Note to users. If you're seeing this message, it means that your browser cannot find this page's style/presentation instructions -- or possibly that you are using a browser that does not support current Web standards. Find out more about why this message is appearing, and what you can do to make your experience of our site the best it can be.

Sci. STKE, 14 December 2004
Vol. 2004, Issue 263, p. tw451
[DOI: 10.1126/stke.2632004tw451]

EDITORS' CHOICE

NEUROSCIENCE Cocaine Signals Never Disappoint

The temporal difference reinforcement learning (TDRL) model provides a computational framework for describing how future rewards are valued, how current choices are made, and how differences between what is received and what is expected are fed back into updated calculations of future rewards. In TDRL, the difference signal between receipt and expectation is carried by neurons that use the transmitter dopamine. Redish (see the Perspective by Ahmed) applies this model and develops an explanation, in neural computational terms, for some aspects of behavior in the context of addictive substances. The key point is that cocaine induces, via pharmacologic pathways, a dopamine signal that does not accurately reflect or respond to the difference in actual and expected reward; cocaine is always valued as being more rewarding than originally thought.

A. D. Redish, Addiction as a computational process gone awry. Science 306, 1944-1947 (2004). [Abstract] [Full Text]

S. H. Ahmed, Addiction as compulsive reward prediction. Science 306, 1901-1902 (2004). [Summary] [Full Text]

Citation: Cocaine Signals Never Disappoint. Sci. STKE 2004, tw451 (2004).

To Advertise     Find Products

Science Signaling. ISSN 1937-9145 (online), 1945-0877 (print). Pre-2008: Science's STKE. ISSN 1525-8882