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A reversal coarse‐grained analysis with application to an altered functional circuit in depression

机译:逆向粗粒度分析及其在抑郁症患者功能电路改变中的应用

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AbstractIntroductionWhen studying brain function using functional magnetic resonance imaging (fMRI) data containing tens of thousands of voxels, a coarse-grained approach – dividing the whole brain into regions of interest – is applied frequently to investigate the organization of the functional network on a relatively coarse scale. However, a coarse-grained scheme may average out the fine details over small spatial scales, thus rendering it difficult to identify the exact locations of functional abnormalities.MethodsA novel and general approach to reverse the coarse-grained approach by locating the exact sources of the functional abnormalities is proposed.ResultsThirty-nine patients with major depressive disorder (MDD) and 37 matched healthy controls are studied. A circuit comprising the left superior frontal gyrus (SFGdor), right insula (INS), and right putamen (PUT) exhibit the greatest changes between the patients with MDD and controls. A reversal coarse-grained analysis is applied to this circuit to determine the exact location of functional abnormalities.ConclusionsThe voxel-wise time series extracted from the reversal coarse-grained analysis (source) had several advantages over the original coarse-grained approach: (1) presence of a larger and detectable amplitude of fluctuations, which indicates that neuronal activities in the source are more synchronized; (2) identification of more significant differences between patients and controls in terms of the functional connectivity associated with the sources; and (3) marked improvement in performing discrimination tasks. A software package for pattern classification between controls and patients is available in Supporting Information.
机译:摘要简介在使用包含成千上万体素的功能磁共振成像(fMRI)数据研究大脑功能时,经常采用一种粗粒度方法(将整个大脑划分为感兴趣的区域)来研究相对粗略的功能网络的组织规模。然而,粗粒度方案可能会在较小的空间尺度上平均出细微的细节,因此难以识别功能异常的确切位置。方法一种新颖而通用的方法是通过定位精确异常源来反转粗粒度方法结果对39例重度抑郁症患者和37例健康对照者进行了研究。由左上额回(SFGdor),右岛(INS)和右壳核(PUT)组成的回路在患有MDD的患者和对照组之间表现出最大的变化。逆向粗粒度分析应用于此电路以确定功能异常的确切位置。结论从逆向粗粒度分析(源)提取的体素时间序列相对于原始粗粒度方法具有以下优点:(1 )存在较大且可检测的波动幅度,这表明源中的神经元活动更加同步; (2)识别患者和对照之间在与来源相关的功能连接方面的更大差异; (3)在执行歧视任务方面有显着改善。支持信息中提供了用于在控件和患者之间进行模式分类的软件包。

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