Isolating Neural Correlates of the Pacemaker for Food Anticipation
Bibliographic record
Abstract
Mice fed a single daily meal at intervals within the circadian range exhibit food anticipatory activity. Previous investigations strongly suggest that this behaviour is regulated by a circadian pacemaker entrained to the timing of fasting/refeeding. The neural correlate(s) of this pacemaker, the food entrainable oscillator (FEO), whether found in a neural network or a single locus, remain unknown. This study used a canonical property of circadian pacemakers, the ability to continue oscillating after removal of the entraining stimulus, to isolate activation within the neural correlates of food entrainable oscillator from all other mechanisms driving food anticipatory activity. It was hypothesized that continued anticipatory activation of central nuclei, after restricted feeding and a return to ad libitum feeding, would elucidate a neural representation of the signaling circuits responsible for the timekeeping component of the food entrainable oscillator. Animals were entrained to a temporally constrained meal then placed back on ad libitum feeding for several days until food anticipatory activity was abolished. Activation of nuclei throughout the brain was quantified using stereological analysis of c-FOS expressing cells and compared against both ad libitum fed and food entrained controls. Several hypothalamic and brainstem nuclei remained activated at the previous time of food anticipation, implicating them in the timekeeping mechanism necessary to track previous meal presentation. This study also provides a proof of concept for an experimental paradigm useful to further investigate the anatomical and molecular substrates of the FEO.
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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) | 0.000 | 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".