Interaction between hypothalamic dorsomedial nucleus and the suprachiasmatic nucleus determines intensity of food anticipatory behavior
Bibliographic record
Abstract
Food anticipatory behavior (FAA) is induced by limiting access to food for a few hours daily. Animals anticipate this scheduled meal event even without the suprachiasmatic nucleus (SCN), the biological clock. Consequently, a food-entrained oscillator has been proposed to be responsible for meal time estimation. Recent studies suggested the dorsomedial hypothalamus (DMH) as the site for this food-entrained oscillator, which has led to considerable controversy in the literature. Herein we demonstrate by means of c-Fos immunohistochemistry that the neuronal activity of the suprachiasmatic nucleus (SCN), which signals the rest phase in nocturnal animals, is reduced when animals anticipate the scheduled food and, simultaneously, neuronal activity within the DMH increases. Using retrograde tracing and confocal analysis, we show that inhibition of SCN neuronal activity is the consequence of activation of GABA-containing neurons in the DMH that project to the SCN. Next, we show that DMH lesions result in a loss or diminution of FAA, simultaneous with increased activity in the SCN. A subsequent lesion of the SCN restored FAA. We conclude that in intact animals, FAA may only occur when the DMH inhibits the activity of the SCN, thus permitting locomotor activity. As a result, FAA originates from a neuronal network comprising an interaction between the DMH and SCN. Moreover, this study shows that the DMH-SCN interaction may serve as an intrahypothalamic system to gate activity instead of rest overriding circadian predetermined temporal patterns.
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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".