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A Unified Framework for Dopamine Signals across Timescales

Cell, 2020-12, Vol.183 (6), p.1600-1616.e25 [Peer Reviewed Journal]

2020 Elsevier Inc. ;Copyright © 2020 Elsevier Inc. All rights reserved. ;ISSN: 0092-8674 ;EISSN: 1097-4172 ;DOI: 10.1016/j.cell.2020.11.013 ;PMID: 33248024

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Title:
A Unified Framework for Dopamine Signals across Timescales
Author: Kim, HyungGoo R. ; Malik, Athar N. ; Mikhael, John G. ; Bech, Pol ; Tsutsui-Kimura, Iku ; Sun, Fangmiao ; Zhang, Yajun ; Li, Yulong ; Watabe-Uchida, Mitsuko ; Gershman, Samuel J. ; Uchida, Naoshige
Subjects: Action Potentials - physiology ; Animals ; Axons - metabolism ; Calcium - metabolism ; Calcium Signaling ; Cell Body - metabolism ; Cues ; Dopamine - metabolism ; Dopaminergic Neurons - physiology ; Fluorometry ; Male ; Mice, Inbred C57BL ; Models, Neurological ; Photic Stimulation ; Reward ; Sensation ; Signal Transduction ; Time Factors ; Ventral Tegmental Area - metabolism ; Virtual Reality
Is Part Of: Cell, 2020-12, Vol.183 (6), p.1600-1616.e25
Description: Rapid phasic activity of midbrain dopamine neurons is thought to signal reward prediction errors (RPEs), resembling temporal difference errors used in machine learning. However, recent studies describing slowly increasing dopamine signals have instead proposed that they represent state values and arise independent from somatic spiking activity. Here we developed experimental paradigms using virtual reality that disambiguate RPEs from values. We examined dopamine circuit activity at various stages, including somatic spiking, calcium signals at somata and axons, and striatal dopamine concentrations. Our results demonstrate that ramping dopamine signals are consistent with RPEs rather than value, and this ramping is observed at all stages examined. Ramping dopamine signals can be driven by a dynamic stimulus that indicates a gradual approach to a reward. We provide a unified computational understanding of rapid phasic and slowly ramping dopamine signals: dopamine neurons perform a derivative-like computation over values on a moment-by-moment basis. [Display omitted] •Temporal difference (TD) error is a powerful teaching signal in machine learning•Teleport and speed manipulations are used to characterize dopamine signals in mice•Slowly ramping as well as phasic dopamine responses convey TD errors•Dopamine neurons compute TD error or changes in value on a moment-by-moment basis Examination of dopamine circuit activity and striatal dopamine concentrations in mice experiencing virtual reality teleportation and speed manipulation reveals that rapid phasic and slowly ramping dopamine signals compute changes in value on a moment-by-moment basis.
Publisher: United States: Elsevier Inc
Language: English
Identifier: ISSN: 0092-8674
EISSN: 1097-4172
DOI: 10.1016/j.cell.2020.11.013
PMID: 33248024
Source: Cell Press Free Archives
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A Unified Framework for Dopamine Signals across Timescales

2020 Elsevier Inc. ;Copyright © 2020 Elsevier Inc. All rights reserved. ;ISSN: 0092-8674 ;EISSN: 1097-4172 ;DOI: 10.1016/j.cell.2020.11.013 ;PMID: 33248024

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