Abstract

In this paper we propose the use of a time-varying multivariate estimator based on the partial directed coherence (PDC), a frequency-domain estimator able to describe interactions between cortical areas in terms of the concept of Granger causality. Time-varying PDC was obtained by the adaptive recursive fit of an MVAR model with time-dependent parameters, by means of a generalized recursive least-square (RLS) algorithm, taking into consideration a set of EEG epochs. Such estimator is able to follow rapid changes in the connectivity between cortical areas during an experimental task. We provide an application to the cortical estimations obtained from high resolution EEG data, recorded from a group of healthy subject during a combined foot-lips movement, and from a patient with spinal cord injury during the attempt to move the paralysed limb. Normal subjects and the SCI patient exhibit similar cortical networks, although certain differences between the time evolution of connectivity strengths between the primary foot and lips areas arose.

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