Toward a Functional Characterization of Cognitive Control Networks
Abstract
Cognitive control is an executive process that has been associated with a distributed set of cortical regions. These distributed regions appear to cluster into distinct networks with dissociable functions. In this study, independent component analysis was used as a tool to investigate functional connectivity in event-related fMRI data. Extracted networks of interest were functionally characterized using a hybrid task that independently probed moment-to-moment adjustments in control, and stable task-set maintenance. A cinguloinsular network was implicated in the processing of moment-to-moment adjustments in control based on its activation patterns during this task. Subsequently, functional connectivity between two networks previously implicated in control, two default mode networks, and a visual network were investigated overall, and in specific condition windows. Findings from this study emphasize the utility of independent component analysis in directly functionally characterizing dissociable cognitive control networks.