Uncovering the organization of neural circuits with generalized phase locking analysis

Abstract

AbstractDespite the considerable progress of in vivo neural recording techniques, inferring the biophysical mechanisms underlying large scale coordination of brain activity from neural data remains challenging. One obstacle is the difficulty to link functional connectivity measures to mechanistic models of network activity. We address this question for the case of spike-field coupling, which quantifies the synchronization between neurophysiological activities observed at two different scales: on the one hand, the action potential produced by neurons, on the other hand a mesoscopic “field” signal, reflecting subthreshold activities. We develop Generalized Phase Locking Analysis (GPLA) as a multichannel extension of univariate spike-field coupling that can be interpreted based on neural field models of mesoscopic network activity. GPLA estimates the dominant spatio-temporal distributions of field activity and neural ensembles, and the strength of the coupling between them. We demonstrate the statistical benefits and interpretability of this approach in various biophysical neuronal network models and Utah array recordings. In particular, GPLA, uncovers the contribution of recurrent microcircuits to the spatio-temporal dynamics observed in multi-channel recordings.