ArticleScientific reports2026
Disorder-specific alterations of transient oscillatory dynamics during sleep across cortical and subcortical networks.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- The DYNAM-O Toolbox: Characterizing Individualized Neural Signatures in Sleep EEG.bioRxiv : the preprint server for biology · 2026Article
- Narcolepsy: immunity, neural circuitry, and brain network reconfiguration.Frontiers in immunology · 2026Review
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17 authors.
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Abstract
Transient sleep oscillations reflect the dynamic coordination of cortical and subcortical circuits, modulated by slow oscillatory activity. However, the disorder-specific signatures of these events across neurological, pain, and sleep disorders remain poorly characterized. In this exploratory study, we analyzed transient oscillatory dynamics in 99 individuals, including healthy controls and patients with narcolepsy type 1, non-REM parasomnia, idiopathic REM sleep behavior disorder, and fibromyalgia syndrome. Using slow oscillatory referenced time-frequency peak histograms, we applied principal and independent component analysis to uncover spectral and phase-coupling patterns across non-REM and REM stages. We identified reproducible, trait-like oscillatory structures in controls and disorder-specific deviations in patient groups, particularly during NREM sleep. Specifically, patients with narcolepsy type 1 and non-REM parasomnia exhibited altered fast sigma coupling and phase dispersion, while idiopathic REM sleep behavior disorder patients showed reduced fast sigma density and diminished phase synchrony, despite retention of spindle-like spectral structure. In internal cross-validation, slow oscillatory-power features supported robust group-level discrimination in select EEG derivations; however, broader validation in independent samples is required. These findings highlight distinctive, stage-specific microstructural alterations in sleep and pain pathologies and support the future potential of time-frequency peak analysis as a non-invasive tool for phenotyping thalamocortical and subcortical circuit function.
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