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觉醒阈值揭示了独立于传统睡眠阶段的新型睡眠深度神经标志物。

Arousal threshold reveals novel neural markers of sleep depth independently from the conventional sleep stages.

作者信息

Picchioni Dante, Yang Fan Nils, de Zwart Jacco A, Wang Yicun, Mandelkow Hendrik, Özbay Pinar S, Chen Gang, Taylor Paul A, Lam Niki, Chappel-Farley Miranda G, Chang Catie, Liu Jiaen, van Gelderen Peter, Duyn Jeff H

机构信息

Advanced Magnetic Resonance Imaging Section, National Institute of Neurological Disorders and Stroke, USA.

Department of Radiology, Stony Brook University, USA.

出版信息

bioRxiv. 2025 Feb 26:2024.08.09.607376. doi: 10.1101/2024.08.09.607376.

Abstract

Reports of sleep-specific brain activity patterns have been constrained by assessing brain function as it related to the conventional polysomnographic sleep stages. This limits the variety of sleep states and underlying activity patterns that one can discover. The current study used all-night functional MRI sleep data and defined sleep behaviorally with auditory arousal threshold (AAT) to characterize sleep depth better by searching for novel neural markers of sleep depth that are neuroanatomically localized and temporally unrelated to the conventional stages. Functional correlation values calculated in a four-min time window immediately before the determination of AAT were entered into a linear mixed effects model, allowing multiple arousals across the night per subject into the analysis, and compared to models with sleep stage to determine the unique relationships with AAT. These unique relationships were for thalamocerebellar correlations, the relationship between the right language network and the right "default-mode network dorsal medial prefrontal cortex subsystem," and the relationship between thalamus and ventral attention network. These novel neural markers of sleep depth would have remained undiscovered if the data were merely analyzed with the conventional sleep stages.

摘要

关于睡眠特异性脑活动模式的报告一直受到限制,原因在于评估脑功能时是将其与传统多导睡眠图睡眠阶段联系起来。这限制了人们能够发现的睡眠状态及潜在活动模式的多样性。当前研究使用了整夜功能性磁共振成像睡眠数据,并通过听觉唤醒阈值(AAT)从行为学角度定义睡眠,通过寻找在神经解剖学上定位且在时间上与传统睡眠阶段无关的新型睡眠深度神经标志物,来更好地表征睡眠深度。在确定AAT之前的一个四分钟时间窗口内计算的功能相关值被输入到一个线性混合效应模型中,该模型允许将每个受试者整夜的多次唤醒纳入分析,并与基于睡眠阶段的模型进行比较,以确定与AAT的独特关系。这些独特关系涉及丘脑 - 小脑相关性、右侧语言网络与右侧“默认模式网络背内侧前额叶皮质子系统”之间的关系以及丘脑与腹侧注意网络之间的关系。如果仅根据传统睡眠阶段对数据进行分析,这些新型睡眠深度神经标志物可能就会一直未被发现。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/71d4/11874915/0884e7f45364/nihpp-2024.08.09.607376v4-f0001.jpg

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