Ensemble dynamics and information flow deduction from whole-brain imaging data.

ABSTRACT: The recent advancements in large-scale activity imaging of neuronal ensembles offer valuable opportunities to comprehend the process involved in generating brain activity patterns and understanding how information is transmitted between neurons or neuronal ensembles. However, existing methodologies for extracting the underlying properties that generate overall dynamics are still limited. In this study, we applied previously unexplored methodologies to analyze time-lapse 3D imaging (4D imaging) data of head neurons of the nematode Caenorhabditis elegans. By combining time-delay embedding with the independent component analysis, we successfully decomposed whole-brain activities into a small number of component dynamics. Through the integration of results from multiple samples, we extracted c

SUBMITTER: Toyoshima Y 

PROVIDER: S-EPMC10942262 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature