Evidence map›Paper›PMID 37662243›Full record

ArticlebioRxiv : the preprint server for biology2023

Dorsal raphe neurons signal integrated value during multi-attribute decision-making.

Yang-Yang Feng, Ethan S Bromberg-Martin, Ilya E Monosov

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Yang-Yang FengDepartment of Neuroscience, Washington University School of Medicine, St. Louis, Missouri, USA.
Ethan S Bromberg-MartinDepartment of Neuroscience, Washington University School of Medicine, St. Louis, Missouri, USA.
Ilya E MonosovDepartment of Neuroscience, Washington University School of Medicine, St. Louis, Missouri, USA.

Funding

MECHANISMS OF INFORMATION SEEKING IN THE PRIMATE BRAINR01MH116937 · NIMH · WASHINGTON UNIVERSITY · PI Ilya E. Monosov · 2019 to 2026
$4.0M
Neural Circuits that Regulate Risk SeekingR01MH110594 · NIMH · WASHINGTON UNIVERSITY · PI Ilya E. Monosov · 2017 to 2026
$3.9M
Neuronal mechanisms of novelty seekingR01MH128344 · NIMH · WASHINGTON UNIVERSITY · PI Ilya E. Monosov · 2022 to 2026
$1.9M
Determining the role of the primate raphe-habenula circuit in multi-attribute decision-makingF30MH130103 · NIMH · WASHINGTON UNIVERSITY · PI FENG, YAN-YANG · 2022 to 2024
$158k
INTERFERONS IN AUTOIMMUNE ASSOCIATED-AVOIDANCE LEARNINGF32MH010643 · NIMH · UNIVERSITY OF COLORADO DENVER · PI SCHROTT, LISA M · 1993 to 1995
–
NIMH NIH HHS F30 MH130103NIMH NIH HHS F32 MH010643NIMH NIH HHS R01 MH110594NIMH NIH HHS R01 MH116937NIMH NIH HHS R01 MH128344
6 · The paper itself

Abstract

The dorsal raphe nucleus (DRN) is implicated in psychiatric disorders that feature impaired sensitivity to reward amount, impulsivity when facing reward delays, and risk-seeking when grappling with reward uncertainty. However, whether and how DRN neurons signal reward amount, reward delay, and reward uncertainty during multi-attribute value-based decision-making, where subjects consider all these attributes to make a choice, is unclear. We recorded DRN neurons as monkeys chose between offers whose attributes, namely expected reward amount, reward delay, and reward uncertainty, varied independently. Many DRN neurons signaled offer attributes. Remarkably, these neurons commonly integrated offer attributes in a manner that reflected monkeys' overall preferences for amount, delay, and uncertainty. After decision-making, in response to post-decision feedback, these same neurons signaled signed reward prediction errors, suggesting a broader role in tracking value across task epochs and behavioral contexts. Our data illustrate how DRN participates in integrated value computations, guiding theories of DRN in decision-making and psychiatric disease.

Identifiers

PMID37662243
PMCPMC10473596

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.