Identification of temporal targets for closed-loop personalized brain stimulation in psychiatry
Bibliographic record
Abstract
Sleep is far more than a period of inactivity; it is a dynamic state where complex neural rhythms unfold, providing critical insights into our overall health.These brain oscillations, which define various stages of sleep, are increasingly understood not only as markers of sleep architecture but also as key contributors to its restorative functions.Dr. Lustenberger and her team have pioneered innovative techniques, using both stationary and portable technologies to modulate brain oscillations during sleep via EEG-feedbackcontrolled auditory stimulation.This technique has been successfully applied in both controlled laboratory environments and in everyday home settings.Their work aims to unravel the role of sleep oscillations in brain and body processes, while paving the way for the development of non-invasive sleep interventions.In this talk, Dr. Lustenberger will provide an overview of how auditory stimulation can enhance the sleep oscillations characteristic of deep sleep, with implications for cardiovascular health.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".