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Intracerebral dynamics of sleep arousals: a combined scalp-intracranial EEG study

2024· article· en· W4392696379 on OpenAlexafffund
Yingqi Laetitia Wang, Tamir Avigdor, Sana Hannan, Chifaou Abdallah, François Dubeau, Laure Peter‐Derex, Birgit Frauscher

Bibliographic record

VenueJournal of Neuroscience · 2024
Typearticle
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersNatural Sciences and Engineering Research Council of CanadaUCB PharmaFonds de recherche du QuébecEisai
KeywordsStereoelectroencephalographyElectroencephalographyScalpPolysomnographyWakefulnessArousalSlow-wave sleepSleep (system call)Sleep StagesNeurosciencePsychologyNon-rapid eye movement sleepHippocampusAudiologyIctalAnesthesiaMedicineAnatomy

Abstract

fetched live from OpenAlex

As an intrinsic component of sleep architecture, sleep arousals represent an intermediate state between sleep and wakefulness and play an important role in sleep-wake regulation. They have been defined in an all-or-none manner, whereas they actually present a wide range of scalp-electroencephalography (EEG) activity patterns. It is poorly understood how these arousals differ in their mechanisms. Stereo-EEG (SEEG) provides the unique opportunity to record intracranial activities in superficial and deep structures in humans. Using combined polysomnography and SEEG, we quantitatively categorized arousals in non-rapid eye movement sleep into slow wave (SW) and Non-SW arousals based on whether they co-occurred with a scalp-EEG SW event. We then investigated their intracranial correlates in up to 26 brain regions from 26 patients (12 females). Across both arousal types, intracranial theta, alpha, sigma, and beta activities increased in up to 25 regions (p<0.05,d=0.06-0.63), while gamma and high frequency (HF) activities decreased in up to 18 regions across five brain lobes (p<0.05,d=0.06-0.44). Intracranial delta power widely increased across five lobes during SW arousals (p<0.05 in 22 regions,d=0.10-0.39), while it widely decreased during Non-SW arousals (p<0.05 in 19 regions,d=0.10-0.30). Despite these main patterns, unique activity was observed locally in some regions such as the hippocampus and middle cingulate cortex, indicating spatial heterogeneity of arousal responses. Our results suggest that Non-SW arousals correspond to a higher level of brain activation than SW arousals. The decrease in HF activities could potentially explain the absence of awareness and recollection during arousals. Significance StatementIntrinsic to sleep architecture, sleep arousals play an important role in sleep-wake regulation. They are defined in an all-or-none manner, whereas they actually present various scalp electroencephalography (EEG) patterns. Using simultaneous scalp and intracranial EEG in humans, we analyzed the intracranial activity during two types of arousals marked on scalp EEG, quantitatively categorized by whether they co-occurred with a scalp-EEG slow wave (SW). Non-SW arousals present prevalent low-voltage fast activity, while SW arousals exhibit high-voltage slow waves alongside fast activities. This work represents the first intracranial study of different types of NREM sleep arousals and provides a comprehensive description of local brain activities during both arousal types, serving as a foundation for future studies investigating regional behaviors during sleep-wake transition.

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)0.000
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.039
GPT teacher head0.329
Teacher spread0.290 · 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

Citations8
Published2024
Admission routes2
Has abstractyes

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