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Disrupted correlation between low frequency power and connectivity strength of resting state brain networks in schizophrenia

机译:精神分裂症中休息状态脑网络的低频功率与连接力的相关性中断

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摘要

Altered brain connectivity has emerged as a central feature of schizophrenia. Low frequency oscillations and connectivity strength (CS) of resting state brain networks are altered in patients with schizophrenia (SZs). However, the relationship between these two measures has not yet been studied. Such work may be helpful in understanding the so-called “rich club” organization (i.e. high-CS nodes are more densely connected among themselves than are nodes of a lower CS in the human brain) in healthy controls (HCs) and SZs. Here we present a study of HCs and SZs examining low frequency oscillations and CS by first decomposing resting state fMRI (R-fMRI) data into independent components (ICs) using group independent component analysis (ICA) and computing the low frequency power ratio (LFPR) of each ICA time course. Weighted brain graphs consisting of ICs were built based on correlations between ICA time courses. Positive CS and negative CS of each node in the brain graphs were then examined. The correlations between LFPR and CSs as well as “rich club” coefficients of group mean brain graphs were assessed. Results demonstrate that the LFPR of some ICs were lower in SZs compared to HCs. In addition, LFPR was correlated with positive CS in HCs, but to a lesser extent in SZs. HCs showed higher normalized rich club parameter than SZs. The findings provide new insight into disordered intrinsic brain graphs in schizophrenia.
机译:大脑连接性的改变已成为精神分裂症的主要特征。精神分裂症(SZs)患者的静止状态脑网络的低频振荡和连接强度(CS)发生改变。但是,这两种措施之间的关系尚未得到研究。此类工作可能有助于理解健康对照(HC)和SZ中所谓的“丰富俱乐部”组织(即,高CS节点之间的连接比人脑中低CS的节点更紧密地连接)。在这里,我们对HC和SZ进行研究,首先通过使用组独立成分分析(ICA)将静止状态fMRI(R-fMRI)数据分解为独立成分(IC)并计算低频功率比(LFPR),从而检查低频振荡和CS )。基于ICA时间过程之间的相关性,建立了由IC组成的加权脑图。然后检查脑图中每个节点的正CS和负CS。评估了LFPR和CS之间的相关性,以及组平均脑图的“丰富俱乐部”系数。结果表明,与HC相比,SZ中某些IC的LFPR较低。此外,LFPR与HC中的CS阳性相关,而在SZ中则较小。 HCs显示出比SZs更高的归一化富俱乐部参数。这些发现为精神分裂症的内在失调的大脑图谱提供了新的见解。

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