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

Abstract

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.