Spontaneous network coupling enables efficient task performance without local task-induced activations

Abstract

AbstractNeurobehavioral studies in humans have long concentrated on changes in local activity levels during repetitive executions of a task. Spontaneous neural coupling within extended networks has latterly been found to also influence performance. Here, we intend to uncover the underlying mechanisms and the interaction with task-induced activations. We demonstrate that high performers in visual perception and motor sequence tasks present an absence of classical task-induced activations, but, instead, strong spontaneous network coupling. Activations were thus a compensation mechanism needed only in subjects with lower spontaneous network interactions. This challenges classical models of neural processing and calls for new strategies in attempts to train and enhance performance.