Measuring electrophysiological connectivity by power envelope correlation: a technical review on MEG methods

脑磁图 计算机科学 公制(单位) 人类连接体项目 连接体 神经影像学 相关性 包络线(雷达) 人工智能 模式识别(心理学) 机器学习 神经科学 功能连接 心理学 脑电图 数学 电信 经济 运营管理 雷达 几何学
作者
George C. O’Neill,Eleanor L. Barratt,Benjamin A.E. Hunt,Prejaas Tewarie,Matthew J. Brookes
出处
期刊:Physics in Medicine and Biology [IOP Publishing]
卷期号:60 (21): R271-R295 被引量:152
标识
DOI:10.1088/0031-9155/60/21/r271
摘要

The human brain can be divided into multiple areas, each responsible for different aspects of behaviour. Healthy brain function relies upon efficient connectivity between these areas and, in recent years, neuroimaging has been revolutionised by an ability to estimate this connectivity. In this paper we discuss measurement of network connectivity using magnetoencephalography (MEG), a technique capable of imaging electrophysiological brain activity with good (~5 mm) spatial resolution and excellent (~1 ms) temporal resolution. The rich information content of MEG facilitates many disparate measures of connectivity between spatially separate regions and in this paper we discuss a single metric known as power envelope correlation. We review in detail the methodology required to measure power envelope correlation including (i) projection of MEG data into source space, (ii) removing confounds introduced by the MEG inverse problem and (iii) estimation of connectivity itself. In this way, we aim to provide researchers with a description of the key steps required to assess envelope based functional networks, which are thought to represent an intrinsic mode of coupling in the human brain. We highlight the principal findings of the techniques discussed, and furthermore, we show evidence that this method can probe how the brain forms and dissolves multiple transient networks on a rapid timescale in order to support current processing demand. Overall, power envelope correlation offers a unique and verifiable means to gain novel insights into network coordination and is proving to be of significant value in elucidating the neural dynamics of the human connectome in health and disease.
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