Anxious individuals have difficulty learning the causal statistics of aversive environments.
Anxious individuals have difficulty learning the causal statistics of aversive environments.
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DOI：
10.1038/nn.3961
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发表时间：
2015-04
影响因子：
25
通讯作者：
Bishop SJ
中科院分区：
文献类型：
--
作者：
Browning M;Behrens TE;Jocham G;O'Reilly JX;Bishop SJ
环境因果结构中的统计分析使我们能够预测我们行为的可能结果。行动结果或有事项的稳定或波动程度因环境而异。难以使用这些信息来最佳地更新结果预测可能会导致焦虑中的决策困难。我们使用一个操纵环境波动性的厌恶学习任务来测试这一点。低特质焦虑的人类参与者将其结果预测的更新与当前环境的波动相匹配，正如贝叶斯模型所预测的那样。高特质焦虑的人表现出较低的能力，以调整更新的结果预期之间的稳定和动荡的环境。这与瞳孔扩张反应对波动性的敏感性降低有关，可能表明去甲肾上腺素能对这方面环境信息变化的反应性改变。
Statistical regularities in the causal structure of the environment enable us to predict the probable outcomes of our actions. Environments differ in the extent to which action-outcome contingencies are stable or volatile. Difficulty in being able to use this information to optimally update outcome predictions might contribute to the decision-making difficulties seen in anxiety. We tested this using an aversive learning task manipulating environmental volatility. Low trait anxious human participants matched updating of their outcome predictions to the volatility of the current environment, as predicted by a Bayesian model. High trait anxious individuals showed less ability to adjust updating of outcome expectancies between stable and volatile environments. This was linked to reduced sensitivity of the pupil dilatory response to volatility, potentially indicative of altered norepinephrinergic responsivity to changes in this aspect of environmental information.