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静息态脑磁图数据的图论分析:识别大脑两半球间的连接和默认模式。

Graph theoretical analysis of resting-state MEG data: Identifying interhemispheric connectivity and the default mode.

机构信息

Advanced Neuroscience Imaging Research (ANSIR) Laboratory, Wake Forest School of Medicine, Winston-Salem, NC 27157-1088, USA; Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC 27157-1088, USA; Department of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, NC 27157-1088, USA.

Advanced Neuroscience Imaging Research (ANSIR) Laboratory, Wake Forest School of Medicine, Winston-Salem, NC 27157-1088, USA; Department of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, NC 27157-1088, USA; Virginia Tech - Wake Forest School of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, NC 27157-1088, USA.

出版信息

Neuroimage. 2014 Aug 1;96:88-94. doi: 10.1016/j.neuroimage.2014.03.065. Epub 2014 Mar 31.

Abstract

Interhemispheric connectivity with resting state MEG has been elusive, and demonstration of the default mode network (DMN) yet more challenging. Recent seed-based MEG analyses have shown interhemispheric connectivity using power envelope correlations. The purpose of this study is to compare graph theoretic maps of brain connectivity generated using MEG with and without signal leakage correction to evaluate for the presence of interhemispheric connectivity. Eight minutes of resting state eyes-open MEG data were obtained in 22 normal male subjects enrolled in an IRB-approved study (ages 16-18). Data were processed using an in-house automated MEG processing pipeline and projected into standard (MNI) source space at 7mm resolution using a scalar beamformer. Mean beta-band amplitude was sampled at 2.5second epochs from the source space time series. Leakage correction was performed in the time domain of the source space beam formed signal prior to amplitude transformation. Graph theoretic voxel-wise source space correlation connectivity analysis was performed for leakage corrected and uncorrected data. Degree maps were thresholded across subjects for the top 20% of connected nodes to identify hubs. Additional degree maps for sensory, visual, motor, and temporal regions were generated to identify interhemispheric connectivity using laterality indices. Hubs for the uncorrected MEG networks were predominantly symmetric and midline, bearing some resemblance to fMRI networks. These included the cingulate cortex, bilateral inferior frontal lobes, bilateral hippocampal formations and bilateral cerebellar hemispheres. These uncorrected networks however, demonstrated little to no interhemispheric connectivity using the ROI-based degree maps. Leakage corrected MEG data identified the DMN, with hubs in the posterior cingulate and biparietal areas. These corrected networks demonstrated robust interhemispheric connectivity for the ROI-based degree maps. Graph theoretic analysis of MEG resting state data without signal leakage correction can demonstrate symmetric networks with some resemblance to fMRI networks. These networks however, are an artifact of high local correlation from signal leakage and lack interhemispheric connectivity. Following signal leakage correction, MEG hubs emerge in the DMN, with strong interhemispheric connectivity.

摘要

大脑半球间连接在静息态 MEG 中一直难以捉摸,而默认模式网络 (DMN) 的显示则更具挑战性。最近基于种子的 MEG 分析使用功率包络相关显示了大脑半球间的连接。本研究的目的是比较使用 MEG 进行的和未进行信号泄漏校正的脑连接图论图谱,以评估是否存在大脑半球间的连接。在一项经机构审查委员会批准的研究中,共纳入 22 名正常男性被试,获取了 8 分钟静息态睁眼 MEG 数据(年龄 16-18 岁)。使用内部自动化 MEG 处理流水线对数据进行处理,并使用标量波束成形器将数据以 7mm 分辨率投影到标准(MNI)源空间。从源空间时间序列中以 2.5 秒的时窗采集平均β波段振幅。在对幅度进行转换之前,在源空间波束形成信号的时域中进行泄漏校正。对校正和未校正数据进行了基于体素的源空间相关性连接分析。对主体的连接节点进行了 20%的阈值筛选,以确定节点的度数。使用侧性指数生成了用于确定大脑半球间连接的感觉、视觉、运动和颞区的额外的度数图。未校正 MEG 网络的节点主要是对称和中线的,与 fMRI 网络有一些相似之处。这些节点包括扣带回皮质、双侧额下回、双侧海马结构和双侧小脑半球。然而,这些未校正的网络在使用 ROI 为基础的度数图时几乎没有或没有大脑半球间的连接。校正后的 MEG 数据确定了 DMN,其节点位于后扣带回和双侧顶叶区域。这些校正后的网络在 ROI 为基础的度数图中显示出了强大的大脑半球间连接。在未进行信号泄漏校正的 MEG 静息态数据的图论分析中,可以显示出与 fMRI 网络有一些相似的对称网络。然而,这些网络是信号泄漏引起的高局部相关性的伪影,缺乏大脑半球间的连接。在进行信号泄漏校正后,DMN 中的 MEG 节点出现,并显示出强烈的大脑半球间连接。

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