Discrete coding of reward probability and uncertainty by dopamine neurons.

by: CD Fiorillo, PN Tobler, W Schultz

Science, Vol. 299, No. 5614. (21 March 2003), pp. 1898-1902.

View FullText article

DOI, HighWire, Pubmed, Hubmed

Reviews [Write a review of this article]

There are no reviews of this article

Find related articles from these CiteULike users

klouie, stefanherzog, benoithv, ifat, krista, phystor, awooga, Glimcher_Lab (group), CLIC (group), logical_cognition (group), ACS-Basel (group), nishiokov, farhat

Find related articles with these CiteULike tags

comparative, decision-making, dopamine, electrophysiology, monkey, neuroeconomics, neurophysiology, no-tag, reinforcement_learning, reinforcement-learning, reward, reward-uncertainty, time, uncertainty, vta

Abstract

Uncertainty is critical in the measure of information and in assessing the accuracy of predictions. It is determined by probability P, being maximal at P = 0.5 and decreasing at higher and lower probabilities. Using distinct stimuli to indicate the probability of reward, we found that the phasic activation of dopamine neurons varied monotonically across the full range of probabilities, supporting past claims that this response codes the discrepancy between predicted and actual reward. In contrast, a previously unobserved response covaried with uncertainty and consisted of a gradual increase in activity until the potential time of reward. The coding of uncertainty suggests a possible role for dopamine signals in attention-based learning and risk-taking behavior.

@article{citeulike:121957, abstract = {Uncertainty is critical in the measure of information and in assessing the accuracy of predictions. It is determined by probability P, being maximal at P = 0.5 and decreasing at higher and lower probabilities. Using distinct stimuli to indicate the probability of reward, we found that the phasic activation of dopamine neurons varied monotonically across the full range of probabilities, supporting past claims that this response codes the discrepancy between predicted and actual reward. In contrast, a previously unobserved response covaried with uncertainty and consisted of a gradual increase in activity until the potential time of reward. The coding of uncertainty suggests a possible role for dopamine signals in attention-based learning and risk-taking behavior.}, address = {Institute of Physiology, University of Fribourg, CH-1700 Fribourg, Switzerland. cdf28@cam.ac.uk}, author = {Fiorillo, C. D. and Tobler, P. N. and Schultz, W. }, citeulike-article-id = {121957}, doi = {http://dx.doi.org/10.1126/science.1077349}, issn = {1095-9203}, journal = {Science}, keywords = {comparative, neuroeconomics}, month = {March}, number = {5614}, pages = {1898--1902}, posted-at = {2005-03-16 16:26:02}, priority = {3}, title = {Discrete coding of reward probability and uncertainty by dopamine neurons.}, url = {http://dx.doi.org/10.1126/science.1077349}, volume = {299}, year = {2003} }

RIS record

TY - JOUR ID - citeulike:121957 L3 - citeulike-article-id:121957 TI - Discrete coding of reward probability and uncertainty by dopamine neurons. JF - Science VL - 299 IS - 5614 SP - 1898 EP - 1902 AD - Institute of Physiology, University of Fribourg, CH-1700 Fribourg, Switzerland. cdf28@cam.ac.uk SN - 1095-9203 N2 - Uncertainty is critical in the measure of information and in assessing the accuracy of predictions. It is determined by probability P, being maximal at P = 0.5 and decreasing at higher and lower probabilities. Using distinct stimuli to indicate the probability of reward, we found that the phasic activation of dopamine neurons varied monotonically across the full range of probabilities, supporting past claims that this response codes the discrepancy between predicted and actual reward. In contrast, a previously unobserved response covaried with uncertainty and consisted of a gradual increase in activity until the potential time of reward. The coding of uncertainty suggests a possible role for dopamine signals in attention-based learning and risk-taking behavior. KW - comparative KW - neuroeconomics AU - Fiorillo, CD AU - Tobler, PN AU - Schultz, W PY - 2003/03/21/ UR - http://dx.doi.org/10.1126/science.1077349 ER -

RIS BibTeX