Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.
Curr Med Sci. 2020 Dec;40(6):1057-1066. doi: 10.1007/s11596-020-2287-9. Epub 2021 Jan 11.
Examining the spontaneous BOLD activity to understand the neural mechanism of Parkinson's disease (PD) with mild cognitive impairment (MCI) is a focus in resting-state functional MRI (rs-fMRI) studies. This study aimed to investigate the alteration of brain functional connectivity in PD with MCI in a systematical way at two levels: functional connectivity analysis within resting state networks (RSNs) and functional network connectivity (FNC) analysis. Using group independent component analysis (ICA) on rs-fMRI data acquired from 30 participants (14 healthy controls and 16 PD patients with MCI), 16 RSNs were identified, and functional connectivity analysis within the RSNs and FNC analysis were carried out between groups. Compared to controls, patients with PD showed decreased functional connectivity within putamen network, thalamus network, cerebellar network, attention network, and self-referential network, and increased functional connectivity within execution network. Globally disturbed, mostly increased functional connectivity of FNC was observed in PD group, and insular network and execution network were the dominant network with extensively increased functional connectivity with other RSNs. Cerebellar network showed decreased functional connectivity with caudate network, insular network, and self-referential network. In general, decreased functional connectivity within RSNs and globally disturbed, mostly increased functional connectivity of FNC may be characteristics of PD. Increased functional connectivity within execution network may be an early marker of PD. The multi-perspective study based on RSNs may be a valuable means to assess functional changes corresponding to specific RSN, contributing to the understanding of the neural mechanism of PD.
运用静息态功能磁共振成像(rs-fMRI)技术研究自发性脑活动，以了解伴有轻度认知障碍(MCI)的帕金森病(PD)的神经机制，是目前研究的热点。本研究旨在从两个层面系统地研究 PD 伴 MCI 患者的脑功能连接变化：静息态网络（RSN）内的功能连接分析和功能网络连接（FNC）分析。对 rs-fMRI 数据进行组独立成分分析（ICA），该数据来自 30 名参与者（14 名健康对照者和 16 名 PD 伴 MCI 患者），共识别出 16 个 RSN，并在组间进行了 RSN 内功能连接分析和 FNC 分析。与对照组相比，PD 患者的壳核网络、丘脑网络、小脑网络、注意网络和自我参照网络内的功能连接降低，执行网络内的功能连接增加。PD 组观察到全局功能连接紊乱，主要表现为功能连接增加，其中岛叶网络和执行网络与其他 RSN 的功能连接广泛增加。小脑网络与尾状核、岛叶网络和自我参照网络的功能连接降低。总的来说，RSN 内功能连接降低和 FNC 全局功能连接紊乱，主要表现为功能连接增加，可能是 PD 的特征。执行网络内功能连接增加可能是 PD 的早期标志物。基于 RSN 的多视角研究可能是评估与特定 RSN 对应的功能变化的一种有价值的手段，有助于理解 PD 的神经机制。
