State anxiety alters the neural oscillatory correlates of predictions and prediction errors during reward-based learning

Hein, Thomas and Herrojo Ruiz, Maria. 2022. State anxiety alters the neural oscillatory correlates of predictions and prediction errors during reward-based learning. Neuroimage, 249, 118895. ISSN 1053-8119 [Article]

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Abstract or Description

Anxiety influences how the brain estimates and responds to uncertainty. The consequences of these processes on behaviour have been described in theoretical and empirical studies, yet the associated neural correlates remain unclear. Rhythm-based accounts of Bayesian predictive coding propose that predictions in generative models of perception are represented in alpha (8–12 Hz) and beta oscillations (13–30 Hz). Updates to predictions are driven by prediction errors weighted by precision (inverse variance), and are encoded in gamma oscillations (>30 Hz) and associated with suppression of beta activity. We tested whether state anxiety alters the neural oscillatory activity associated with predictions and precision-weighted prediction errors (pwPE) during learning. Healthy human participants performed a probabilistic reward-based learning task in a volatile environment. In our previous work, we described learning behaviour in this task using a hierarchical Bayesian model, revealing more precise (biased) beliefs about the tendency of the reward contingency in state anxiety, consistent with reduced learning in this group. The model provided trajectories of predictions and pwPEs for the current study, allowing us to assess their parametric effects on the time-frequency representations of EEG data. Using convolution modelling for oscillatory responses, we found that, relative to a control group, state anxiety increased beta activity in frontal and sensorimotor regions during processing of pwPE, and in fronto-parietal regions during encoding of predictions. No effects of state anxiety on gamma modulation were found. Our findings expand prior evidence on the oscillatory representations of predictions and pwPEs into the reward-based learning domain. The results suggest that state anxiety modulates beta-band oscillatory correlates of pwPE and predictions in generative models, providing insights into the neural processes associated with biased belief updating and poorer learning.

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Anxiety, Predictive coding, Oscillations, EEG, Convolution, Uncertainty

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15 March 2021Submitted
8 January 2022Accepted
10 January 2022Published Online
April 2022Published

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Date Deposited:

07 Jan 2022 12:07

Last Modified:

31 Jan 2022 13:45

Peer Reviewed:

Yes, this version has been peer-reviewed.


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