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Exploring MEG brain fingerprints: Evaluation, pitfalls, and interpretations.

Ekansh Sareen1, Sélima Zahar2, Dimitri Van De Ville3

  • 1Signal Processing and Biomedical Imaging, Dept. of Electronics and Communication Engineering, IIIT-Delhi, New Delhi, India.

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|July 8, 2021
PubMed
Summary
This summary is machine-generated.

Magnetoencephalography (MEG) functional connectome (FC) fingerprinting shows promise for individual identification. Performance varies with connectivity measures, frequency bands, and data processing, with phase-coupling methods and alpha/beta bands yielding better results.

Keywords:
Brain fingerprintingBrain networksFunctional connectomesMEG connectivity

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Area of Science:

  • Neuroscience
  • Brain Imaging
  • Computational Neuroscience

Background:

  • Individual characterization using functional connectome (FC) fingerprinting is a key goal in neuroscience.
  • Functional magnetic resonance imaging (fMRI) has shown success in FC fingerprinting.
  • FC fingerprinting using magnetoencephalography (MEG) remains largely unexplored.

Purpose of the Study:

  • To assess the feasibility and characteristics of FC fingerprinting in resting-state MEG data.
  • To investigate the influence of connectivity measures, frequency bands, and spatial leakage correction on MEG fingerprinting.
  • To explore cross-modality fingerprinting patterns between MEG and fMRI, and their behavioral significance.

Main Methods:

  • Utilized resting-state MEG data from the Human Connectome Project.
  • Employed differential identifiability and success rate scoring methods for quantitative fingerprinting.
  • Analyzed edgewise and nodal fingerprinting patterns across frequency bands (delta, theta, alpha, beta, gamma) and compared with fMRI data.

Main Results:

  • MEG FC fingerprinting performance is dependent on connectivity measure, frequency band, scoring method, and spatial leakage correction.
  • Higher performance observed with phase-coupling methods, alpha and beta bands, and specific brain networks (visual, frontoparietal, attention, default-mode).
  • Cross-modality analysis revealed spatial concordance between MEG and fMRI fingerprinting, particularly in the visual system.

Conclusions:

  • MEG FC fingerprinting is a viable method for individual characterization, with performance modulated by methodological choices.
  • Phase-coupling and central frequency bands (alpha, beta) enhance MEG fingerprinting accuracy.
  • MEG connectomes demonstrate behavioral significance, supporting their utility in understanding brain function across modalities.