Adaptive Coding of Reward Value by Dopamine Neurons

It is important for animals to estimate the value of rewards as accurately as possible. Because the number of potential reward values is very large, it is necessary that the brain's limited resources be allocated so as to discriminate better among more likely reward outcomes at the expense of less likely outcomes. We found that midbrain dopamine neurons rapidly adapted to the information provided by reward-predicting stimuli. Responses shifted relative to the expected reward value, and the gain adjusted to the variance of reward value. In this way, dopamine neurons maintained their reward sensitivity over a large range of reward values.

[1]  W. D. Halliburton,et al.  Handbook of Physiology , 1870, Edinburgh Medical Journal.

[2]  F. Plum Handbook of Physiology. , 1960 .

[3]  L. Brain The Nervous System , 1963, Nature.

[4]  W. F. Prokasy,et al.  Classical conditioning II: Current research and theory. , 1972 .

[5]  I. Ohzawa,et al.  Contrast gain control in the cat visual cortex , 1982, Nature.

[6]  S. Laughlin,et al.  Predictive coding: a fresh view of inhibition in the retina , 1982, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[7]  R. Wise,et al.  Localization of drug reward mechanisms by intracranial injections , 1992, Synapse.

[8]  K. Berridge,et al.  The neural basis of drug craving: An incentive-sensitization theory of addiction , 1993, Brain Research Reviews.

[9]  P. Nicole,et al.  La logique, ou, L'art de penser , 1993 .

[10]  T. Robbins,et al.  Neurobehavioural mechanisms of reward and motivation , 1996, Current Opinion in Neurobiology.

[11]  Peter Dayan,et al.  A Neural Substrate of Prediction and Reward , 1997, Science.

[12]  P. Shizgal Neural basis of utility estimation , 1997, Current Opinion in Neurobiology.

[13]  Michael J. Berry,et al.  Adaptation of retinal processing to image contrast and spatial scale , 1997, Nature.

[14]  C. Gallistel,et al.  Self-stimulating rats combine subjective reward magnitude and subjective reward rate multiplicatively. , 1998, Journal of experimental psychology. Animal behavior processes.

[15]  W. Schultz Predictive reward signal of dopamine neurons. , 1998, Journal of neurophysiology.

[16]  William Bialek,et al.  Adaptive Rescaling Maximizes Information Transmission , 2000, Neuron.

[17]  Adrienne L. Fairhall,et al.  Efficiency and ambiguity in an adaptive neural code , 2001, Nature.

[18]  D. Wilkin,et al.  Neuron , 2001, Brain Research.

[19]  W. Schultz,et al.  Dopamine responses comply with basic assumptions of formal learning theory , 2001, Nature.

[20]  P. Glimcher decisions, uncertainty and the brain , 2003 .

[21]  W. Schultz,et al.  Discrete Coding of Reward Probability and Uncertainty by Dopamine Neurons , 2003, Science.

[22]  Tatsuo K Sato,et al.  Correlated Coding of Motivation and Outcome of Decision by Dopamine Neurons , 2003, The Journal of Neuroscience.

[23]  O. Hikosaka,et al.  Dopamine Neurons Can Represent Context-Dependent Prediction Error , 2004, Neuron.

[24]  O. Hikosaka,et al.  Reward-predicting activity of dopamine and caudate neurons--a possible mechanism of motivational control of saccadic eye movement. , 2004, Journal of neurophysiology.

[25]  E. Thorndike Animal Intelligence; Experimental Studies , 2009 .