Reproducibility of graph measures derived from resting‐state MEG functional connectivity metrics in sensor and source spaces

Prior studies have used graph analysis of resting‐state magnetoencephalography (MEG) to characterize abnormal brain networks in neurological disorders. However, a present challenge for researchers is the lack of guidance on which network construction strategies to employ. The reproducibility of grap...

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Veröffentlicht in:Human brain mapping 2022-03, Vol.43 (4), p.1342-1357
Hauptverfasser: Pourmotabbed, Haatef, Jongh Curry, Amy L., Clarke, Dave F., Tyler‐Kabara, Elizabeth C., Babajani‐Feremi, Abbas
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Sprache:eng
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Zusammenfassung:Prior studies have used graph analysis of resting‐state magnetoencephalography (MEG) to characterize abnormal brain networks in neurological disorders. However, a present challenge for researchers is the lack of guidance on which network construction strategies to employ. The reproducibility of graph measures is important for their use as clinical biomarkers. Furthermore, global graph measures should ideally not depend on whether the analysis was performed in the sensor or source space. Therefore, MEG data of the 89 healthy subjects of the Human Connectome Project were used to investigate test–retest reliability and sensor versus source association of global graph measures. Atlas‐based beamforming was used for source reconstruction, and functional connectivity (FC) was estimated for both sensor and source signals in six frequency bands using the debiased weighted phase lag index (dwPLI), amplitude envelope correlation (AEC), and leakage‐corrected AEC. Reliability was examined over multiple network density levels achieved with proportional weight and orthogonal minimum spanning tree thresholding. At a 100% density, graph measures for most FC metrics and frequency bands had fair to excellent reliability and significant sensor versus source association. The greatest reliability and sensor versus source association was obtained when using amplitude metrics. Reliability was similar between sensor and source spaces when using amplitude metrics but greater for the source than the sensor space in higher frequency bands when using the dwPLI. These results suggest that graph measures are useful biomarkers, particularly for investigating functional networks based on amplitude synchrony. Test–retest reliability of resting‐state magnetoencephalography global graph measures was quantified and compared for three connectivity metrics in sensor and source space. Reliability and sensor versus source association was greater for amplitude than phase metrics. Reliability for the phase metric was greater in source than sensor space at higher frequencies.
ISSN:1065-9471
1097-0193
DOI:10.1002/hbm.25726