What dopamine teaches depends on what the brain believes.

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Title: What dopamine teaches depends on what the brain believes.
Authors: Bano, Eleonora (AUTHOR), Ryu, Steven (AUTHOR), Kepecs, Adam (AUTHOR)
Source: Nature Neuroscience. Jun2025, Vol. 28 Issue 6, p1121-1123. 3p.
Abstract: How does the brain learn to predict rewards? In this issue of Nature Neuroscience, Qian, Burrell et al. show that understanding how dopamine guides learning requires knowledge of how animals interpret tasks — what they believe is happening and when. By carefully manipulating cue–reward contingencies, the authors show that dopamine responses track belief-state reward prediction errors. These findings reaffirm — against recent challenges — that mesolimbic dopamine neurons signal prediction errors in line with the temporal difference learning rule, a core algorithm that bridges neuroscience and artificial intelligence. [ABSTRACT FROM AUTHOR]
Copyright of Nature Neuroscience is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: How does the brain learn to predict rewards? In this issue of Nature Neuroscience, Qian, Burrell et al. show that understanding how dopamine guides learning requires knowledge of how animals interpret tasks — what they believe is happening and when. By carefully manipulating cue–reward contingencies, the authors show that dopamine responses track belief-state reward prediction errors. These findings reaffirm — against recent challenges — that mesolimbic dopamine neurons signal prediction errors in line with the temporal difference learning rule, a core algorithm that bridges neuroscience and artificial intelligence. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Nature Neuroscience is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: Jun2025
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