Reconstructing coherent networks from electroencephalography and magnetoencephalography with reduced contamination from volume conduction or magnetic field spread

PloS One
Mark DrakesmithStephen Welbourne

Abstract

Volume conduction (VC) and magnetic field spread (MFS) induce spurious correlations between EEG/MEG sensors, such that the estimation of functional networks from scalp recordings is inaccurate. Imaginary coherency [1] reduces VC/MFS artefacts between sensors by assuming that instantaneous interactions are caused predominantly by VC/MFS and do not contribute to the imaginary part of the cross-spectral densities (CSDs). We propose an adaptation of the dynamic imaging of coherent sources (DICS) [2] - a method for reconstructing the CSDs between sources, and subsequently inferring functional connectivity based on coherences between those sources. Firstly, we reformulate the principle of imaginary coherency by performing an eigenvector decomposition of the imaginary part of the CSD to estimate the power that only contributes to the non-zero phase-lagged (NZPL) interactions. Secondly, we construct an NZPL-optimised spatial filter with two a priori assumptions: (1) that only NZPL interactions exist at the source level and (2) the NZPL CSD at the sensor level is a good approximation of the projected source NZPL CSDs. We compare the performance of the NZPL method to the standard method by reconstructing a coherent network from simulated...Continue Reading

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Citations

Aug 15, 2014·PloS One·Mahmoud HassanFabrice Wendling
Jul 21, 2017·Frontiers in Human Neuroscience·Yvonne HöllerEugen Trinka
Sep 19, 2019·Journal of Clinical Medicine·Antonino NaroRocco Salvatore Calabrò
Apr 24, 2020·Neurotherapeutics : the Journal of the American Society for Experimental NeuroTherapeutics·Sook Ling LeongDirk De Ridder
Jul 1, 2020·NeuroImage·Vahab YoussofzadehManoj Raghavan

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Software Mentioned

FieldTrip
NZPL
DICS
NZPL DICS

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