSTRACT:

Background

In the field of neuroscience, neural modules and circuits that control biological functions have been found throughout entire neural networks. Correlations in neural activity can be used to identify such neural modules. Recent technological advances enable us to measure whole-brain neural activity with single-cell resolution in several species including [Formula: see text]. Because current neural activity data in C. elegans contain many missing data points, it is necessary to merge results from as many animals as possible to obtain more reliable functional modules.

Results

In this work, we developed a new time-series clustering method, WormTensor, to identify functional modules using whole-brain activity data from C. elegans. WormTensor uses a distance measure, mo

SUBMITTER: Tsuyuzaki K 

PROVIDER: S-EPMC10273573 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature