Changes in nucleus accumbens dopamine transmission associated with fixed‐ and variable‐time schedule‐induced feeding
Bibliographic record
Abstract
We examined the changes in nucleus accumbens (NAcc) dopamine (DA) transmission associated with non-contingent meal presentations under conditions of high (fixed time-, FT-schedule) and low (variable time-, VT-schedule) predictability. Of interest were the changes in NAcc DA transmission associated with discrepancies between the time food is expected and when it is actually presented. We used in vivo voltammetry to monitor NAcc DA levels as rats received, on the first and second test days, 30-s meals of condensed milk on a VT-52 schedule (inter-meal intervals of 32, 35, 40, 45, 52, 64, and 95 s). On the third and subsequent days meals were presented first on a VT-52 s schedule and then on an FT-52 s schedule. On day 1, monotonic increases in NAcc DA signals were observed during both meal consumption and the intervals between VT meal presentations. By day 2, however, meal presentations on the VT schedule elicited biphasic DA signal fluctuations; DA signals increased prior to each meal presentation but then started to decline during the feeding bout that followed. Fixed-time meal presentations on day 3 disrupted this pattern, resulting in a concurrent escalation of DA signal fluctuations upon subsequent VT meal presentations. These findings provide further evidence that, in trained animals, NAcc DA transmission is activated by conditioned incentive cues rather than by primary rewards. They also suggest that the increases in NAcc DA transmission associated with reward expectancy are sensitive to temporal cues (e.g. interval timing) and to discrepancies between expected and actual outcomes.
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 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 | 0.001 |
| 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".