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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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Introduction:\udWhen 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.\ud\udMethods:\udA novel and general approach to reverse the coarse-grained approach by locating the exact sources of the functional abnormalities is proposed.\ud\udResults:\udThirty-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.\ud\udConclusions:\udThe 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:简介:\ ud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)来研究功能网络的组织。相对粗略的规模。但是,粗粒度方案可能会在较小的空间尺度上平均出精细的细节,因此很难识别功能异常的确切位置。\ ud \ udMethods:\ ud一种新颖而通用的方法可以通过提议确定功能异常的确切来源。\ ud \ ud结果:\ ud研究了39例重度抑郁症(MDD)患者和37名匹配的健康对照者。包含左上额回(SFGdor),右岛(INS)和右壳核(PUT)的回路在患有MDD的患者和对照组之间表现出最大的变化。将反向粗粒度分析应用于此电路以确定功能异常的确切位置。\ ud \ ud结论:\ ud从反向粗粒度分析(源)中提取的体素方向时间序列比原始粗略分析具有多个优势-粒度方法:(1)存在较大且可检测到的波动幅度,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了显着改善。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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