脑电图
额叶皮质
计算模型
认知
神经科学
心理学
概率逻辑
人工智能
均方预测误差
人工神经网络
计算机科学
任务(项目管理)
额叶
机制(生物学)
钥匙(锁)
经颅交流电刺激
前额叶皮质
机器学习
适应性行为
脑刺激
认知心理学
基本认知任务
因果模型
经颅直流电刺激
适应(眼睛)
预测能力
认知神经科学
意识的神经相关物
功率(物理)
任务切换
刺激
作者
Yifei Zhang,Feng Deng,Jiajun Liao,Tom Verguts,Qi Chen
标识
DOI:10.1523/jneurosci.1236-25.2025
摘要
Cognitive flexibility, the ability to switch behavior in response to changing rules in an uncertain environment, is crucial for adaptive decision making. Prior research has hypothesized a key role of prediction error and theta oscillations in medial frontal cortex in this process. However, the causal link between such processes remains to be established. To address this, we combined neural stimulation, EEG, behavioral measurement, and computational modeling. Specifically, we applied high-definition transcranial direct current stimulation (HD-tDCS) to modulate theta oscillations as measured via EEG followed by a probabilistic reversal learning task in 48 adults (18 female and 30 male human subjects). We found that anodal stimulation reduced theta power and rule prediction error, and it increased the number of trials needed to reliably switch between rules. These findings support the role of rule prediction error signaling as a key mechanism linking neural oscillations to behavioral adaptation and highlight the importance of theta power and rule prediction error for cognitive flexibility. Significance statement Cognitive flexibility—the ability to adjust behavior when rules change—is critical for adaptive behavior in uncertain environments. Although prediction error signaling and theta oscillations in medial frontal cortex have been proposed as key mechanisms, their causal relationship remains unclear. Here, we combine high-definition transcranial direct current stimulation (HD-tDCS), EEG, behavioral assessment, and computational modeling to test the causal contribution of those factors on cognitive flexibility. We show that anodal stimulation reduces frontal theta power and rule-level prediction errors, leading to more trials to commit to the new rule. These findings provide causal evidence that supports behavioral flexibility, advancing our understanding of the neural computations underlying adaptive decision making.
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