Frontal Theta Oscillatory Activity Is a Common Mechanism for the Computation of Unexpected Outcomes and Learning Rate

被引:58
|
作者
Mas-Herrero, Ernest [1 ]
Marco-Pallares, Josep [1 ,2 ]
机构
[1] LHospitalet Llobregat, Barcelona, Spain
[2] Univ Barcelona, Barcelona 08097, Spain
关键词
FEEDBACK-RELATED NEGATIVITY; ANTERIOR CINGULATE CORTEX; PREDICTION ERROR; PREFRONTAL CORTEX; DECISION-MAKING; MIDLINE THETA; SIGNALS; EEG; INFORMATION; ADJUSTMENTS;
D O I
10.1162/jocn_a_00516
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
In decision-making processes, the relevance of the information yielded by outcomes varies across time and situations. It increases when previous predictions are not accurate and in contexts with high environmental uncertainty. Previous fMRI studies have shown an important role of medial pFC in coding both reward prediction errors and the impact of this information to guide future decisions. However, it is unclear whether these two processes are dissociated in time or occur simultaneously, suggesting that a common mechanism is engaged. In the present work, we studied the modulation of two electro-physiological responses associated to outcome processing-the feedback-related negativity ERP and frontocentral theta oscillatory activity-with the reward prediction error and the learning rate. Twenty-six participants performed two learning tasks differing in the degree of predictability of the outcomes: a reversal learning task and a probabilistic learning task with multiple blocks of novel cue-outcome associations. We implemented a reinforcement learning model to obtain the single-trial reward prediction error and the learning rate for each participant and task. Our results indicated that midfrontal theta activity and feedback-related negativity increased linearly with the unsigned prediction error. In addition, variations of frontal theta oscillatory activity predicted the learning rate across tasks and participants. These results support the existence of a common brain mechanism for the computation of unsigned prediction error and learning rate.
引用
收藏
页码:447 / 458
页数:12
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