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快速功能磁共振成像的滞后分析揭示发作性睡病中默认模式网络与其他网络之间的信息流延迟

Lag Analysis of Fast fMRI Reveals Delayed Information Flow Between the Default Mode and Other Networks in Narcolepsy.

作者信息

Järvelä M, Raatikainen V, Kotila A, Kananen J, Korhonen V, Uddin L Q, Ansakorpi H, Kiviniemi V

机构信息

Department of Diagnostic Radiology, Medical Research Center (MRC), Oulu University Hospital, 90220 Oulu, Finland.

Research Unit of Logopedics, University of Oulu, 90014 Oulu, Finland.

出版信息

Cereb Cortex Commun. 2020 Oct 10;1(1):tgaa073. doi: 10.1093/texcom/tgaa073. eCollection 2020.

Abstract

Narcolepsy is a chronic neurological disease characterized by dysfunction of the hypocretin system in brain causing disruption in the wake-promoting system. In addition to sleep attacks and cataplexy, patients with narcolepsy commonly report cognitive symptoms while objective deficits in sustained attention and executive function have been observed. Prior resting-state functional magnetic resonance imaging (fMRI) studies in narcolepsy have reported decreased inter/intranetwork connectivity regarding the default mode network (DMN). Recently developed fast fMRI data acquisition allows more precise detection of brain signal propagation with a novel dynamic lag analysis. In this study, we used fast fMRI data to analyze dynamics of inter resting-state network (RSN) information signaling between narcolepsy type 1 patients (NT1,  = 23) and age- and sex-matched healthy controls (HC,  = 23). We investigated dynamic connectivity properties between positive and negative peaks and, furthermore, their anticorrelative (pos-neg) counterparts. The lag distributions were significantly ( < 0.005, familywise error rate corrected) altered in 24 RSN pairs in NT1. The DMN was involved in 83% of the altered RSN pairs. We conclude that narcolepsy type 1 is characterized with delayed and monotonic inter-RSN information flow especially involving anticorrelations, which are known to be characteristic behavior of the DMN regarding neurocognition.

摘要

发作性睡病是一种慢性神经疾病,其特征在于大脑中下丘脑分泌素系统功能障碍,导致促觉醒系统紊乱。除了发作性睡眠和猝倒外,发作性睡病患者通常还报告有认知症状,同时观察到其在持续注意力和执行功能方面存在客观缺陷。先前针对发作性睡病的静息态功能磁共振成像(fMRI)研究报告称,默认模式网络(DMN)的网络间/网络内连接性降低。最近开发的快速fMRI数据采集方法,通过一种新颖的动态滞后分析,能够更精确地检测脑信号传播。在本研究中,我们使用快速fMRI数据来分析1型发作性睡病患者(NT1,n = 23)与年龄和性别匹配的健康对照(HC,n = 23)之间静息态网络(RSN)信息信号的动态变化。我们研究了正峰和负峰之间的动态连接特性,以及它们的反相关(正 - 负)对应关系。NT1组中24对RSN的滞后分布有显著改变(P < 0.005,经家族性错误率校正)。DMN参与了83%的改变的RSN对。我们得出结论,1型发作性睡病的特征是RSN间信息流延迟且单调,尤其涉及反相关,而反相关是DMN在神经认知方面的典型行为。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/966b/8153076/70e16f2e0360/tgaa073f1.jpg

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