Event‐related potential measures of the disruptive effects of trains of auditory stimuli during waking and sleeping states
Bibliographic record
Abstract
Acoustic backup alarms have been reported to particularly disrupt sleep. The present study simulated backup alarms by presenting trains of five consecutive 500 ms duration audible tones, with the time between the onset of each tone being 1 s and the time between trains (offset to onset) between 15 and 20 s. In different conditions, the tones were set at either 80 or 60 dB sound pressure level (SPL). Twelve young adults spent two consecutive nights in the laboratory. Stimuli were presented only on the second night. Measures of traditional sleep architecture (sleep stages) were not affected by the acoustic trains. Event-related potentials were also measured following presentation of the stimuli. In the waking state, the initial 80 dB stimulus elicited a large amplitude N1, peaking at about 100 ms, followed by a positive peak, P3, peaking at about 325 ms. N1 was attenuated following presentation of the 60 dB stimulus. The amplitude of N1 was much reduced following presentation of the subsequent second to fifth stimuli in the train. During non-rapid eye movement (NREM) sleep, the initial 80 dB stimulus elicited a large and later negativity (N350) that was reduced in amplitude for the 60 dB stimulus. A K-Complex (a composite N350 and a much larger N550) was elicited following 35% of the initial 80 dB tones and 12% of the initial 60 dB tones. The amplitude of N550 did not, however, significantly vary as a function of stimulus SPL. During REM sleep, N1 continued to be elicited by the initial louder stimulus, but the later positive wave was not apparent. A late negativity peaking at about 350 ms was, however, apparent. When queried the next morning, subjects rarely indicated that the stimulus presentations disturbed their sleep. This might be because of the absence of the late positivity. The presence of the long latency negativities (N350 and N550) might serve to protect sleep from obtrusive sound during sleep.
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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 | 0.001 |
| 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) | 0.001 | 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".