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早期精神分裂症的功能网络连接。

Functional network connectivity in early-stage schizophrenia.

机构信息

Department of Psychiatry, Indiana University School of Medicine, United States of America; Indiana University Psychotic Disorders Program, Indiana University School of Medicine, United States of America.

Department of Psychiatry, Indiana University School of Medicine, United States of America.

出版信息

Schizophr Res. 2020 Apr;218:107-115. doi: 10.1016/j.schres.2020.01.023. Epub 2020 Feb 7.

DOI:10.1016/j.schres.2020.01.023
PMID:32037204
Abstract

Schizophrenia is a disorder of altered neural connections resulting in impaired information integration. Whole brain assessment of within- and between-network connections may determine how information processing is disrupted in schizophrenia. Patients with early-stage schizophrenia (n = 56) and a matched control sample (n = 32) underwent resting-state fMRI scans. Gray matter regions were organized into nine distinct functional networks. Functional connectivity was calculated between 278 gray matter regions for each subject. Network connectivity properties were defined by the mean and variance of correlations of all regions. Whole-brain network measures of global efficiency (reflecting overall interconnectedness) and locations of hubs (key regions for communication) were also determined. The control sample had greater connectivity between the following network pairs: somatomotor-limbic, somatomotor-default mode, dorsal attention-default mode, ventral attention-limbic, and ventral attention-default mode. The patient sample had greater variance in interactions between ventral attention network and other functional networks. Illness duration was associated with overall increases in the variability of network connections. The control group had higher global efficiency and more hubs in the cerebellum network, while patient group hubs were more common in visual, frontoparietal, or subcortical networks. Thus, reduced functional connectivity in patients was largely present between distinct networks, rather than within-networks. The implications of these findings for the pathophysiology of schizophrenia are discussed.

摘要

精神分裂症是一种神经连接改变的疾病,导致信息整合受损。对脑内和脑间连接的全脑评估可以确定信息处理在精神分裂症中是如何受到干扰的。56 名早期精神分裂症患者(n=56)和 32 名匹配的对照组(n=32)接受了静息态 fMRI 扫描。灰质区域被组织成九个不同的功能网络。为每个受试者计算了 278 个灰质区域之间的功能连接。网络连接特性由所有区域相关性的平均值和方差定义。还确定了全脑网络的全局效率(反映整体连通性)和枢纽位置(用于通信的关键区域)的指标。对照组在以下网络对之间具有更高的连接性:躯体运动-边缘,躯体运动-默认模式,背侧注意-默认模式,腹侧注意-边缘,和腹侧注意-默认模式。患者组在腹侧注意网络与其他功能网络之间的相互作用的方差更大。疾病持续时间与网络连接的整体可变性增加有关。对照组在小脑网络中具有更高的全局效率和更多的枢纽,而患者组的枢纽则更常见于视觉、额顶叶或皮质下网络中。因此,患者的功能连接减少主要存在于不同的网络之间,而不是在网络内部。讨论了这些发现对精神分裂症病理生理学的意义。

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