Identifying Task-Related Brain Functional States Via Cortical Networks

A long standing goal of neuroscience studies has been to understand how brain functions are related to behavior. In this paper, we investigate changes in brain functional networks under two behavioral conditions (lick (L) and no-lick (NL)) across two frequency bands. Cortical activity in Thy1-GCaMP6s transgenic calcium reporter mice is recorded during L/NL activity experiments using widefield calcium imaging. We demonstrate how cortical connectivity can be used to identify behavior-related brain states. Connectivity links that significantly contribute to the network difference of L and NL behavioral conditions are spatially localized in two frequency bands. The effectiveness of cortical networks in predicting L and NL behavior are assessed using commonly-used classifiers. Results demonstrate that frequency-dependent cortical network analysis can be utilized to decode the brain states associated with behavior.