Amygdala Lesions Reduce Cataplexy in Orexin Knock-Out Mice
Bibliographic record
Abstract
Narcolepsy is characterized by excessive sleepiness and cataplexy, sudden episodes of muscle weakness during waking that are thought to be an intrusion of rapid eye movement sleep muscle atonia into wakefulness. One of the most striking aspects of cataplexy is that it is often triggered by strong, generally positive emotions, but little is known about the neural pathways through which positive emotions trigger muscle atonia. We hypothesized that the amygdala is functionally important for cataplexy because the amygdala has a role in processing emotional stimuli and it contains neurons that are active during cataplexy. Using anterograde and retrograde tracing in mice, we found that GABAergic neurons in the central nucleus of the amygdala heavily innervate neurons that maintain waking muscle tone such as those in the ventrolateral periaqueductal gray, lateral pontine tegmentum, locus ceruleus, and dorsal raphe. We then found that bilateral, excitotoxic lesions of the amygdala markedly reduced cataplexy in orexin knock-out mice, a model of narcolepsy. These lesions did not alter basic sleep-wake behavior but substantially reduced the triggering of cataplexy. Lesions also reduced the cataplexy events triggered by conditions associated with high arousal and positive emotions (i.e., wheel running and chocolate). These observations demonstrate that the amygdala is a functionally important part of the circuitry underlying cataplexy and suggest that increased amygdala activity in response to emotional stimuli could directly trigger cataplexy by inhibiting brainstem regions that suppress muscle atonia.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".