# Disorder-specific alterations of transient oscillatory dynamics during sleep across cortical and subcortical networks

## TL;DR

The study explores how sleep oscillations differ in people with various sleep and neurological disorders, revealing distinct patterns that could help diagnose and understand these conditions.

## Contribution

The study introduces a novel approach using time-frequency peak histograms to identify disorder-specific alterations in sleep oscillatory dynamics.

## Key findings

- Narcolepsy type 1 and non-REM parasomnia patients showed altered fast sigma coupling and phase dispersion.
- Idiopathic REM sleep behavior disorder patients exhibited reduced fast sigma density and diminished phase synchrony.
- Slow oscillatory-power features enabled robust group-level discrimination in select EEG derivations.

## 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.

The online version contains supplementary material available at 10.1038/s41598-025-33669-1.