How cognitive task information emerges from brain activity is a central question in neuroscience. We identified the spatiotemporal emergence of task information in the human brain using individualized source electroencephalography and dynamic multivariate pattern analysis. We then substantially extended recently developed brain activity flow models to predict the future emergence of task information dynamics. The model simulated the flow of task-evoked activity over causally interpretable resting-state functional connections (dynamic, lagged, direct and directional) to accurately predict response information dynamics underlying cognitive task behavior. Predicting event-related spatiotemporal activity patterns and fine-grained representational geometry confirmed the model’s faithfulness to how the brain veridically represents response information. Simulated network "lesioning" revealed cognitive control networks (CCNs) as the dominant causal drivers of response information flow. These results demonstrate the efficacy of dynamic activity flow models in predicting the emergence of task information, thereby revealing a mechanistic role for CCNs in producing behavior.
bioRxiv Subject Collection: Neuroscience