Spectral dynamics prior to motor events differ between NREM sleep parasomnias and healthy sleepers.

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Tác giả: Spyros Balafas, Giulia Balella, Chiara Brombin, Anna Castelnovo, Clelia Di Serio, Giuseppe Loddo, Greta Mainieri, Mauro Manconi, Angelica Montini, Federica Provini

Ngôn ngữ: eng

Ký hiệu phân loại: 978.02 1800–1899

Thông tin xuất bản: United States : Sleep , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 688354

STUDY OBJECTIVES: The umbrella term "Disorders of Arousal" (DoA), encompassing sleepwalking, confusional arousals, and sleep terrors, refers to parasomnias manifesting during nonrapid eye movement (NREM) sleep, commonly thought to arise from an aberrant arousal process. While previous studies have detailed electroencephalographic (EEG) changes linked to DoA episodes, it remains uncertain how these alterations differ from a physiological arousal process. This study directly compared brain activity between DoA episodes and arousals associated with physiological movements (motor arousal) in individuals with DoA and healthy sleepers. METHODS: Fifty-three adult participants with DoA (25 males, 32.2 ± 15.5 years) and 33 control participants (14 males, 31.4 ± 11.4 years) underwent one or more home EEG recordings. A semiparametric regression model was employed to elucidate the complex relationship between EEG activity across channels, within and across different groups, including motor arousals in DoA (n = 169), parasomnia episodes in DoA (n = 361), and motor arousals in healthy sleepers (n = 137). RESULTS: Parasomnia episodes and motor arousals in both groups were preceded by a diffuse increase in slow-wave activity (SWA) and beta power, and a widespread decrease in sigma power. However, motor arousals in DoA displayed lower beta and central sigma than in healthy sleepers. Within participants with DoA, episodes were preceded by lower beta, frontal sigma, and higher SWA than motor arousals. CONCLUSIONS: Our findings suggest that the arousal process is altered in participants with DoA, and that specific EEG patterns are required for DoA episodes to emerge. These insights will help guide future research into the underlying circuits and objective markers of DoA.
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