A prospective code for value in the serotonin system

The in vivo responses of dorsal raphe nucleus serotonin neurons to emotionally salient stimuli are a puzzle<sup>1</sup>. Existing theories centring on reward<sup>2</sup>, surprise<sup>3</sup>, salience<sup>4</sup> and uncertainty<sup>5</sup> individually account for some aspects of serotonergic activity but not others. Merging ideas from reinforcement learning theory<sup>6</sup> with recent insights into the filtering properties of the dorsal raphe nucleus<sup>7</sup>, here we find a unifying perspective in a prospective code for value. This biological code for near-future reward explains why serotonin neurons are activated by both rewards and punishments<sup>3,4,8-13</sup>, and why these neurons are more strongly activated by surprising rewards but have no such surprise preference for punishments<sup>3,9</sup>-observations that previous theories have failed to reconcile. Finally, our model quantitatively predicts in vivo population activity better than previous theories. By reconciling previous theories and establishing a precise connection with reinforcement learning, our work represents an important step towards understanding the role of serotonin in learning and behaviour.

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Publication Details

Journal
Nature
Published
2025-03-26
DOI
https://doi.org/10.1038/s41586-025-08731-7
Citations
17
Primary Topic
Neurotransmitter Receptor Influence on Behavior
Type
article
Field-Weighted Citation Impact
15.45
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article

A prospective code for value in the serotonin system

Jeremiah Y. Cohen, Emerson F. Harkin, Cooper D. Grossman, Jean‐Claude Béïque et al.
17 citations
Nature
Neurotransmitter Receptor Influence on Behavior
15.45
article

A prospective code for value in the serotonin system

Jeremiah Y. Cohen, Emerson F. Harkin, Cooper D. Grossman, Jean‐Claude Béïque, Richard Naud
article en
17 citations

Abstract

The in vivo responses of dorsal raphe nucleus serotonin neurons to emotionally salient stimuli are a puzzle<sup>1</sup>. Existing theories centring on reward<sup>2</sup>, surprise<sup>3</sup>, salience<sup>4</sup> and uncertainty<sup>5</sup> individually account for some aspects of serotonergic activity but not others. Merging ideas from reinforcement learning theory<sup>6</sup> with recent insights into the filtering properties of the dorsal raphe nucleus<sup>7</sup>, here we find a unifying perspective in a prospective code for value. This biological code for near-future reward explains why serotonin neurons are activated by both rewards and punishments<sup>3,4,8-13</sup>, and why these neurons are more strongly activated by surprising rewards but have no such surprise preference for punishments<sup>3,9</sup>-observations that previous theories have failed to reconcile. Finally, our model quantitatively predicts in vivo population activity better than previous theories. By reconciling previous theories and establishing a precise connection with reinforcement learning, our work represents an important step towards understanding the role of serotonin in learning and behaviour.

NatureVol. 641(8064)
California Institute of Technology (US), Johns Hopkins University (US), University of Ottawa (CA), Discovery Institute (US), MIND Research Institute (US), General Dynamics (Canada) (CA), Max Planck Institute for Biological Cybernetics (DE), Allen Institute (US), Allen Institute for Neural Dynamics (US)
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Neurotransmitter Receptor Influence on Behavior
15.45
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