Oscillatory coupling reveals the dynamic reorganization of large-scale neural networks as cognitive demands change

Cognitive operations are thought to emerge from dynamic interactions between spatially distinct brain areas. Synchronization of oscillations has been proposed to regulate these interactions, but we do not know whether this large-scale synchronization can respond rapidly to changing cognitive demands. Here we show that, as task demands change during a trial, multiple distinct networks are dynamically formed and reformed via oscillatory synchronization. Distinct frequency-coupled networks were rapidly formed to process reward value, maintain information in visual working memory, and deploy visual attention. Strong single-trial correlations showed that networks formed even before the presentation of imperative stimuli could predict the strength of subsequent networks, as well as the speed and accuracy of behavioral responses seconds later. These frequency-coupled networks better predicted single-trial behavior than either local oscillations or ERPs. Our findings demonstrate the rapid reorganization of networks formed by dynamic activity in response to changing task demands within a trial.