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利用经验模态分解研究早期帕金森病时间变化的功能磁共振成像数据分析方法进展

Advances in functional magnetic resonance imaging data analysis methods using Empirical Mode Decomposition to investigate temporal changes in early Parkinson's disease.

作者信息

Cordes Dietmar, Zhuang Xiaowei, Kaleem Muhammad, Sreenivasan Karthik, Yang Zhengshi, Mishra Virendra, Banks Sarah J, Bluett Brent, Cummings Jeffrey L

机构信息

Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, USA.

Departments of Psychology and Neuroscience, University of Colorado, Boulder, CO, USA.

出版信息

Alzheimers Dement (N Y). 2018 Jun 14;4:372-386. doi: 10.1016/j.trci.2018.04.009. eCollection 2018.

Abstract

INTRODUCTION

Previous neuroimaging studies of Parkinson's disease (PD) patients have shown changes in whole-brain functional connectivity networks. Whether connectivity changes can be detected in the early stages (first 3 years) of PD by resting-state functional magnetic resonance imaging (fMRI) remains elusive. Research infrastructure including MRI and analytic capabilities is required to investigate this issue. The National Institutes of Health/National Institute of General Medical Sciences Center for Biomedical Research Excellence awards support infrastructure to advance research goals.

METHODS

Static and dynamic functional connectivity analyses were conducted on early stage never-medicated PD subjects (N = 18) and matched healthy controls (N = 18) from the Parkinson's Progression Markers Initiative.

RESULTS

Altered static and altered dynamic functional connectivity patterns were found in early PD resting-state fMRI data. Most static networks (with the exception of the default mode network) had a reduction in frequency and energy in specific low-frequency bands. Changes in dynamic networks in PD were associated with a decreased switching rate of brain states.

DISCUSSION

This study demonstrates that in early PD, resting-state fMRI networks show spatial and temporal differences of fMRI signal characteristics. However, the default mode network was not associated with any measurable changes. Furthermore, by incorporating an optimum window size in a dynamic functional connectivity analysis, we found altered whole-brain temporal features in early PD, showing that PD subjects spend significantly more time than healthy controls in a specific brain state. These findings may help in improving diagnosis of early never-medicated PD patients. These key observations emerged in a Center for Biomedical Research Excellence-supported research environment.

摘要

引言

先前对帕金森病(PD)患者的神经影像学研究显示全脑功能连接网络发生了变化。静息态功能磁共振成像(fMRI)能否在PD早期阶段(前3年)检测到连接性变化仍不清楚。需要包括MRI和分析能力在内的研究基础设施来研究这个问题。美国国立卫生研究院/国立综合医学科学研究所卓越生物医学研究中心奖为推进研究目标提供基础设施支持。

方法

对帕金森病进展标志物倡议中的早期未用药PD受试者(N = 18)和匹配的健康对照(N = 18)进行静态和动态功能连接分析。

结果

在早期PD静息态fMRI数据中发现了静态和动态功能连接模式的改变。大多数静态网络(默认模式网络除外)在特定低频带的频率和能量降低。PD中动态网络的变化与脑状态切换率降低有关。

讨论

本研究表明,在早期PD中,静息态fMRI网络显示出fMRI信号特征的空间和时间差异。然而,默认模式网络与任何可测量的变化无关。此外,通过在动态功能连接分析中纳入最佳窗口大小,我们发现早期PD中全脑时间特征发生了改变,表明PD受试者在特定脑状态下花费的时间比健康对照显著更多。这些发现可能有助于改善早期未用药PD患者的诊断。这些关键观察结果出现在卓越生物医学研究中心支持的研究环境中。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fe2/6115608/3de30de6746e/gr1.jpg

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