In this chapter we will describe recent developments in magnetoencephalography (MEG) network analysis, where we will focus on the rationale behind, and application in clinical cohorts, of an atlas-based beamforming approach. This approach contains three main components, namely, (i) the reconstruction of time series of neuronal activation through beamforming; (ii) the use of a standard atlas, which enables comparisons across studies and modalities; and (iii) the estimation of functional connectivity using the phase lag index (PLI), a measure that is insensitive to the effects of field spread/volume conduction. Moreover, we will discuss the use of the minimum spanning tree (MST), which allows for a biasfree characterization of the topology of the reconstructed functional networks. Application of this approach will be illustrated through examples from recent studies in patients with gliomas, Parkinson's disease, and multiple sclerosis.
|Title of host publication||Magnetoencephalography|
|Subtitle of host publication||From Signals to Dynamic Cortical Networks: Second Edition|
|Publisher||Springer International Publishing AG|
|Number of pages||287|
|Publication status||Published - 17 Oct 2019|