Threshold for computing generalized model of default mode network connectivity

Waqas Rasheed, T. Tang, N. H. Hamid
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Abstract

Functional connectivity is becoming popular as a second opinion for neurosurgeons and specialists in order to decide on the need for surgical resection, or prescribing medication and appraise prognosis. Neuroimaging modalities such as fMRI, fNIRS, PET, and EEG provide functional connectivity estimation. MEG is the most recent trend in functional connectivity assessment research as it gives more accurate results. The magnetic signals are not disrupted by volume conduction, as in EEG. Besides a reasonable spatial resolution, it offers an extraordinary temporal resolution. However there is a need of a generalized model for default mode network connectivity using MEG. This paper presents a novel method for generating a generalized model and discusses significance of threshold levels in assessing synchronization of activity from various brain regions.
默认模式网络连通性广义模型的阈值计算
功能连通性作为神经外科医生和专家决定是否需要手术切除、开药和评估预后的第二意见,正变得越来越受欢迎。神经成像模式,如fMRI, fNIRS, PET和EEG提供功能连接估计。脑磁图是功能连接评估研究的最新趋势,其结果更为准确。磁信号不像脑电图那样受到体积传导的干扰。除了合理的空间分辨率外,它还提供了非凡的时间分辨率。然而,需要一种基于MEG的缺省模式网络连接的通用模型。本文提出了一种生成广义模型的新方法,并讨论了阈值水平在评估大脑各区域活动同步中的意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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