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帕金森病中大脑神经连接的改变:基于结构连接组的分析

Altered Brain Wiring in Parkinson's Disease: A Structural Connectome-Based Analysis.

作者信息

Shah Apurva, Lenka Abhishek, Saini Jitender, Wagle Shivali, Naduthota Rajini M, Yadav Ravi, Pal Pramod Kumar, Ingalhalikar Madhura

机构信息

1 Department of Electronics and Telecommunications, Symbiosis Institute of Technology, Symbiosis International University , Pune, India .

2 Department of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS) , Bengaluru, India .

出版信息

Brain Connect. 2017 Aug;7(6):347-356. doi: 10.1089/brain.2017.0506.

Abstract

Parkinson's disease (PD) is a neurodegenerative disorder that predominantly affects the motor system. Diffusion magnetic resonance imaging (MRI) has demonstrated deficits in anisotropy as well as increased diffusivity in the sub-cortical structures, primarily in the substantia nigra in PD. However, the clinical spectrum of PD is not limited to motor symptoms; rather, it encompasses several nonmotor symptoms such as depression, psychosis, olfactory dysfunction, and cognitive impairment. These nonmotor symptoms underscore PD as a complex neurological disorder arising from dysfunction of several network components. Therefore, to decipher the underlying neuropathology, it is crucial to employ novel network-based methods that can elucidate associations between specific network changes. This study aimed at assessing the large-scale structural network changes in PD. Structural connectomes were computed by using probabilistic fiber tracking on diffusion MRI between 86 regions of interest. Graph theoretic analysis on the connectome was carried out at several levels of granularity: global, local (nodal), lobar, and edge wise. Our findings demonstrate lower network clustering capability, overall lower neural connectivity, and significantly reduced nodal influence of the hippocampus in PD. In addition, extensive patterns of reduced connectivity were observed within and between the temporal, parietal, and occipital areas. In summary, our findings corroborate widespread structural disconnectivity that can be potentially linked to the nonmotor symptoms in PD.

摘要

帕金森病(PD)是一种主要影响运动系统的神经退行性疾病。扩散磁共振成像(MRI)已证实,在帕金森病中,皮层下结构,主要是黑质,存在各向异性缺陷以及扩散率增加。然而,帕金森病的临床症状并不局限于运动症状;相反,它还包括多种非运动症状,如抑郁、精神病、嗅觉功能障碍和认知障碍。这些非运动症状突显了帕金森病是一种由多个网络组件功能障碍引起的复杂神经系统疾病。因此,为了解释潜在的神经病理学,采用能够阐明特定网络变化之间关联的新型基于网络的方法至关重要。本研究旨在评估帕金森病中大规模结构网络的变化。通过对86个感兴趣区域之间的扩散MRI进行概率纤维追踪来计算结构连接组。对连接组进行了多个粒度级别的图论分析:全局、局部(节点)、脑叶和边级别。我们的研究结果表明,帕金森病患者的网络聚类能力较低,整体神经连接性较低,海马体的节点影响力显著降低。此外,在颞叶、顶叶和枕叶区域内部和之间观察到广泛的连接性降低模式。总之,我们的研究结果证实了广泛存在的结构不连接性,这可能与帕金森病的非运动症状有关。

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