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Record W2135148159 · doi:10.1093/brain/awh425

Atypical sleep architecture and the autism phenotype

2005· article· en· W2135148159 on OpenAlexafffund
Élyse Limoges, Laurent Mottron, Christianne Bolduc, Claude Berthiaume, Roger Godbout

Bibliographic record

VenueBrain · 2005
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsUniversité de MontréalHôpital Rivière-des-Prairies
FundersCanadian Institutes of Health Research
KeywordsAutismSleep architectureSleep (system call)Genetic architecturePhenotypePsychologyNeuroscienceMedicinePsychiatryGeneticsPolysomnographyBiologyElectroencephalographyComputer scienceGene

Abstract

fetched live from OpenAlex

A growing body of evidence indicates that people with autism frequently experience sleep disorders and exhibit atypical sleep architecture. In order to establish whether sleep disorders truly belong to the autism spectrum disorder (ASD) phenotype, we conducted a subjective and objective study of sleep in a group of high-functioning adults with ASD but without sleep complaints, psychiatric disorders or neurological comorbidity. We compared the subjective data of 27 ASD participants with those of 78 healthy controls matched for chronological age and gender. Subjective measures of sleep in the clinical group were compatible with insomnia and/or a tolerable phase advance of the sleep-wake cycle. Subjective data were confirmed by objective laboratory sleep recordings in a subset of 16 patients and 16 controls. Persons with autism presented with a longer sleep latency (P < 0.04), more frequent nocturnal awakenings (P < 0.03), lower sleep efficiency (P < 0.03), increased duration of stage 1 sleep (P < 0.02), decreased non-REM sleep (stages 2 + 3 + 4, P < 0.04) and slow-wave sleep (stages 3 + 4, P < 0.05), fewer stage 2 EEG sleep spindles (P < 0.004), and a lower number of rapid eye movements during REM sleep (P < 0.006) than did control participants. On clinical scales, the scores of persons with ASD on the Beck Depression Inventory were similar to those of persons without, but their trait anxiety scores on the Spielberger Anxiety Scale were higher (P < 0.02). The state anxiety scores of the Spielberger scale and cortisol levels were the same in the two groups. Objective total sleep time correlated negatively with the Social (-0.52, P < 0.05) and Communication (-0.54, P < 0.02) scales of the Autism Diagnostic Interview-Revised. The sleep of clinical subgroups (10 with high-functioning autism, six with Asperger syndrome) did not differ, except for the presence of fewer EEG sleep spindles in the Asperger syndrome subgroup (P < 0.05). In conclusion, these findings indicate that atypicalities of sleep constitute a salient feature of the adult ASD phenotype and this should be further investigated in younger patients. Moreover, the results are consistent with an atypical organization of neural networks subserving the macro- and microstructure of sleep in ASD. We are furthering this research with quantified analysis of sleep EEG.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.272
Teacher spread0.257 · 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 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

Citations347
Published2005
Admission routes2
Has abstractyes

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