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Mapping anhedonia onto reinforcement learning: a behavioural meta-analysis

机译:将性欲减退映射到强化学习上:行为荟萃分析

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Background Depression is characterised partly by blunted reactions to reward. However, tasks probing this deficiency have not distinguished insensitivity to reward from insensitivity to the prediction errors for reward that determine learning and are putatively reported by the phasic activity of dopamine neurons. We attempted to disentangle these factors with respect to anhedonia in the context of stress, Major Depressive Disorder (MDD), Bipolar Disorder (BPD) and a dopaminergic challenge. Methods Six behavioural datasets involving 392 experimental sessions were subjected to a model-based, Bayesian meta-analysis. Participants across all six studies performed a probabilistic reward task that used an asymmetric reinforcement schedule to assess reward learning. Healthy controls were tested under baseline conditions, stress or after receiving the dopamine D2 agonist pramipexole. In addition, participants with current or past MDD or BPD were evaluated. Reinforcement learning models isolated the contributions of variation in reward sensitivity and learning rate. Results MDD and anhedonia reduced reward sensitivity more than they affected the learning rate, while a low dose of the dopamine D2 agonist pramipexole showed the opposite pattern. Stress led to a pattern consistent with a mixed effect on reward sensitivity and learning rate. Conclusion Reward-related learning reflected at least two partially separable contributions. The first related to phasic prediction error signalling, and was preferentially modulated by a low dose of the dopamine agonist pramipexole. The second related directly to reward sensitivity, and was preferentially reduced in MDD and anhedonia. Stress altered both components. Collectively, these findings highlight the contribution of model-based reinforcement learning meta-analysis for dissecting anhedonic behavior.
机译:背景抑郁的部分特征是对奖励的反应迟钝。但是,探测这种缺陷的任务并未将对奖励的不敏感性与对确定学习的奖励的预测误差的不敏感性区分开来,并据推测是由多巴胺神经元的相活动所报告的。我们试图在压力,重度抑郁症(MDD),双相情感障碍(BPD)和多巴胺能挑战的背景下,将这些因素与快感缺乏症区分开。方法对涉及392个实验阶段的六个行为数据集进行基于模型的贝叶斯荟萃分析。所有六项研究的参与者均执行了概率性奖励任务,该任务使用非对称强化时间表来评估奖励学习。在基线条件,压力或接受多巴胺D 2 激动剂普拉克索后测试健康对照组。此外,对当前或过去的MDD或BPD的参与者进行了评估。强化学习模型隔离了奖励敏感性和学习率变化的贡献。结果MDD和快感缺乏症对奖赏敏感性的降低远大于其对学习率的影响,而低剂量的多巴胺D 2 激动剂普拉克索表现出相反的模式。压力导致一种模式,与奖励敏感性和学习率的混合影响一致。结论奖励相关的学习至少反映了两个部分可分离的贡献。第一个与相位预测误差信号有关,并且优先通过低剂量的多巴胺激动剂普拉克索来调节。第二种与奖赏敏感性直接相关,在MDD和快感缺乏症中优先降低。压力改变了两个部分。总的来说,这些发现突出了基于模型的强化学习元分析对解剖性快感行为的贡献。

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