Effects of bilateral anterior agranular insula lesions on food anticipatory activity in rats
Bibliographic record
Abstract
Food anticipatory activity (FAA) refers to a daily rhythm of locomotor activity that emerges under conditions of food restriction, whereby animals develop an intense, predictable period of activity in the few hours leading up to a predictable, daily delivery of food. The neural mechanisms by which FAA is regulated are not yet fully understood. Although a number of brain regions appear to be involved in regulating the development and expression of FAA, there is little evidence to date concerning the role of the anterior agranular insular cortex (AICa). The AICa plays a critical role in integrating the perception of visceral states with motivational behaviour such as feeding. We assessed the effect of bilateral electrolytic or ibotenic acid lesions of the AICa on FAA in male Wistar rats receiving food for varying lengths of time (2 h, 3 h, or 5 h) during the middle of the light phase (starting at either ZT4 or ZT6). Contrary to our initial expectations, we found that both electrolytic and ibotenic acid lesions significantly increased, rather than decreased, the amount of FAA expressed in lesioned rats. Despite increased FAA, lesioned rats did not eat significantly more during restricted feeding (RF) periods than control rats. Similar to controls, AlCa-lesioned rats showed negligible anticipatory activity to a restricted treat suggesting that the increased anticipatory activity in lesioned rats is associated with food restriction, rather than the appetitive value of the meal. Monitoring behaviour in an open field indicated that increased FAA in AlCa-lesioned rats was not explained by a general increase in locomotor activity. Together, these findings suggest that the AICa contributes to the network of brain regions involved in FAA.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".