State anxiety alters the neural oscillatory correlates of predictions and prediction errors during reward learning
State anxiety alters the neural oscillatory correlates of predictions and prediction errors during reward learning
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状态焦虑改变奖励学习期间预测和预测错误的神经振荡相关性
DOI：
10.1101/2021.03.08.434415
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Hein T
中科院分区：
文献类型：
--
作者：
Hein T
焦虑会影响大脑对不确定性的估计和反应。这些行为影响已经在预测编码和贝叶斯推理框架中得到了描述，但相关的神经关联仍不清楚。最近的研究表明，感知的生成模型中的预测是以α-β振荡(8-30赫兹)表示的，而预测的更新是由按精度加权的预测误差(逆方差；pwPE)和以伽马振荡(>；30赫兹)编码的预测误差驱动的。我们测试了状态焦虑是否改变了学习过程中与预测和pwPE相关的神经振荡活动。健康的人类参与者在不稳定的环境中完成了一项概率奖励学习任务。在我们之前的工作中，我们使用分层贝叶斯模型描述了这项任务中的学习行为，揭示了关于状态焦虑中的奖励倾向的更准确(有偏见)的信念，这与这一组中学习的减少一致。该模型为当前的研究提供了预测和pwPE的轨迹，使我们能够评估它们对脑电数据的时频表示的参数影响。使用振荡反应的卷积模型，我们发现，与对照组相比，状态焦虑在处理pwPE过程中增加了额叶和感觉运动区的α-β活性，在编码预测时增加了额顶区的α-β活性。未发现状态焦虑对伽马调制的影响。我们的发现将先前关于预测和PwPE的振荡表征的证据扩展到奖励学习领域。结果表明，状态焦虑在生成模型中调节pwPE和预测的振荡相关，为解释有偏见的信念更新和较差的奖励学习的潜在机制提供了见解。意义陈述学习在临床和亚临床焦虑中发挥核心作用。这项研究测试了在健康的人类参与者中暂时诱导的焦虑状态是否会改变与预测和从奖励中学习相关的神经振荡模式。我们发现，精确度加权的预测误差与我们状态焦虑组中α-β振荡的增加有关。这一发现表明，焦虑状态可能会抑制相关信号的编码，这些信号传达了预测的奖励和观察到的奖励之间的差异。在处理预测的过程中，状态焦虑也增加了α-β活性，表明对先前关于奖励倾向的信念有更强的依赖。结果发现，α-β振荡的改变是解释焦虑中的不确定性和不适应学习的错误估计的候选机制。
Anxiety influences how the brain estimates and responds to uncertainty. These behavioural effects have been described within predictive coding and Bayesian inference frameworks, yet the associated neural correlates remain unclear. Recent work suggests that predictions in generative models of perception are represented in alpha-beta oscillations (8-30 Hz), while updates to predictions are driven by prediction errors weighted by precision (inverse variance; pwPE) and encoded in gamma oscillations (>30 Hz). We tested whether state anxiety alters the neural oscillatory activity associated with predictions and pwPE during learning. Healthy human participants performed a probabilistic reward-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 reward tendency 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 alpha-beta activity in frontal and sensorimotor regions during processing pwPE, and in fronto-parietal regions during encoding 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-learning domain. The results suggest that state anxiety modulates oscillatory correlates of pwPE and predictions in generative models, providing insights into a potential mechanism explaining biased belief updating and poorer reward learning.Significance StatementLearning plays a central role in clinical and subclinical anxiety. This study tests whether a temporarily-induced state of anxiety in healthy human participants alters the neural oscillatory patterns associated with predicting and learning from rewards. We found that precision-weighted prediction errors were associated with increases in alpha-beta oscillations in our state anxious group. This finding suggested that anxiety states may inhibit encoding of relevant signals conveying the discrepancy between the predicted and observed reward. State anxiety also increased alpha-beta activity during processing predictions, indicating a stronger reliance on prior beliefs about the reward tendency. The results identify the alteration in alpha-beta oscillations as a candidate mechanism explaining misestimation of uncertainty and maladaptive learning in anxiety.
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影响因子：
4.3
作者：
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影响因子：
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作者：
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影响因子：
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作者：
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影响因子：
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作者：
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DOI：
--
发表时间：
2020
期刊：
Psychology Science
影响因子：
--
作者：
A. Lamba;M. Frank;Oriel FeldmanHall
通讯作者：
Oriel FeldmanHall