CiteULike: benoithv Glimcher

Midbrain dopamine neurons encode a quantitative reward prediction error signal.

HM Bayer — 2005-07-20T16:11:35-00:00

Neuron, Vol. 47, No. 1. (7 July 2005), pp. 129-141.

The midbrain dopamine neurons are hypothesized to provide a physiological correlate of the reward prediction error signal required by current models of reinforcement learning. We examined the activity of single dopamine neurons during a task in which subjects learned by trial and error when to make an eye movement for a juice reward. We found that these neurons encoded the difference between the current reward and a weighted average of previous rewards, a reward prediction error, but only for outcomes that were better than expected. Thus, the firing rate of midbrain dopamine neurons is quantitatively predicted by theoretical descriptions of the reward prediction error signal used in reinforcement learning models for circumstances in which this signal has a positive value. We also found that the dopamine system continued to compute the reward prediction error even when the behavioral policy of the animal was only weakly influenced by this computation.

Physiological utility theory and the neuroeconomics of choice

Paul Glimcher — 2005-03-15T19:55:50-00:00

Games and Economic Behavior, Vol. In Press, Corrected Proof

Over the past half century economists have responded to the challenges of Allais [Econometrica (1953) 53], Ellsberg [Quart. J. Econ. (1961) 643] and others raised to neoclassicism either by bounding the reach of economic theory or by turning to descriptive approaches. While both of these strategies have been enormously fruitful, neither has provided a clear programmatic approach that aspires to a complete understanding of human decision making as did neoclassicism. There is, however, growing evidence that economists and neurobiologists are now beginning to reveal the physical mechanisms by which the human neuroarchitecture accomplishes decision making. Although in their infancy, these studies suggest both a single unified framework for understanding human decision making and a methodology for constraining the scope and structure of economic theory. Indeed, there is already evidence that these studies place mathematical constraints on existing economic models. This article reviews some of those constraints and suggests the outline of a neuroeconomic theory of decision.

Neural correlates of decision variables in parietal cortex.

ML Platt — 2005-02-01T19:51:55-00:00

Nature, Vol. 400, No. 6741. (15 July 1999), pp. 233-238.

Decision theory proposes that humans and animals decide what to do in a given situation by assessing the relative value of each possible response. This assessment can be computed, in part, from the probability that each action will result in a gain and the magnitude of the gain expected. Here we show that the gain (or reward) a monkey can expect to realize from an eye-movement response modulates the activity of neurons in the lateral intraparietal area, an area of primate cortex that is thought to transform visual signals into eye-movement commands. We also show that the activity of these neurons is sensitive to the probability that a particular response will result in a gain. When animals can choose freely between two alternative responses, the choices subjects make and neuronal activation in this area are both correlated with the relative amount of gain that the animal can expect from each response. Our data indicate that a decision-theoretic model may provide a powerful new framework for studying the neural processes that intervene between sensation and action.

Activity in posterior parietal cortex is correlated with the relative subjective desirability of action.

MC Dorris — 2005-02-04T21:13:00-00:00

Neuron, Vol. 44, No. 2. (14 October 2004), pp. 365-378.

Behavioral studies suggest that making a decision involves representing the overall desirability of all available actions and then selecting that action that is most desirable. Physiological studies have proposed that neurons in the parietal cortex play a role in selecting movements for execution. To test the hypothesis that these parietal neurons encode the subjective desirability of making particular movements, we exploited Nash's game theoretic equilibrium, during which the subjective desirability of multiple actions should be equal for human players. Behavior measured during a strategic game suggests that monkeys' choices, like those of humans, are guided by subjective desirability. Under these conditions, activity in the parietal cortex was correlated with the relative subjective desirability of actions irrespective of the specific combination of reward magnitude, reward probability, and response probability associated with each action. These observations may help place many recent findings regarding the posterior parietal cortex into a common conceptual framework.