Frontal network dynamics reflect neurocomputational mechanisms for reducing maladaptive biases in motivated action

Motivation exerts control over behavior by eliciting Pavlovian responses, which can either match or conflict with instrumental action. We can overcome maladaptive motivational influences, putatively through frontal cognitive control. However, the neurocomputational mechanisms subserving this control are unclear; does control entail upregulating instrumental systems, downregulating Pavlovian systems, or both? We combined EEG recordings with a motivational Go/NoGo learning task (N=34), where multiple Go options enabled us to disentangle selective action learning from non-selective Pavlovian responses. Midfrontal theta-band (4-8Hz) activity covaried with the level of Pavlovian conflict, and was associated with reduced Pavlovian biases, rather than reduced instrumental learning biases. Motor and lateral prefrontal regions synchronized to the midfrontal cortex, and these network dynamics predicted the reduction of Pavlovian biases over and above local, midfrontal theta activity. This work links midfrontal processing to detecting Pavlovian conflict, and highlights the importance of network processing in reducing the impact of maladaptive, Pavlovian biases.

动机通过唤起巴甫洛夫反应（Pavlovian responses）来支配行为，这类反应可与工具性行动（instrumental action）相一致或产生冲突。我们能够克服适应不良的动机性影响，这一过程被认为依赖于前额叶认知控制（frontal cognitive control）。然而，支撑该控制过程的神经计算机制尚不明确：认知控制究竟是通过上调工具性系统、下调巴甫洛夫系统，抑或是同时调控二者实现的？本研究结合脑电图（EEG）记录与动机性Go/NoGo学习任务（N=34），实验中设置的多重Go反应选项使我们能够将选择性行动学习与非选择性巴甫洛夫反应区分开来。额中区theta频段（4-8Hz）活动与巴甫洛夫冲突程度呈共变关系，且与巴甫洛夫偏差的降低相关，而非工具性学习偏差的降低。运动皮层与外侧前额叶皮层与额中区皮层形成功能同步活动，且这类网络动态在控制局部额中区theta活动的影响后，仍可预测巴甫洛夫偏差的降低。本研究将额中区加工与巴甫洛夫冲突的检测联系起来，并强调了网络加工在降低适应不良的巴甫洛夫偏差影响中的重要性。