Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany.
Department for Social and Preventive Medicine, University of Potsdam, Potsdam, Germany.
Psychopharmacology (Berl). 2019 Aug;236(8):2437-2449. doi: 10.1007/s00213-019-05299-9. Epub 2019 Jun 28.
Aversive stimuli in the environment influence human actions. This includes valence-dependent influences on action selection, e.g., increased avoidance but decreased approach behavior. However, it is yet unclear how aversive stimuli interact with complex learning and decision-making in the reward and avoidance domain. Moreover, the underlying computational mechanisms of these decision-making biases are unknown.
To elucidate these mechanisms, 54 healthy young male subjects performed a two-step sequential decision-making task, which allows to computationally model different aspects of learning, e.g., model-free, habitual, and model-based, goal-directed learning. We used a within-subject design, crossing task valence (reward vs. punishment learning) with emotional context (aversive vs. neutral background stimuli). We analyzed choice data, applied a computational model, and performed simulations.
Whereas model-based learning was not affected, aversive stimuli interacted with model-free learning in a way that depended on task valence. Thus, aversive stimuli increased model-free avoidance learning but decreased model-free reward learning. The computational model confirmed this effect: the parameter lambda that indicates the influence of reward prediction errors on decision values was increased in the punishment condition but decreased in the reward condition when aversive stimuli were present. Further, by using the inferred computational parameters to simulate choice data, our effects were captured. Exploratory analyses revealed that the observed biases were associated with subclinical depressive symptoms.
Our data show that aversive environmental stimuli affect complex learning and decision-making, which depends on task valence. Further, we provide a model of the underlying computations of this affective modulation. Finally, our finding of increased decision-making biases in subjects reporting subclinical depressive symptoms matches recent reports of amplified Pavlovian influences on action selection in depression and suggests a potential vulnerability factor for mood disorders. We discuss our findings in the light of the involvement of the neuromodulators serotonin and dopamine.
环境中的厌恶性刺激会影响人类的行为。这包括对行为选择的效价依赖性影响,例如增加回避但减少接近行为。然而,目前尚不清楚厌恶性刺激如何与奖励和回避领域的复杂学习和决策相互作用。此外,这些决策偏差的潜在计算机制尚不清楚。
为了阐明这些机制,54 名健康年轻男性受试者进行了两步顺序决策任务,该任务允许对不同方面的学习进行计算建模,例如,无模型、习惯和基于模型的目标导向学习。我们使用了一种被试内设计,交叉任务效价(奖励与惩罚学习)与情绪背景(厌恶与中性背景刺激)。我们分析了选择数据,应用了计算模型,并进行了模拟。
虽然无模型学习不受影响,但厌恶性刺激与无模型学习相互作用的方式取决于任务效价。因此,厌恶性刺激增加了无模型的回避学习,但减少了无模型的奖励学习。计算模型证实了这一效应:在惩罚条件下,指示奖励预测误差对决策值影响的参数 lambda 增加,但在奖励条件下,当存在厌恶性刺激时,lambda 减少。此外,通过使用推断出的计算参数来模拟选择数据,我们捕捉到了我们的效应。探索性分析表明,观察到的偏差与亚临床抑郁症状有关。
我们的数据表明,厌恶性环境刺激会影响复杂的学习和决策,这取决于任务效价。此外,我们提供了一个对这种情感调节的潜在计算的模型。最后,我们发现报告亚临床抑郁症状的受试者的决策偏差更大,这与抑郁时增加的巴甫洛夫式影响对行为选择的近期报告相吻合,并表明了情绪障碍的一个潜在脆弱性因素。我们根据神经调质 5-羟色胺和多巴胺的参与讨论了我们的发现。