Impaired adaptation of learning to contingency volatility in internalizing psychopathology.
Impaired adaptation of learning to contingency volatility in internalizing psychopathology.
复制标题
内在化精神病理学中学习对偶然波动的适应性受损。
DOI：
10.7554/elife.61387
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发表时间：
2020-12-22
期刊：
影响因子：
7.7
通讯作者：
Bishop SJ
中科院分区：
文献类型：
--
作者：
Gagne C;Zika O;Dayan P;Bishop SJ
使用权变波动操纵，我们测试的假设，难以适应二阶不确定性的概率决策可能反映了一个核心赤字，削减焦虑和抑郁，并持有无论结果是令人厌恶的，还是涉及奖励收益或损失。我们使用了内化症状的双因素模型，将焦虑和抑郁共同的症状方差与各自独特的症状方差分开。在两个实验中，我们使用分层贝叶斯框架对波动性任务下的概率决策进行了建模。共同内化因子的分数升高，焦虑和抑郁项目的负荷高，与学习波动性的贫困调整有关，无论结果是否涉及奖励获得，电刺激或奖励损失。特别是，高共同因素分数与在动荡环境中取得好于预期的成果后学习受到抑制有关。没有观察到这种关系的焦虑或抑郁症的具体症状因素。
Using a contingency volatility manipulation, we tested the hypothesis that difficulty adapting probabilistic decision-making to second-order uncertainty might reflect a core deficit that cuts across anxiety and depression and holds regardless of whether outcomes are aversive or involve reward gain or loss. We used bifactor modeling of internalizing symptoms to separate symptom variance common to both anxiety and depression from that unique to each. Across two experiments, we modeled performance on a probabilistic decision-making under volatility task using a hierarchical Bayesian framework. Elevated scores on the common internalizing factor, with high loadings across anxiety and depression items, were linked to impoverished adjustment of learning to volatility regardless of whether outcomes involved reward gain, electrical stimulation, or reward loss. In particular, high common factor scores were linked to dampened learning following better-than-expected outcomes in volatile environments. No such relationships were observed for anxiety- or depression-specific symptom factors.