How Uncertain Are You? Disentangling Expected and Unexpected Uncertainty in Pupil-linked Brain Arousal During Reversal Learning

During decision making, we are continuously faced with two sources of uncertainty regarding the links between stimuli, our actions, and outcomes. On the one hand, our expectations are often probabilistic, that is, stimuli or actions yield the expected outcome only with a certain probability (expected uncertainty). On the other hand, expectations might become invalid due to sudden, unexpected changes in the environment (unexpected uncertainty). Several lines of research show that pupil-linked brain arousal is a sensitive indirect measure of brain mechanisms underlying uncertainty computations. Thus, we investigated whether it is involved in disentangling these two forms of uncertainty. To this aim, we measured pupil size during a probabilistic reversal learning task. In this task, participants had to figure out which of two response options led to reward with higher probability, whereby sometimes the identity of the more advantageous response option was switched. Expected uncertainty was manipulated by varying the reward probability of the advantageous choice option, whereas the level of unexpected uncertainty was assessed by using a Bayesian computational model estimating change probability and resulting uncertainty. We found that both aspects of unexpected uncertainty influenced pupil responses, confirming that pupil-linked brain arousal is involved in model updating after unexpected changes in the environment. Furthermore, high level of expected uncertainty impeded the detection of sudden changes in the environment, both on physiological and behavioral level. These results emphasize the role of pupil-linked brain arousal and underlying neural structures in handling situations in which the previously established contingencies are no longer valid.