The detection of cognitive state transitions by stability changes in event-related cortical field potentials

Cognitive tasks are characterized by sequences of stable states, which are thought to reflect distinct steps of neurocognitive processing. Here, we in vestigate a stability measure, derived from adaptive multivariate autoregre ssive (AMVAR) modeling of cortical field potentials, as an index for relati ng changes in large-scale neural activity to changes in cognitive state. We show that this stability measure can be used to decide the optimal window length for AMVAR modeling and to detect state transitions related to extern al sensory or motor events. By using this approach, we demonstrate clear di fferentiation of GO and NO-GO processes in a macaque monkey performing a vi suomotor pattern discrimination task. Moreover, we are able to identify reg ional differences in state transitions, apparently reflecting regional info rmation processing differences. (C) 2001 Elsevier Science B.V. All rights r eserved.