Goldsmiths, University of London, Psychology Department, Whitehead Building, New Cross, London, SE146NW, United Kingdom.
Goldsmiths, University of London, Psychology Department, Whitehead Building, New Cross, London, SE146NW, United Kingdom; Center for Cognition and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russian Federation.
Neuroimage. 2021 Jan 1;224:117424. doi: 10.1016/j.neuroimage.2020.117424. Epub 2020 Oct 6.
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.
临床和亚临床（特质）焦虑会损害决策能力并干扰学习。人们对健康人群中暂时性焦虑状态对学习和决策的影响知之甚少，也不知道这些是否可以作为临床焦虑的模型。在这里，我们测试了健康个体的焦虑状态是否会引起行为、神经和生理反应的异常模式，这种模式与焦虑障碍中的反应模式类似——尤其是在不稳定环境中处理不确定性时。在我们的研究中，状态焦虑组和对照组在一个不稳定的任务环境中学习概率刺激-结果映射，同时记录他们的脑电图（EEG）信号。通过使用推理和学习的分层贝叶斯模型，我们评估了状态焦虑对贝叶斯信念更新的影响，重点关注不确定性估计。状态焦虑与对环境不确定性的低估以及对奖励倾向的信息不确定性有关。焦虑个体对奖励规律的信念更准确（不确定性更小），因此更难更新，最终导致基于奖励的学习受损。状态焦虑也与对波动性的不确定性增加有关。我们将这种模式解释为状态焦虑个体对环境中控制其环境的规律的信息不确定性的容忍度较低，并且更愿意对世界本身的稳定性水平不确定的证据。此外，我们在逐试 EEG 幅度中跟踪了信念更新信号的神经表示。在对照组参与者中，关于奖励倾向的较低水平的精确加权预测误差（pwPE）在 ERP 信号中以中央和顶叶电极为代表，在 496ms 时达到峰值，与经典 ERP 分析中的晚期 P300 重叠。状态焦虑组没有表现出低水平 pwPE 的显著表示，并且两组之间没有显著差异。状态焦虑中关于奖励倾向的低水平 pwPE 的方差较小，这可能部分解释了无效结果。扩展了特质焦虑的先前计算工作，我们的发现表明，健康个体的暂时性焦虑状态会在不稳定的环境中损害基于奖励的学习，主要是通过不确定性估计的变化，这在当前的贝叶斯感知推理和学习模型中起着核心作用。
