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Record W2608407040 · doi:10.1093/sleepj/zsx050.091

0092 INFORMATION PROCESSING DURING SLEEP AND SLEEP MISPERCEPTION IN INSOMNIA: AN ERP STUDY.

2017· article· en· W2608407040 on OpenAlexaff
Jessica Lebel, C.H. Bastien

Bibliographic record

VenueSLEEP · 2017
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPsychologySleep onsetModerationAudiologyInformation processingVigilance (psychology)InsomniaOddball paradigmEvent-related potentialDevelopmental psychologyCognitionCognitive psychologyPsychiatrySocial psychologyMedicine

Abstract

fetched live from OpenAlex

Hyperarousal is linked to sleep misperception, which is especially present in paradoxical insomnia (PARA-I). ERP studies showed that hyperarousal can be expressed through enhanced information processing, which is different between PARA-I and psychophysiological insomnia (PSY-I). Our objective is to use ERPs to investigate the link between misperception and information processing. Specifically, N1 (vigilance) and P2 (inhibition) were chosen for information processing and sleep onset latency (SOL) and wake after sleep onset (WASO) were used for misperception. Our hypothesis is that the link between misperception and information processing will be stronger for PARA-I than for PSY-I and good sleepers (GS). 50 GS (age 34.7 ± 9.0), 40 PSY-I (40.9 ± 9.1) and 29 PARA-I (39.41 ± 9.2) underwent four PSG nights. Subjective and objective sleep measures were obtained for SOL and WASO. ERPs were recorded all night on Night 4 (oddball paradigm). A linear mixed model including 3 within-subject factors (peak, N1 and P2; auditory stimuli, standard and deviant; recording time, S2E, S2L, SWS, REM), 3 between-subject independent factors (group, GS, PARA-I, PSY-I; SOL and WASO misperception, over, good, under) was computed on amplitude data at Cz. Misperception was calculated as the difference between subjective and objective measures. Results revealed no differences between groups for information processing (p = 0.451). However, the interaction effect group x peak, (p=0.004), showed that P2 was higher in PARA-I. There was no moderator effect of group on the link between misperception and hyperarousal (p=0.769, p=0.440). A higher P2 in PARA-I would indicate that they need to deploy more energy to inhibit information processing, which would explain their greater misperception. Knowing that hyperarousal is a 24-hour problem, daytime ERPs should be investigated in connexion with sleep misperception. No group moderation effect means that the link between misperception and hyperarousal stays stable across sleep types. Consequently, mechanisms linking sleep misperception and hyperarousal appear similar for each group. -

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.515
Threshold uncertainty score0.834

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.301
Teacher spread0.288 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2017
Admission routes1
Has abstractyes

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