Abstract
Decision-making under uncertainty commonly entails the accumulation of decision-relevant ‘evidence’ over time. In natural environments, this accumulation process is complicated by the existence of hidden changes in the state of the environment. Optimal behavior in such contexts requires a rapid, non-linear tuning of the evidence accumulation. The neural basis of this adaptive computation has remained elusive. Here, we unraveled the underlying mechanisms across sensory, associative, and motor regions of the human cerebral cortex. We combined a visuo-motor choice task with hidden changes in the evidence source, monitoring of pupil-linked arousal, and model-based analysis of behavior and cortical population activity (assessed with magnetoencephalography). We found that normative, non-linear evidence accumulation results from the interplay of recurrent cortical dynamics and phasic arousal signals from ascending brainstem systems. Our insights forge a strong connection between normative computations for adaptive decision-making and the large-scale neural mechanisms for their implementation.
