Increased and biased deliberation in social anxiety.

Increased and biased deliberation in social anxiety.
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DOI:
10.1038/s41562-021-01180-y
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发表时间:
2022-01
影响因子:
29.9
通讯作者:
Daw, Nathaniel D.
Daw, Nathaniel D.
中科院分区:
心理学1区
文献类型:
--
作者:
Hunter, Lindsay E.;Meer, Elana A.;Gillan, Claire M.;Hsu, Ming;Daw, Nathaniel D.

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计算精神病学的一个目标是将症状建立在更基本的计算机制中。理论表明,情绪障碍中的沉思和其他症状反映了心理模拟失调,这一过程通常用于评估候选人的行为。如果是这样,这些隐性症状应该会产生明显的后果:过度深思熟虑的选择,特别是与沉思内容相关的选择。在两个大型普通人群样本中,我们研究了社交焦虑症 (SAD) 的症状如何预测社交框架强化学习任务(专利竞赛游戏)中的选择。使用计算学习模型来评估学习策略,我们发现自我报告的社交焦虑确实与慎重评估的增加有关。这种效应是从反馈的特定(“向上反事实”)子集中学习所特有的,大致与季节性情绪失调中沉思的偏见内容相匹配。它对于控制其他精神症状也很有效。这些结果将 SAD 的症状(例如社交互动中的过度思考和瘫痪)纳入了明确的神经计算机制中,并提供了疾病功能增强的罕见例子。
A goal of computational psychiatry is to ground symptoms in more fundamental computational mechanisms. Theory suggests that rumination and other symptoms in mood disorders reflect dysregulated mental simulation, a process that normally serves to evaluate candidate actions. If so, these covert symptoms should have observable consequences: excessively deliberative choices, specifically about options related to the content of rumination. In two large general population samples, we examined how symptoms of social anxiety disorder (SAD) predict choices in a socially framed reinforcement learning task, the Patent Race game. Using a computational learning model to assess learning strategy, we found that self-reported social anxiety was indeed associated with an increase in deliberative evaluation. The effect was specific to learning from a particular (“upward counterfactual”) subset of feedback, broadly matching the biased content of rumination in SAD. It was also robust to controlling for other psychiatric symptoms. These results ground the symptoms of SAD, such as overthinking and paralysis in social interactions, in well characterized neuro-computational mechanisms and offer a rare example of enhanced function in disease.
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