Evidence map›Paper›PMID 41648485›Full record

ArticlebioRxiv : the preprint server for biology2026

Dopamine signatures of excessive and compulsive cocaine and fentanyl use.

Ke Chen, Hao Zheng, Gabrielle Sevrain, Wenxi Xiao, Charlotte Wang, Akili Sundai, Ila Fiete, Fan Wang

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Ke ChenDepartment of Brain and Cognitive Sciences, Massachusetts Institute of Technology; Cambridge, 02139, USA.ORCID 0009-0009-6948-0157
Hao ZhengDepartment of Brain and Cognitive Sciences, Massachusetts Institute of Technology; Cambridge, 02139, USA.
Gabrielle SevrainDepartment of Brain and Cognitive Sciences, Massachusetts Institute of Technology; Cambridge, 02139, USA.
Wenxi XiaoDepartment of Brain and Cognitive Sciences, Massachusetts Institute of Technology; Cambridge, 02139, USA.
Charlotte WangDepartment of Brain and Cognitive Sciences, Massachusetts Institute of Technology; Cambridge, 02139, USA.
Akili SundaiDepartment of Brain and Cognitive Sciences, Massachusetts Institute of Technology; Cambridge, 02139, USA.
Ila FieteDepartment of Brain and Cognitive Sciences, Massachusetts Institute of Technology; Cambridge, 02139, USA.ORCID 0000-0003-4738-2539
Fan WangDepartment of Brain and Cognitive Sciences, Massachusetts Institute of Technology; Cambridge, 02139, USA.

Funding

Viral ModuleP30EY012196 · NEI · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI MARGARET S LIVINGSTONE · 1998 to 2026
$21.3M
NEI NIH HHS P30 EY012196
6 · The paper itself

Abstract

Excessive and compulsive drug use despite adverse consequences is a hallmark of substance use disorder, yet individuals differ markedly in their vulnerability to develop these behaviors. Drugs of abuse are long known to alter endogenous dopamine (DA) signaling, but shared principles for how DA dynamics impact compulsive use among individuals and across drug classes are lacking. Here, we monitored DA release in the medial shell of nucleus accumbens (NAc) during cocaine and fentanyl self-administration, with or without coincident punishment, in large cohorts of mice. Contingent cocaine and fentanyl self-administration evoked complex and individually distinct DA dynamics; nevertheless, a robust negative correlation held across both drugs, such that high takers exhibited lower drug-evoked DA signals. During punished drug taking, cocaine and fentanyl cases were associated with distinct DA signatures of compulsivity. For cocaine, punishment-resistant mice showed lower sustained DA responses during the post-shock, drug-associated cue period, whereas for fentanyl, punishment-resistant mice displayed larger phasic DA at the co-occurrence of footshock and drug infusion. To identify common principles underlying these observations, we developed a computational model grounded in an Actor-Critic temporal-difference (TD) learning framework that incorporates internal states, agent's uncertainty, and drug-specific effects. Remarkably, this model captures the observed diversity in DA dynamics across drug classes and among mice with variable drug taking propensities, hereby providing a unified interpretation of NAc DA signals as encoding TD reward prediction errors.

Identifiers

PMID41648485
PMCPMC12871853

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.