State anxiety biases estimates of uncertainty and impairs reward learning in volatile environments

Hein, Thomas; De Fockert, J. W. and Herrojo Ruiz, Maria. 2021. State anxiety biases estimates of uncertainty and impairs reward learning in volatile environments. NeuroImage, 224, 117424. ISSN 1053-8119 [Article]

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Abstract or Description

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.

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The study was supported by Goldsmiths University of London, funded by the Economic and Social Research Council (ESRC) and the South East Network for Social Sciences (SeNSS) through grant ES/P00072X/1, and the National Research University Higher School of Economics, through the Basic Research Program and the Russian Academic Excellence Project ’5–100’.

Supplementary material associated with this article can be found, in
the online version, at doi:10.1016/j.neuroimage.2020.117424

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Anxiety, Uncertainty, Hierarchical Bayesian inference, Computational modeling, Precision-weighted prediction error, Single-trial EEG

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15 October 2019Submitted
29 September 2020Accepted
6 October 2020Published Online
1 January 2021Published

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Date Deposited:

14 May 2020 14:38

Last Modified:

10 Aug 2021 13:13

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Yes, this version has been peer-reviewed.


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