Decision making relies on the interplay between two distinct learning mechanisms, namely habitual model-free learning and goal-directed model-based learning. Recent literature suggests that this interplay is significantly shaped by the environmental structure as represented by an internal model. We employed a modified two-stage but one-decision Markov decision task to investigate how two internal models differing in the predictability of stage transitions influence the neural correlates of feedback processing. Our results demonstrate that fronto-central theta and the feedback-related negativity (FRN), two correlates of reward prediction errors in the medial frontal cortex, are independent of the internal representations of the environmental structure. In contrast, centro-parietal delta and the P3, two correlates possibly reflecting feedback evaluation in working memory, were highly susceptible to the underlying internal model. Model-based analyses of single-trial activity showed a comparable pattern, indicating that while the computation of unsigned reward prediction errors is represented by theta and the FRN irrespective of the internal models, the P3 adapts to the internal representation of an environment. Our findings further substantiate the assumption that the feedback-locked components under investigation reflect distinct mechanisms of feedback processing and that different internal models selectively influence these mechanisms.

决策依赖于两种不同学习机制之间的相互作用，即习惯性无模型学习和目标导向的基于模型的学习。最近的文献表明，这种相互作用很大程度上是由内部模型所代表的环境结构决定的。我们采用了一种改进的两阶段单决策马尔可夫决策任务来研究阶段转换可预测性不同的两个内部模型如何影响反馈处理的神经相关性。我们的结果表明，额中央θ和反馈相关负性（FRN）是内侧额叶皮层奖励预测误差的两个相关因素，独立于环境结构的内部表征。相比之下，中央顶叶三角洲和 P3 这两个可能反映工作记忆中反馈评估的相关因素非常容易受到潜在内部模型的影响。对单次试验活动的基于模型的分析显示出类似的模式，表明虽然无符号奖励预测误差的计算由 theta 和 FRN 表示，而与内部模型无关，但 P3 会适应环境的内部表示。我们的研究结果进一步证实了这样的假设：所研究的反馈锁定组件反映了不同的反馈处理机制，并且不同的内部模型选择性地影响这些机制。