Abstract
Understanding the statistical structure of the environment is crucial for adaptive behavior. Humans and non-human decision-makers seem to track such structure through a process of probabilistic inference, which enables predictions about behaviorally relevant events. Deviations from such predictions cause surprise, which in turn helps improve the inference. Surprise about the timing of behaviorally relevant sensory events drives phasic responses of neuromodulatory brainstem systems, which project to the cerebral cortex. Here, we developed a computational model-based magnetoencephalography (MEG) approach for mapping the resulting cortical transients across space, time, and frequency, in the human brain. We used a Bayesian updating model to estimate the predicted timing of the next stimulus change in a simple visual detection task. This model yielded quantitative trial-by-trial estimates of temporal surprise. The model-based surprise variable predicted trial-by-trial variations in reaction time more strongly than the externally observable interval timings alone. Trial-by-trial variations in surprise were negatively correlated with the power of cortical population activity measured with MEG. This surprise-related power suppression occurred transiently around the behavioral response, specifically in the beta frequency band. It peaked in left lateral prefrontal as well as in frontal midline regions, and its cortical distribution was distinct from the movement-related suppression of beta power in motor cortex. Our results indicate that surprise about sensory event timing transiently suppresses ongoing beta-band oscillations in association cortex. This transient suppression of frontal beta-band oscillations might reflect an active reset triggered by surprise, and is in line with the idea that beta-oscillations help maintain cognitive sets.
Significance statement Agents continuously track the statistical structure of the environment, in order to make predictions about behaviorally relevant sensory events. Deviations from such predictions cause surprise, which in turn drives phasic responses of neuromodulatory brainstem systems that project to the cerebral cortex. We developed a computational model-based magnetoencephalography approach, which enabled us to map out transients changes in cortical population dynamics elicited by surprise about sensory event timing, across space, time, and frequency, in the human brain. The model-based estimates of surprise predicted behavior as well as a transient suppression of beta frequency-band oscillations in frontal cortical regions. Our results are in line with conceptual accounts that have linked neural oscillations in the beta-band to the maintenance of cognitive sets.
Footnotes
Conflict of Interest: The authors declare no competing financial interests.