Characterization of Cortical Networks during Motor Tasks in Humans

Abstract

The present study proposes a theoretical graph approach in order to evaluate the functional connectivity patterns obtained from high-resolution EEG signals. In particular, we evaluated the dynamics of the cerebral networks during the preparation and the execution of the foot movement in healthy subjects. High-resolution EEG represents a novel technique that can estimate non-invasively the cortical activity from the standard scalp EEG measurements. Brain functional networks are obtained by the time-varying Partial Directed Coherence, which describes the time-frequency relationships between the signals of different cortical regions. The evaluation of the time-varying topology of the estimated networks is addressed by means of graph theory, which describes concisely the complexity of the interconnected cerebral system. Altogether, our findings reveal new insights about the time-frequency dynamics of the cortical networks involved throughout the performance of a simple foot movement.