Thu, 21 Aug 2008 14:05:21 BST CiteULike: nelmor's Okamoto http://www.citeulike.org/user/nelmor/author/Okamoto CiteULike.org en-gb Copyright © 2004-2008 citeulike.org http://www.citeulike.org/user/nelmor/article/2712965 <i>J. Neurosci., Vol. 28, No. 17. (23 April 2008), pp. 4528-4532.</i><br /><br />Previous animal experiments have shown that serotonin is involved in the control of impulsive choice, as characterized by high preference for small immediate rewards over larger delayed rewards. Previous human studies under serotonin manipulation, however, have been either inconclusive on the effect on impulsivity or have shown an effect in the speed of action-reward learning or the optimality of action choice. Here, we manipulated central serotonergic levels of healthy volunteers by dietary tryptophan depletion and loading. Subjects performed a "dynamic" delayed reward choice task that required a continuous update of the reward value estimates to maximize total gain. By using a computational model of delayed reward choice learning, we estimated the parameters governing the subjects' reward choices in low-, normal, and high-serotonin conditions. We found an increase of proportion in small reward choices, together with an increase in the rate of discounting of delayed rewards in the low-serotonin condition compared with the control and high-serotonin conditions. There were no significant differences between conditions in the speed of learning of the estimated delayed reward values or in the variability of reward choice. Therefore, in line with previous animal experiments, our results show that low-serotonin levels steepen delayed reward discounting in humans. The combined results of our previous and current studies suggest that serotonin may adjust the rate of delayed reward discounting via the modulation of specific loops in parallel corticobasal ganglia circuits. 10.1523/JNEUROSCI.4982-07.2008 Low-Serotonin Levels Increase Delayed Reward Discounting in Humans Nicolas Schweighofer Mathieu Bertin Kazuhiro Shishida Yasumasa Okamoto Saori Tanaka Shigeto Yamawaki Kenji Doya doi:10.1523/JNEUROSCI.4982-07.2008 J. Neurosci., Vol. 28, No. 17. (23 April 2008), pp. 4528-4532. 2008-04-24T13:04:57-00:00 2008 J. Neurosci. 28 17 4528 4532 discounting human reward serotonin http://www.citeulike.org/user/nelmor/article/822873 <i>Neural Networks, Vol. In Press, Corrected Proof</i><br /><br />Animals or humans often encounter such situations in which they must choose their behavioral responses to be made in the near or distant future. Such a decision is made through continuous and bidirectional interactions between the environment surrounding the brain and its internal state or dynamical processes. Therefore, decision making may provide a unique field of researches for studying information processing by the brain, a biological system open to information exchanges with the external world. To make a decision, the brain must analyze pieces of information given externally, past experiences in a similar situation, possible behavioral responses, and predicted outcomes of the individual responses. In this article, we review results of recent experimental and theoretical studies of neuronal substrates and computational algorithms for decision processes. Computational algorithms and neuronal network models underlying decision processes Yutaka Sakai Hiroshi Okamoto Tomoki Fukai doi:10.1016/j.neunet.2006.05.034 Neural Networks, Vol. In Press, Corrected Proof 2006-08-31T10:00:55-00:00 Neural Networks In Press, Corrected Proof decision model reinforcement-learning