Cortical functional network organization from autoregressive modeling of local field potential oscillations

Abstract

A framework is presented for quantifying functional network organization in the brain by spectral analysis based on autoregressive modeling. Local field potentials (LFPs), simultaneously recorded from distributed sites in the cerebral cortex of monkeys, are treated as signals generated by local neuronal assemblies. During the delay period of a visual pattern discrimination task, oscillatory assembly activity is manifested in the LFPs in the beta-frequency range (14-30 Hz). Coherence analysis has shown that these oscillations are phase synchronized in functional networks in the sensorimotor cortex in relation to maintenance of contralateral hand position, and in the visual cortex in relation to anticipation of the visual stimulus. Granger causality analysis has revealed information flow in the sensorimotor network that is consistent with a peripheral sensorimotor feedback loop, and in the visual network that is consistent with top-down anticipatory modulation of assemblies in the primary visual cortex.