Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
STOC'93 25th Annual ACM Symposium on the Theory of Computing
Playing the matching-shoulders lob-pass game with logarithmic regret
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
Learning to Predict by the Methods of Temporal Differences
Machine Learning
Computational algorithms and neuronal network models underlying decision processes
Neural Networks - 2006 Special issue: Neurobiology of decision making
Journal of Cognitive Neuroscience
Operant matching as a nash equilibrium of an intertemporal game
Neural Computation
| Hi-index | 0.00 |
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 agree ment 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.