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Review
. 2020 May;30(2):125-143.
doi: 10.1016/j.nic.2020.02.001.

Magnetoencephalography Signal Processing, Forward Modeling, Magnetoencephalography Inverse Source Imaging, and Coherence Analysis

Matti Hämäläinen  1 , Mingxiong Huang  2 , Susan M Bowyer  3
Affiliations
Review

Magnetoencephalography Signal Processing, Forward Modeling, Magnetoencephalography Inverse Source Imaging, and Coherence Analysis

Matti Hämäläinen et al. Neuroimaging Clin N Am. 2020 May.

Abstract

Magnetoencephalography (MEG) is a noninvasive functional imaging technique for the brain. MEG directly measures the magnetic signal due to neuronal activation in gray matter with high spatial localization accuracy. The first part of this article covers the overall concepts of MEG and the forward and inverse modeling techniques. It is followed by examples of analyzing evoked and resting-state MEG signals using a high-resolution MEG source imaging technique. Next, different techniques for connectivity and network analysis are reviewed with examples showing connectivity estimates from resting-state and epileptic activity.

Keywords: Distributed current estimates; Fast-VESTAL; Magnetoencephalography; Network connectivity measurement; Neurons; Parametric source models; Scanning approaches.

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Conflict of interest statement

Disclosure The authors have nothing to disclose.

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