Individual variation in incentive salience attribution and accumbens dopamine transporter expression and function
Bibliographic record
Abstract
Cues (conditioned stimuli; CSs) associated with rewards can come to motivate behavior, but there is considerable individual variation in their ability to do so. For example, a lever-CS that predicts food reward becomes attractive and wanted, and elicits reward-seeking behavior, to a greater extent in some rats ('sign-trackers'; STs) than others ('goal-trackers'; GTs). Variation in dopamine (DA) neurotransmission in the nucleus accumbens (NAc) core is thought to contribute to such individual variation. Given that the DA transporter (DAT) exerts powerful regulation over DA signaling, we characterized the expression and function of the DAT in the accumbens of STs and GTs. STs showed greater DAT surface expression in ventral striatal synaptosomes than GTs, and ex vivo fast-scan cyclic voltammetry recordings of electrically evoked DA release confirmed enhanced DAT function in STs, as indicated by faster DA uptake, specifically in the NAc core. Consistent with this, systemic amphetamine (AMPH) produced greater inhibition of DA uptake in STs than in GTs. Furthermore, injection of AMPH directly into the NAc core enhanced lever-directed approach in STs, presumably by amplifying the incentive value of the CS, but had no effect on goal-tracking behavior. On the other hand, there were no differences between STs and GTs in electrically-evoked DA release in slices, or in total ventral striatal DA content. We conclude that greater DAT surface expression may facilitate the attribution of incentive salience to discrete reward cues. Investigating this variability in animal sub-populations may help explain why some people abuse drugs while others do not.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".