Abstract

Clinical and subclinical (trait) anxiety impairs decision making and interferes with learning. Less understood are the effects of temporary anxious states on learning and decision making in healthy populations, and whether these can serve as a model for clinical anxiety. Here we test whether anxious states in healthy individuals elicit a pattern of aberrant behavioural, neural, and physiological responses comparable with those found in anxiety disorders—particularly when processing uncertainty in unstable environments. In our study, both a state anxious and a control group learned probabilistic stimulus-outcome mappings in a volatile task environment while we recorded their electrophysiological (EEG) signals. By using a hierarchical Bayesian model of inference and learning, we assessed the effect of state anxiety on Bayesian belief updating with a focus on uncertainty estimates. State anxiety was associated with an underestimation of environmental uncertainty, and informational uncertainty about the reward tendency. Anxious individuals’ beliefs about reward contingencies were more precise (had smaller uncertainty) and thus more resistant to updating, ultimately leading to impaired reward-based learning. State anxiety was also associated with greater uncertainty about volatility. We interpret this pattern as evidence that state anxious individuals are less tolerant to informational uncertainty about the contingencies governing their environment and more willing to be uncertain about the level of stability of the world itself. Further, we tracked the neural representation of belief update signals in the trial-by-trial EEG amplitudes. In control participants, lower-level precision-weighted prediction errors (pwPEs) about reward tendencies were represented in the ERP signals across central and parietal electrodes peaking at 496 ms, overlapping with the late P300 in classical ERP analysis. The state anxiety group did not exhibit a significant representation of low-level pwPEs, and there were no significant differences between the groups. Smaller variance in low-level pwPE about reward tendencies in state anxiety could partially account for the null results. Expanding previous computational work on trait anxiety, our findings establish that temporary anxious states in healthy individuals impair reward-based learning in volatile environments, primarily through changes in uncertainty estimates, which play a central role in current Bayesian accounts of perceptual inference and learning.

Highlights

  • Anxiety is characterised by excessive worry about negative possibilities (Grupe and Nitschke, 2013)

  • Our key finding is that state anxiety was associated with a reduced estimate of tonic volatility, which resulted in an overall lower learning rate, and corresponded to a significant underestimation of environmental and informational uncertainty

  • We found that precision-weighted prediction error (PE) about the stimulus-reward contingency explained trial-wise modulation of observed event-related potential (ERP) responses in control participants only

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Summary

Introduction

Anxiety is characterised by excessive worry about negative possibilities (Grupe and Nitschke, 2013). It can lead to distinct difficulties when making decisions and learning about the world, as anxious individuals experience negative reactions to uncertainty—known as intolerance of uncertainty (IU; Bishop, 2007; Carleton, 2016). Identifying the computations that subserve learning under state anxiety is important due to the prevalence of highly anxious states in most real-world environments that are filled with uncertainty (Bach et al, 2011; Bishop and Gagne, 2018). These insights could expand our understanding of the mechanisms by which anxiety biases beliefs about the world, linking to anxiety-related disorders

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