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Rewarding and aversive effects of nicotine are segregated within the nucleus accumbens

2008· article· en· W2133414659 on OpenAlexaff
Laurie H. L. Sellings, Golriz Baharnouri, Lindsey E. McQuade, Paul B. S. Clarke

Bibliographic record

VenueEuropean Journal of Neuroscience · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNicotinic Acetylcholine Receptors Study
Canadian institutionsMcGill UniversityUniversity of Toronto
FundersUniversity of Pennsylvania
KeywordsNucleus accumbensNicotineNeurosciencePsychologyNicotine dependenceDopamine

Abstract

fetched live from OpenAlex

Forebrain dopamine plays a critical role in motivated behavior. According to the classic view, mesolimbic dopamine selectively guides behavior motivated by positive reinforcers. However, this has been challenged in favor of a wider role encompassing aversively motivated behavior. This controversy is particularly striking in the case of nicotine, with opposing claims that either the rewarding or the aversive effect of nicotine is critically dependent on mesolimbic dopamine transmission. In the present study, the effects of 6-hydroxydopamine lesions of nucleus accumbens core vs. medial shell on intravenous nicotine conditioned place preference and conditioned taste aversion were examined in male adult rats. Dopaminergic denervation in accumbens medial shell was associated with decreased nicotine conditioned place preference. Conversely, denervation in accumbens core was associated with an increase in conditioned place preference. In addition, dopaminergic denervation of accumbens core but not medial shell abolished conditioned taste aversion for nicotine. We conclude that nucleus accumbens core and medial shell dopaminergic innervation exert segregated effects on rewarding and aversive effects of nicotine. More generally, our findings indicate that dopaminergic transmission may mediate or enable opposing motivational processes within functionally distinct domains of the accumbens.

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 score0.163
Threshold uncertainty score0.306

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.015
GPT teacher head0.235
Teacher spread0.220 · 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

Citations75
Published2008
Admission routes1
Has abstractyes

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