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Coherence a measure of the brain networks: past and present

机译:相干性对大脑网络的度量:过去和现在

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Brian connectivity describes the networks of functional and anatomical connections across the brain. The functional network communications across the brain networks dependent on neuronal oscillations. Detection of the synchronous activation of neurons can be used to determine the wellbeing or integrity of the functional connectivity in the human brain networks. Well-connected highly synchronous functional activity can be measured by Electroencephalography (EEG) or Magnetoencephalography (MEG) and then analyzed with several types of mathematical algorithms. Coherence is one mathematical method that can be used to determine if two or more sensors, or brain regions, have similar neuronal oscillatory activity with each other. Since the 1960’s, coherence has generally been assessed on the similarity of the frequency content across EEG sensors. Recently coherence, after it has been imaged in the brain, has been used to assess how coherent or connected specific locations in the brain are networked together in several different neurological disorders. Statistical analysis can then be performed on the coherence results to verify evidence of normal or abnormal network activity in a patient. In this review we highlight how functional brain connectivity is assessed in Source space using coherence technique measured by MEG.
机译:Brian连通性描述了整个大脑的功能和解剖学连接网络。跨大脑网络的功能网络通信取决于神经元振荡。神经元同步激活的检测可用于确定人脑网络中功能连接的状态或完整性。连接良好的高度同步功能活动可以通过脑电图(EEG)或磁脑电图(MEG)进行测量,然后使用几种数学算法进行分析。相干性是一种数学方法,可用于确定两个或多个传感器或大脑区域是否具有相似的神经元振荡活动。自1960年代以来,通常就通过EEG传感器的频率含量相似性来评估一致性。最近,在将其在大脑中成像后,相干性已用于评估在几种不同的神经系统疾病中,大脑中相干或连接的特定位置如何联网在一起。然后可以对一致性结果执行统计分析,以验证患者正常或异常网络活动的证据。在这篇综述中,我们重点介绍如何使用MEG测量的相干技术在Source空间中评估功能性大脑的连通性。

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