Access to limited-capacity neural systems of cognitive control must be restricted to the most relevant information. How the brain identifies and selects items for preferential processing is not fully understood. Anatomical models often place the selection mechanism in the medial frontal cortex (MFC), and one computational model proposes that the mesotelencephalic dopamine (DA) system, via its reward prediction properties, provides a “gate” through which information gains access to limited-capacity systems. There is a medial frontal event-related potential (ERP) index of attention selection, the anterior positivity (P2a), associated with DA reward system input to the MFC for the identification of task-relevant perceptual representations. The P2a has a similar spatio-temporal distribution as the medial frontal negativity (MFN), elicited to error responses or choices resulting in monetary loss. The MFN has also been linked to DA projections to the MFC but for action monitoring rather than attention selection. This study proposes that the P2a and the MFN reflect the same MFC evaluation function and use a passive reward prediction design containing neither instructed attention nor response to demonstrate that the ERP over medial frontal leads at the P2a/MFN latency is consistent with activity of midbrain DA neurons, positive to unpredicted rewards and negative when a predicted reward is withheld. This result suggests that MFC activity is regulated by DA reward system input and may function to identify items or actions that exceed or fail to meet motivational prediction.

Recent work suggests that fluctuations in dopamine delivery at target structures represent an evaluation of future events that can be used to direct learning and decision-making. To examine the behavioral consequences of this interpretation, we gave simple decision-making tasks to 66 human subjects and to a network based on a predictive model of mesencephalic dopamine systems. The human subjects displayed behavior similar to the network behavior in terms of choice allocation and the character of deliberation times. The agreement between human and model performances suggests a direct relationship between biases in human decision strategies and fluctuating dopamine delivery. We also show that the model offers a new interpretation of deficits that result when dopamine levels are increased or decreased through disease or pharmacological interventions. The bottom-up approach presented here also suggests that a variety of behavioral strategies may result from the expression of relatively simple neural mechanisms in different behavioral contexts.