Random Recurrent Networks Near Criticality Capture the Broadband Power Distribution of Human ECoG Dynamics.

ABSTRACT: Brain electric field potentials are dominated by an arrhythmic broadband signal, but the underlying mechanism is poorly understood. Here we propose that broadband power spectra characterize recurrent neural networks of nodes (neurons or clusters of neurons), endowed with an effective balance between excitation and inhibition tuned to keep the network on the edge of dynamical instability. These networks show a fast mode reflecting local dynamics and a slow mode emerging from distributed recurrent connections. Together, the 2 modes produce power spectra similar to those observed in human intracranial EEG (i.e., electrocorticography, ECoG) recordings. Moreover, such networks convert spatial input correlations across nodes into temporal autocorrelation of network activity. Consequently, increa

SUBMITTER: Chaudhuri R 

PROVIDER: S-EPMC6132289 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature