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  Tamping Ramping: Algorithmic, Implementational, and Computational Explanations of Phasic Dopamine Signals in the Accumbens

Lloyd, K., & Dayan, P. (2015). Tamping Ramping: Algorithmic, Implementational, and Computational Explanations of Phasic Dopamine Signals in the Accumbens. PLoS Computational Biology, 11(12), 1-34. doi:10.1371/journal.pcbi.1004622.

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Lloyd, K, Author              
Dayan, P1, Author              
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1External Organizations, ou_persistent22              

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 Abstract: Substantial evidence suggests that the phasic activity of dopamine neurons represents reinforcement learning's temporal difference prediction error. However, recent reports of ramp-like increases in dopamine concentration in the striatum when animals are about to act, or are about to reach rewards, appear to pose a challenge to established thinking. This is because the implied activity is persistently predictable by preceding stimuli, and so cannot arise as this sort of prediction error. Here, we explore three possible accounts of such ramping signals: (a) the resolution of uncertainty about the timing of action; (b) the direct influence of dopamine over mechanisms associated with making choices; and (c) a new model of discounted vigour. Collectively, these suggest that dopamine ramps may be explained, with only minor disturbance, by standard theoretical ideas, though urgent questions remain regarding their proximal cause. We suggest experimental approaches to disentangling which of the proposed mechanisms are responsible for dopamine ramps.

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 Dates: 2015-12
 Publication Status: Published in print
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 Identifiers: DOI: 10.1371/journal.pcbi.1004622
eDoc: e1004622
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Title: PLoS Computational Biology
Source Genre: Journal
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Publ. Info: San Francisco, CA : Public Library of Science
Pages: - Volume / Issue: 11 (12) Sequence Number: - Start / End Page: 1 - 34 Identifier: ISSN: 1553-734X
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000017180_1