Causal Network Inference for Neural Ensemble Activity

Rong Chen
2021 Neuroinformatics  
AbstractInteractions among cellular components forming a mesoscopic scale brain network (microcircuit) display characteristic neural dynamics. Analysis of microcircuits provides a system-level understanding of the neurobiology of health and disease. Causal discovery aims to detect causal relationships among variables based on observational data. A key barrier in causal discovery is the high dimensionality of the variable space. A method called Causal Inference for Microcircuits (CAIM) is
more » ... d to reconstruct causal networks from calcium imaging or electrophysiology time series. CAIM combines neural recording, Bayesian network modeling, and neuron clustering. Validation experiments based on simulated data and a real-world reaching task dataset demonstrated that CAIM accurately revealed causal relationships among neural clusters.
doi:10.1007/s12021-020-09505-4 pmid:33393054 fatcat:6tstmuzygfgodeoniwcjcui2di