Institut Jean Nicod, Département d'Études Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, Paris, France.
Laboratoire de Neurosciences Cognitives et Computationnelles, Département d'Études Cognitives, École Normale Supérieure, INSERM, PSL University, Paris, France.
Nat Hum Behav. 2020 Oct;4(10):1067-1079. doi: 10.1038/s41562-020-0919-5. Epub 2020 Aug 3.
The valence of new information influences learning rates in humans: good news tends to receive more weight than bad news. We investigated this learning bias in four experiments, by systematically manipulating the source of required action (free versus forced choices), outcome contingencies (low versus high reward) and motor requirements (go versus no-go choices). Analysis of model-estimated learning rates showed that the confirmation bias in learning rates was specific to free choices, but was independent of outcome contingencies. The bias was also unaffected by the motor requirements, thus suggesting that it operates in the representational space of decisions, rather than motoric actions. Finally, model simulations revealed that learning rates estimated from the choice-confirmation model had the effect of maximizing performance across low- and high-reward environments. We therefore suggest that choice-confirmation bias may be adaptive for efficient learning of action-outcome contingencies, above and beyond fostering person-level dispositions such as self-esteem.
好消息往往比坏消息更受重视。我们通过系统地操纵所需行动的来源（自由选择与强制选择）、结果关联（低奖励与高奖励）和运动要求（是选择与否选择），在四个实验中研究了这种学习偏见。通过对模型估计的学习率进行分析，我们发现学习率中的确认偏见特定于自由选择，但与结果关联无关。这种偏见也不受运动要求的影响，因此表明它在决策的表示空间中起作用，而不是运动动作。最后，模型模拟表明，从选择确认模型估计的学习率具有在低奖励和高奖励环境中最大化性能的效果。因此，我们认为，选择确认偏差可能有助于有效地学习行为-结果关联，而不仅仅是培养自尊心等个人特质。
