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帕金森病中全脑及基于网络的功能连接改变

Altered Whole-Brain and Network-Based Functional Connectivity in Parkinson's Disease.

作者信息

de Schipper Laura J, Hafkemeijer Anne, van der Grond Jeroen, Marinus Johan, Henselmans Johanna M L, van Hilten Jacobus J

机构信息

Department of Neurology, Leiden University Medical Center, Leiden, Netherlands.

Department of Radiology, Leiden University Medical Center, Leiden, Netherlands.

出版信息

Front Neurol. 2018 Jun 6;9:419. doi: 10.3389/fneur.2018.00419. eCollection 2018.

Abstract

Functional imaging methods, such as resting-state functional magnetic resonance imaging, reflect changes in neural connectivity and may help to assess the widespread consequences of disease-specific network changes in Parkinson's disease. In this study we used a relatively new graph analysis approach in functional imaging: eigenvector centrality mapping. This model-free method, applied to all voxels in the brain, identifies prominent regions in the brain network hierarchy and detects localized differences between patient populations. In other neurological disorders, eigenvector centrality mapping has been linked to changes in functional connectivity in certain nodes of brain networks. Examining changes in functional brain connectivity architecture on a whole brain and network level in patients with Parkinson's disease. Whole brain resting-state functional architecture was studied with a recently introduced graph analysis approach (eigenvector centrality mapping). Functional connectivity was further investigated in relation to eight known resting-state networks. Cross-sectional analyses included group comparison of functional connectivity measures of Parkinson's disease patients ( = 107) with control subjects ( = 58) and correlations with clinical data, including motor and cognitive impairment and a composite measure of predominantly non-dopaminergic symptoms. Eigenvector centrality mapping revealed that frontoparietal regions were more prominent in the whole-brain network function in patients compared to control subjects, while frontal and occipital brain areas were less prominent in patients. Using standard resting-state networks, we found predominantly increased functional connectivity, namely within sensorimotor system and visual networks in patients. Regional group differences in functional connectivity of both techniques between patients and control subjects partly overlapped for highly connected posterior brain regions, in particular in the posterior cingulate cortex and precuneus. Clinico-functional imaging relations were not found. Changes on the level of functional brain connectivity architecture might provide a different perspective of pathological consequences of Parkinson's disease. The involvement of specific, highly connected (hub) brain regions may influence whole brain functional network architecture in Parkinson's disease.

摘要

功能成像方法,如静息态功能磁共振成像,反映神经连接的变化,可能有助于评估帕金森病中疾病特异性网络变化的广泛后果。在本研究中,我们在功能成像中使用了一种相对较新的图形分析方法:特征向量中心性映射。这种无模型方法应用于大脑中的所有体素,可识别大脑网络层次结构中的突出区域,并检测患者群体之间的局部差异。在其他神经系统疾病中,特征向量中心性映射已与大脑网络某些节点的功能连接变化相关联。研究帕金森病患者全脑和网络水平上的功能性脑连接结构变化。采用最近引入的图形分析方法(特征向量中心性映射)研究全脑静息态功能结构。进一步研究了与八个已知静息态网络相关的功能连接。横断面分析包括帕金森病患者(n = 107)与对照受试者(n = 58)功能连接测量的组间比较,以及与临床数据的相关性,包括运动和认知障碍以及主要非多巴胺能症状的综合测量。特征向量中心性映射显示,与对照受试者相比,患者全脑网络功能中额顶叶区域更突出,而额叶和枕叶脑区在患者中则不那么突出。使用标准静息态网络,我们发现患者主要是功能连接增加,即在感觉运动系统和视觉网络内。患者和对照受试者之间两种技术在功能连接上的区域组差异部分重叠于高度连接的后脑区域,特别是在后扣带回皮质和楔前叶。未发现临床-功能成像关系。功能性脑连接结构水平的变化可能为帕金森病的病理后果提供不同的视角。特定的、高度连接(枢纽)的脑区的参与可能会影响帕金森病中的全脑功能网络结构。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9fe/5997827/176c6a63c21b/fneur-09-00419-g0001.jpg

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