脑磁图
人类连接体项目
连接体
二元分析
功能连接
度量(数据仓库)
多元统计
一般化
计算机科学
方向性
模式识别(心理学)
神经科学
人工智能
数学
脑电图
数据挖掘
机器学习
心理学
生物
数学分析
遗传学
作者
Alessio Basti,Vittorio Pizzella,Federico Chella,Gian Luca Romani,Guido Nolte,Laura Marzetti
出处
期刊:NeuroImage
[Elsevier]
日期:2018-07-01
卷期号:175: 161-175
被引量:32
标识
DOI:10.1016/j.neuroimage.2018.03.004
摘要
The phase slope index (PSI) is a method to disclose the direction of frequency-specific neural interactions from magnetoencephalographic (MEG) time series. A fundamental property of PSI is that of vanishing for linear mixing of independent neural sources. This property allows PSI to cope with the artificial instantaneous connectivity among MEG sensors or brain sources induced by the field spread. Nevertheless, PSI is limited by being a bivariate estimator of directionality as opposite to the multidimensional nature of brain activity as revealed by MEG. The purpose of this work is to provide a multivariate generalization of PSI. We termed this measure as the multivariate phase slope index (MPSI). In order to test the ability of MPSI in estimating the directionality, and to compare the MPSI results to those obtained by bivariate PSI approaches based on maximizing imaginary part of coherency and on canonical correlation analysis, we used extensive simulations. We proved that MPSI achieves the highest performance and that in a large number of simulated cases, the bivariate methods, as opposed to MPSI, do not detect a statistically significant directionality. Finally, we applied MPSI to assess seed-based directed functional connectivity in the alpha band from resting state MEG data of 61 subjects from the Human Connectome Project. The obtained results highlight a directed functional coupling in the alpha band between the primary visual cortex and several key regions of well-known resting state networks, e.g. dorsal attention network and fronto-parietal network.
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