Temporal dynamics of information flow in the cerebral cortex

Abstract

The nature of information flow from one area of the cerebral cortex to another is poorly understood. Frequency-dependent measures of information flow, based on multivariate autoregressive modeling of field potential time series, have shown promise for understanding information transactions between cortical areas (Liang et al., Neuro Report, 11 (2000) 2875–2880). In the present contribution, a time domain measure of information flow between two areas, called the directed transinformation (DTI), is described and applied to investigate causal influences directly from the field potential time series. We show that the DTI, as a generalization of mutual information, can be measured in a rather natural way, such that the interdependence of two time series is the sum of flow from X to Y, flow from Y to X, and instantaneous flow. We demonstrate the usefulness of this technique on both simulated data and multichannel local field potentials from macaque monkeys. Comparison with the frequency-dependent measure is also made.