1 Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France. christian.benar@univ-amu.fr.
2 PERFORM Centre and Physics Department, Concordia University, Montreal, QC, Canada.
3 Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada.
4 Multimodal Functional Imaging Laboratory, Biomedical Engineering Department, McGill University, Montreal, QC, Canada.
5 Centre de Recherches Mathématiques, Montreal, QC, Canada.
6 Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France.
7 Département de Génie Électrique, École de Technologie Supérieure, Montreal, QC, Canada.
8 Centre d'Etudes Avancées en Médecine du Sommeil, Hôpital Sacré Cœur, Montreal, QC, Canada.

Differences in MEG and EEG power-law scaling explained by a coupling between spatial coherence and frequency: a simulation study.

J Comput Neurosci. 2019 Jul 11;:

Authors: Bénar CG, Grova C, Jirsa VK, Lina JM

Abstract

Electrophysiological signals (electroencephalography, EEG, and magnetoencephalography, MEG), as many natural processes, exhibit scale-invariance properties resulting in a power-law (1/f) spectrum. Interestingly, EEG and MEG differ in their slopes, which could be explained by several mechanisms, including non-resistive properties of tissues. Our goal in the present study is to estimate the impact of space/frequency structure of source signals as a putative mechanism to explain spectral scaling properties of neuroimaging signals. We performed simulations based on the summed contribution of cortical patches with different sizes (ranging from 0.4 to 104.2 cm2). Small patches were attributed signals of high frequencies, whereas large patches were associated with signals of low frequencies, on a logarithmic scale. The tested parameters included i) the space/frequency structure (range of patch sizes and frequencies) and ii) the amplitude factor c parametrizing the spatial scale ratios. We found that the space/frequency structure may cause differences between EEG and MEG scale-free spectra that are compatible with real data findings reported in previous studies. We also found that below a certain spatial scale, there were no more differences between EEG and MEG, suggesting a limit for the resolution of both methods.Our work provides an explanation of experimental findings. This does not rule out other mechanisms for differences between EEG and MEG, but suggests an important role of spatio-temporal structure of neural dynamics. This can help the analysis and interpretation of power-law measures in EEG and MEG, and we believe our results can also impact computational modeling of brain dynamics, where different local connectivity structures could be used at different frequencies.

PMID: 31292816 [PubMed - as supplied by publisher]