| Paper: | GS-2.2 | ||
| Session: | Contributed Talks 3-4 | ||
| Location: | H0104 | ||
| Session Time: | Saturday, September 14, 11:50 - 12:30 | ||
| Presentation Time: | Saturday, September 14, 12:10 - 12:30 | ||
| Presentation: | Oral | ||
| Publication: | 2019 Conference on Cognitive Computational Neuroscience, 13-16 September 2019, Berlin, Germany | ||
| Paper Title: | Model-based value in midbrain dopamine signals | ||
| Manuscript: | Click here to view manuscript | ||
| View Video: | Video | ||
| License: |  This work is licensed under a Creative Commons Attribution 3.0 Unported License. |
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| DOI: | https://doi.org/10.32470/CCN.2019.1375-0 | ||
| Authors: | Marta Blanco Pozo, Thomas Akam, Timothy E. Behrens, Mark E. Walton, University of Oxford, United Kingdom | ||
| Abstract: | Midbrain dopamine activity is thought to represent reward prediction errors (RPEs) used to update the value of stimuli and/or actions. However, it remains unclear what sources of value information are available to dopamine neurons, and to what extent values derived from internal models inform dopaminergic RPEs. To assess how midbrain dopamine activity is influenced by internal models of task structure, we trained mice in a multi-step probabilistic decision-making task with changing reward contingencies, and performed photometry recordings from dopamine neurons in the ventral tegmental area (VTA) and dopamine axons in the nucleus accumbens (NAc) and dorsomedial striatum (DMS). Our results indicate that dopamine activity in VTA and NAc terminals is influenced by value information derived from models of task structure. By contrast, value information was absent from activity in DMS dopamine axons, which instead is strongly modulated when making choices towards the option contralateral to the recording site. | ||