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Identifying Dynamic Functional Connectivity Biomarkers Using GIG-ICA: Application to Schizophrenia, Schizoaffective Disorder, and Psychotic Bipolar Disorder

机译:使用Gig-ICA识别动态功能连接生物标志物:应用于精神分裂症,SchizoAfecceive疾病和精神病患者双相情感障碍

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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. (C) 2017 Wiley Periodicals, Inc.
机译:功能性磁共振成像(FMRI)研究表明了精神障碍中的脑动态功能性连接(DFC)改变。在这里,我们的目标是探讨DFC跨越症状相关的疾病,包括与精神病(BPP),SchizoAfecceive疾病(SAD)和精神分裂症(SZ)的双相情感障碍。我们介绍了一个组信息导向的独立组件分析程序,以估计DFC的组级和主题特定的连接状态。使用238个健康对照(HCS)的休息状态FMRI数据,140 bpp,132令伤心和113名SZ患者,我们确定了各种脑DFC和传统静态功能连通性(SFC)的措施分化的措施。结果表明,DFC提供比SFC更多的信息措施。使用DFC分析,诊断相关的连接状态是显而易见的。对于跨群体一致的主导国家,我们发现22个劣质连接性(从HC到BPP的趋势降低到SZ)主要涉及中央,正面和小脑皮质以及34个超连接的例子(随着HC的增加而增加通过SZ)主要涉及丘脑和颞蜂窝。下次垂直性/纤维连接性也分别显示出负面/正相关,临床症状分别。具体而言,连接后和前部陀螺酮的下支链敏感性与平底锅正/负分数显着呈负相关。对于正面连接,BPP类似于HC,同时悲伤和SZ更相似。涉及左脑Crus的三种连接性来自其他组的SZ和连接额头和梭形皮质的一个连接显示出悲伤独特的变化。总之,我们的方法是对评估DFC进行评估,并且可以产生用于量化精神病的维度的成像生物标志物。 (c)2017 Wiley期刊,Inc。

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