Laboratoire de Neurosciences Cognitives et Computationnelles, Institut National de la Santé et de la Recherche Médicale (Inserm), Paris, France.
Département d'Études Cognitives, École Normale Supérieure, Université PSL, Paris, France.
Nat Commun. 2021 Apr 13;12(1):2228. doi: 10.1038/s41467-021-22396-6.
Making accurate decisions in uncertain environments requires identifying the generative cause of sensory cues, but also the expected outcomes of possible actions. Although both cognitive processes can be formalized as Bayesian inference, they are commonly studied using different experimental frameworks, making their formal comparison difficult. Here, by framing a reversal learning task either as cue-based or outcome-based inference, we found that humans perceive the same volatile environment as more stable when inferring its hidden state by interaction with uncertain outcomes than by observation of equally uncertain cues. Multivariate patterns of magnetoencephalographic (MEG) activity reflected this behavioral difference in the neural interaction between inferred beliefs and incoming evidence, an effect originating from associative regions in the temporal lobe. Together, these findings indicate that the degree of control over the sampling of volatile environments shapes human learning and decision-making under uncertainty.
在不确定的环境中做出准确的决策需要识别感官线索的生成原因，以及可能行动的预期结果。尽管这两个认知过程都可以被形式化为贝叶斯推理，但它们通常使用不同的实验框架进行研究，使得它们的正式比较变得困难。在这里，通过将反转学习任务分别表述为基于线索的或基于结果的推理，我们发现，当通过与不确定结果的交互而不是通过观察同样不确定的线索来推断其隐藏状态时，人类将相同的不稳定环境感知为更稳定。脑磁图（MEG）活动的多元模式反映了这种行为差异，即推断的信念和传入证据之间的神经相互作用，这种效应源于颞叶中的关联区域。总之，这些发现表明，对不稳定环境采样的控制程度塑造了人类在不确定情况下的学习和决策。
