Human amygdala activation during rapid eye movements of rapid eye movement sleep: an intracranial study
Bibliographic record
Abstract
The amygdaloid complex plays a crucial role in processing emotional signals and in the formation of emotional memories. Neuroimaging studies have shown human amygdala activation during rapid eye movement sleep (REM). Stereotactically implanted electrodes for presurgical evaluation in epileptic patients provide a unique opportunity to directly record amygdala activity. The present study analysed amygdala activity associated with REM sleep eye movements on the millisecond scale. We propose that phasic activation associated with rapid eye movements may provide the amygdala with endogenous excitation during REM sleep. Standard polysomnography and stereo-electroencephalograph (SEEG) were recorded simultaneously during spontaneous sleep in the left amygdala of four patients. Time-frequency analysis and absolute power of gamma activity were obtained for 250 ms time windows preceding and following eye movement onset in REM sleep, and in spontaneous waking eye movements in the dark. Absolute power of the 44-48 Hz band increased significantly during the 250 ms time window after REM sleep rapid eye movements onset, but not during waking eye movements. Transient activation of the amygdala provides physiological support for the proposed participation of the amygdala in emotional expression, in the emotional content of dreams and for the reactivation and consolidation of emotional memories during REM sleep, as well as for next-day emotional regulation, and its possible role in the bidirectional interaction between REM sleep and such sleep disorders as nightmares, anxiety and post-traumatic sleep disorder. These results provide unique, direct evidence of increased activation of the human amygdala time-locked to REM sleep rapid eye movements.
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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".