Literature DB >> 31997058

Exploring the Correlation Between M/EEG Source-Space and fMRI Networks at Rest.

Jennifer Rizkallah1,2, Hassan Amoud3, Matteo Fraschini4, Fabrice Wendling5, Mahmoud Hassan5,6.   

Abstract

Magneto/electro-encephalography (M/EEG) source connectivity is an emerging approach to estimate brain networks with high temporal and spatial resolutions. Here, we aim to evaluate the effect of functional connectivity (FC) methods on the correlation between M/EEG source-space and fMRI networks at rest. Two main FC families are tested: (i) FC methods that do not remove zero-lag connectivity including Phase Locking Value (PLV) and Amplitude Envelope Correlation (AEC) and (ii) FC methods that remove zero-lag connections such as Phase Lag Index (PLI) and two orthogonalisation approaches combined with PLV (PLVCol, PLVPas) and AEC (AECCol, AECPas). Methods are evaluated on resting state M/EEG signals recorded from healthy participants at rest (N = 74). Networks obtained by each FC method are compared with fMRI networks (obtained from the Human Connectome Project). Results show low correlations for all FC methods, however PLV and AEC networks are significantly correlated with fMRI networks (ρ = 0.12, p = 1.93 × 10-8 and ρ = 0.06, p = 0.007, respectively), while other methods are not. These observations are consistent for all M/EEG frequency bands and for different FC matrices threshold. Our main message is to be careful in selecting FC methods when comparing or combining M/EEG with fMRI. We consider that more comparative studies based on simulation and real data and at different levels (node, module or sub networks) are still needed in order to improve our understanding on the relationships between M/EEG source-space networks and fMRI networks at rest.

Entities:  

Keywords:  Connectivity measures; Functional brain networks; Magneto/electro-encephalography

Year:  2020        PMID: 31997058     DOI: 10.1007/s10548-020-00753-w

Source DB:  PubMed          Journal:  Brain Topogr        ISSN: 0896-0267            Impact factor:   3.020


  4 in total

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4.  Exploring intensity-dependent modulations in EEG resting-state network efficiency induced by exercise.

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Journal:  Eur J Appl Physiol       Date:  2021-05-18       Impact factor: 3.078

  4 in total

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