MétaCan
Menu
Back to cohort
Record W2055011705 · doi:10.4103/1463-1741.63216

Event-related potentials as a measure of sleep disturbance: A tutorial review

2010· review· en· W2055011705 on OpenAlexaff
Kenneth B. Campbell

Bibliographic record

VenueNoise and Health · 2010
Typereview
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsNon-rapid eye movement sleepP3aStimulus (psychology)AudiologyPsychologyElectroencephalographyK-complexEvent-related potentialWakefulnessSleep spindleNeuroscienceCognitive psychologyMedicine

Abstract

fetched live from OpenAlex

This article reviews event-related potentials (ERPs) the minute responses of the human brain that are elicited by external auditory stimuli and how the ERPs can be used to measure sleep disturbance. ERPs consist of a series of negative- and positive-going components. A negative component peaking at about 100 ms, N1, is thought to reflect the outcome of a transient detector system, activated by change in the transient energy in an acoustic stimulus. Its output and thus the amplitude of N1 increases as the intensity level of the stimulus is increased and when the rate of presentation is slowed. When the output reaches a certain critical level, operations of the central executive are interrupted and attention is switched to the auditory channel. This switching of attention is thought to be indexed by a later positivity, P3a, peaking between 250 and 300 ms. In order to sleep, consciousness for all but the most relevant of stimuli must be prevented. Thus, during sleep onset and definitive non-rapid eye movement (NREM) sleep, the amplitude of N1 diminishes to near-baseline level. The amplitude of P2, peaking from 180 to 200 ms, is however larger in NREM sleep than in wakefulness. P2 is thought to reflect an inhibitory process protecting sleep from irrelevant disturbance. As stimulus input becomes increasingly obtrusive, the amplitude of P2 also increases. With increasing obtrusiveness particularly when stimuli are presented slowly, a later large negativity, peaking at about 350 ms, N350, becomes apparent. N350 is unique to sleep, its amplitude also increasing as the stimulus becomes more obtrusive. Many authors postulate that when the N350 reaches a critical amplitude, a very large amplitude N550, a component of the K-Complex is elicited. The K-Complex can only be elicited during NREM sleep. The P2, N350 and N550 processes are thus conceived as sleep protective mechanisms, activated sequentially as the risk for disturbance increases. During REM sleep, the transient detector system again becomes somewhat activated, the amplitude of N1 reaching from 15 to 40% of its waking level. Very intense and/or very infrequently presented stimuli might elicit a P3-like deflection suggesting an intrusion into some aspect of consciousness. The types of experimental paradigms used in most ERP studies are quite different from those used in the study of noise and its effects on sleep. ERP studies will need to employ procedures that have greater ecological generalization; stimulus intensity needs to be lower, less abrupt, with much longer durations, and importantly, stimuli should be presented much less often.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.003
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.003

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.

Opus teacher head0.094
GPT teacher head0.406
Teacher spread0.312 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations23
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueNoise and HealthSame topicNeuroscience and Music PerceptionFrench-language works237,207