Gershman Samuel J, Guitart-Masip Marc, Cavanagh James F
Department of Psychology and Center for Brain Science, Harvard University, Cambridge, Massachusetts, United States of America.
Center for Brains, Minds and Machines, MIT, Cambridge, Massachusetts, United States of America.
PLoS Comput Biol. 2021 Feb 10;17(2):e1008553. doi: 10.1371/journal.pcbi.1008553. eCollection 2021 Feb.
Pavlovian associations drive approach towards reward-predictive cues, and avoidance of punishment-predictive cues. These associations "misbehave" when they conflict with correct instrumental behavior. This raises the question of how Pavlovian and instrumental influences on behavior are arbitrated. We test a computational theory according to which Pavlovian influence will be stronger when inferred controllability of outcomes is low. Using a model-based analysis of a Go/NoGo task with human subjects, we show that theta-band oscillatory power in frontal cortex tracks inferred controllability, and that these inferences predict Pavlovian action biases. Functional MRI data revealed an inferior frontal gyrus correlate of action probability and a ventromedial prefrontal correlate of outcome valence, both of which were modulated by inferred controllability.
巴甫洛夫式关联驱动个体趋向奖励预测线索并回避惩罚预测线索。当这些关联与正确的工具性(操作性)行为冲突时,它们就会“行为失常”。这就引出了一个问题,即巴甫洛夫式和工具性对行为的影响是如何被协调的。我们测试了一种计算理论,根据该理论,当结果的推断可控性较低时,巴甫洛夫式影响会更强。通过对人类受试者进行的基于模型的Go/NoGo任务分析,我们发现前额叶皮层中的θ波段振荡功率跟踪推断的可控性,并且这些推断预测了巴甫洛夫式的行动偏差。功能磁共振成像数据显示,额下回与行动概率相关,腹内侧前额叶与结果效价相关,两者均受推断可控性的调节。