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Record W3012290332 · doi:10.1016/j.celrep.2020.02.095

Nucleus Accumbens Cell Type- and Input-Specific Suppression of Unproductive Reward Seeking

2020· article· en· W3012290332 on OpenAlexafffund
Christopher K. Lafferty, Angela K. Yang, Jesse A. Mendoza, Jonathan P. Britt

Bibliographic record

VenueCell Reports · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReceptor Mechanisms and Signaling
Canadian institutionsMcGill University Health CentreConcordia UniversityMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchCanada Foundation for Innovation
KeywordsNucleus accumbensNeuroscienceAmygdalaStimulationBrain stimulation rewardCell typePsychologyBiologyCellDopamine

Abstract

fetched live from OpenAlex

The nucleus accumbens (NAc) contributes to behavioral inhibition and compulsions, but circuit mechanisms are unclear. Recent evidence suggests that amygdala and thalamic inputs exert opposing control over behavior, much like direct and indirect pathway output neurons. Accordingly, opponent processes between these NAc inputs or cell types may underlie efficient reward seeking. We assess the contributions of these circuit elements to mouse operant behavior during recurring conditions when reward is and is not available. Although direct pathway stimulation is rewarding and indirect pathway stimulation aversive, the activity of both cell types is elevated during periods of behavioral suppression, and the inhibition of either cell-type selectively increases unproductive reward seeking. Amygdala and thalamic inputs are also necessary for behavioral suppression, even though they both support self-stimulation and innervate different NAc subregions. These data suggest that efficient reward seeking relies on complementary activity across NAc cell types and inputs rather than opponent processes between them.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.055
Threshold uncertainty score0.432

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.224
Teacher spread0.209 · 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

Citations87
Published2020
Admission routes2
Has abstractyes

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