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Record W4394933472 · doi:10.1126/science.adk6742

Drugs of abuse hijack a mesolimbic pathway that processes homeostatic need

2024· article· en· W4394933472 on OpenAlexaff
Bowen Tan, Caleb J. Browne, Tobias Nöbauer, Alipasha Vaziri, Jeffrey M. Friedman, Eric J. Nestler

Bibliographic record

VenueScience · 2024
Typearticle
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsCentre for Addiction and Mental Health
FundersNational Institute on Drug AbuseNational Institute of Neurological Disorders and StrokeHoward Hughes Medical InstituteNational Institutes of HealthNational Science Foundation
KeywordsNeurosciencePsychology

Abstract

fetched live from OpenAlex

Drugs of abuse are thought to promote addiction in part by “hijacking” brain reward systems, but the underlying mechanisms remain undefined. Using whole-brain FOS mapping and in vivo single-neuron calcium imaging, we found that drugs of abuse augment dopaminoceptive ensemble activity in the nucleus accumbens (NAc) and disorganize overlapping ensemble responses to natural rewards in a cell type–specific manner. Combining FOS-Seq, CRISPR-perturbation, and single-nucleus RNA sequencing, we identified Rheb as a molecular substrate that regulates cell type–specific signal transduction in NAc while enabling drugs to suppress natural reward consumption. Mapping NAc-projecting regions activated by drugs of abuse revealed input-specific effects on natural reward consumption. These findings characterize the dynamic, molecular and circuit basis of a common reward pathway, wherein drugs of abuse interfere with the fulfillment of innate needs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.531

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.048
GPT teacher head0.317
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations56
Published2024
Admission routes1
Has abstractyes

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