Keeping an Eye Out for Change: Anxiety Disrupts Adaptive Resolution of Policy Uncertainty

Human learning unfolds under uncertainty. Uncertainty is heterogeneous with different forms exerting distinct influences on learning. While one can be uncertain about what to do to maximize rewarding outcomes, known as policy uncertainty, one can also be uncertain about general world knowledge, known as epistemic uncertainty (EU). In complex and naturalistic environments such as the social world, adaptive learning may hinge on striking a balance between attending to and resolving each type of uncertainty. Prior work illustrates that people with anxiety-those with increased threat and uncertainty sensitivity-learn less from aversive outcomes, particularly as outcomes become more uncertain. How does a learner adaptively trade-off between attending to these distinct sources of uncertainty to successfully learn about their social environment?

We developed a novel eye-tracking method to capture highly granular estimates of policy uncertainty and EU based on gaze patterns and pupil diameter (a physiological estimate of arousal).

These empirically derived uncertainty measures revealed that humans (N = 94) flexibly switched between resolving policy uncertainty and EU to adaptively learn about which individuals can be trusted and which should be avoided. However, those with increased anxiety (n = 49) did not flexibly switch between resolving policy uncertainty and EU and instead expressed less uncertainty overall.

Combining modeling and eye-tracking techniques, we show that altered learning in people with anxiety emerged from an insensitivity to policy uncertainty and rigid choice policies, leading to maladaptive behaviors with untrustworthy people.