A computational role for dopamine delivery in human decision-making

n Recent work suggests that uctuations in dopamine deliv-ery 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 mes-encephalic dopamine systems. The human subjects displayed behavior similar to the network behavior in terms of choice allocation and the character of deliberation times. The agree-ment between human and model performances suggests a direct relationship between biases in human decision strate-gies and uctuating dopamine delivery. We also show that the model offers a new interpretation of decits that result when dopamine levels are increased or decreased through disease or pharmacological interventions. The bottom-up approach pre-sented here also suggests that a variety of behavioral strategies may result from the expression of relatively simple neural mechanisms in different behavioral contexts.