Zona Incerta Suppressed Escape During Hunger
Bibliographic record
Abstract
Wild animals must avoid starvation and predators to survive. However, the motivation to seek food and shelter promote opposing behaviors and require rapid neural adaptations that are poorly understood. The zona incerta (ZI) is a specialized region that integrates multisensory input, projects strongly to motor-related regions, and can thus initiate escape from threats to survive. One subset of medial ZI neurons producing dopamine (DA) and gamma-aminobutyric acid (GABA) send dense projections to the medial motor-related superior colliculus (SCm), which promotes escape from threats in the upper visual field. We determined whether ZI-GABA/DA cells respond to hunger and investigated whether activating ZI-GABA/DA cells in hungry mice suppressed escape. We transduced ZI-GABA/DA cells with an excitatory chemogenetic receptor hM3(Dq) and found that stimulating their projections in the medial SCm suppressed escape from an upper visual threat in male and female mice. Interestingly, fasting activated ZI-GABA/DA cells and enhanced hM3(Dq)-mediated escape suppression. To evaluate the contribution of GABA and/or DA in escape suppression, we co-infused a cocktail of DA or GABA receptor antagonists, respectively. Both GABA and DA are required to suppress escape in fasted male mice, but DA independently suppressed escape in female mice. Activation of ZI-GABA/DA cells did not impact locomotor or any anxiety-related functions but uniquely integrated hunger signals to suppress escape. Our findings suggested that the ZI-SCm neurocircuit is sexually dimorphic and that the ZI is a critical node regulating the competition between the need to seek food and shelter.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".