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使用广义独立成分分析(GIG-ICA)识别动态功能连接生物标志物:在精神分裂症、分裂情感性障碍和精神病性双相情感障碍中的应用。

Identifying dynamic functional connectivity biomarkers using GIG-ICA: Application to schizophrenia, schizoaffective disorder, and psychotic bipolar disorder.

作者信息

Du Yuhui, Pearlson Godfrey D, Lin Dongdong, Sui Jing, Chen Jiayu, Salman Mustafa, Tamminga Carol A, Ivleva Elena I, Sweeney John A, Keshavan Matcheri S, Clementz Brett A, Bustillo Juan, Calhoun Vince D

机构信息

The Mind Research Network & LBERI, Albuquerque, New Mexico.

School of Computer & Information Technology, Shanxi University, Taiyuan, China.

出版信息

Hum Brain Mapp. 2017 May;38(5):2683-2708. doi: 10.1002/hbm.23553. Epub 2017 Mar 10.

Abstract

Functional magnetic resonance imaging (fMRI) studies have shown altered brain dynamic functional connectivity (DFC) in mental disorders. Here, we aim to explore DFC across a spectrum of symptomatically-related disorders including bipolar disorder with psychosis (BPP), schizoaffective disorder (SAD), and schizophrenia (SZ). We introduce a group information guided independent component analysis procedure to estimate both group-level and subject-specific connectivity states from DFC. Using resting-state fMRI data of 238 healthy controls (HCs), 140 BPP, 132 SAD, and 113 SZ patients, we identified measures differentiating groups from the whole-brain DFC and traditional static functional connectivity (SFC), separately. Results show that DFC provided more informative measures than SFC. Diagnosis-related connectivity states were evident using DFC analysis. For the dominant state consistent across groups, we found 22 instances of hypoconnectivity (with decreasing trends from HC to BPP to SAD to SZ) mainly involving post-central, frontal, and cerebellar cortices as well as 34 examples of hyperconnectivity (with increasing trends HC through SZ) primarily involving thalamus and temporal cortices. Hypoconnectivities/hyperconnectivities also showed negative/positive correlations, respectively, with clinical symptom scores. Specifically, hypoconnectivities linking postcentral and frontal gyri were significantly negatively correlated with the PANSS positive/negative scores. For frontal connectivities, BPP resembled HC while SAD and SZ were more similar. Three connectivities involving the left cerebellar crus differentiated SZ from other groups and one connection linking frontal and fusiform cortices showed a SAD-unique change. In summary, our method is promising for assessing DFC and may yield imaging biomarkers for quantifying the dimension of psychosis. Hum Brain Mapp 38:2683-2708, 2017. © 2017 Wiley Periodicals, Inc.

摘要

功能磁共振成像(fMRI)研究表明,精神障碍患者的大脑动态功能连接(DFC)发生了改变。在此,我们旨在探索一系列症状相关疾病中的DFC,包括伴有精神病性症状的双相情感障碍(BPP)、精神分裂症性障碍(SAD)和精神分裂症(SZ)。我们引入了一种群体信息引导的独立成分分析程序,以从DFC中估计群体水平和个体特异性的连接状态。利用238名健康对照者(HC)、140名BPP患者、132名SAD患者和113名SZ患者的静息态fMRI数据,我们分别从全脑DFC和传统静态功能连接(SFC)中确定了区分不同组别的指标。结果表明,DFC提供了比SFC更多的信息性指标。使用DFC分析可明显看出与诊断相关的连接状态。对于各组一致的主要状态,我们发现22例连接减弱(从HC到BPP到SAD再到SZ呈下降趋势),主要涉及中央后回、额叶和小脑皮质,以及34例连接增强(从HC到SZ呈上升趋势),主要涉及丘脑和颞叶皮质。连接减弱/增强也分别与临床症状评分呈负/正相关。具体而言,连接中央后回和额叶回的连接减弱与阳性和阴性症状评定量表(PANSS)的阳性/阴性评分显著负相关。对于额叶连接,BPP与HC相似,而SAD和SZ更相似。涉及左侧小脑脚的三种连接将SZ与其他组区分开来,一种连接额叶和梭状回的连接显示出SAD特有的变化。总之,我们的方法在评估DFC方面很有前景,可能会产生用于量化精神病维度的成像生物标志物。《人类大脑图谱》38:2683 - 2708,2017。© 2017威利期刊公司。

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