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Multistage classification identifies altered cortical phase- and amplitude-coupling in Multiple Sclerosis.

Marcus Siems1, Johannes Tünnerhoff2, Ulf Ziemann2

  • 1Department of Neural Dynamics and Magnetoencephalography, Hertie Institute for Clinical Brain Research, University of Tübingen, Germany; Centre for Integrative Neuroscience, University of Tübingen, Germany; MEG Center, University of Tübingen, Germany; Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.

Neuroimage
|November 18, 2022
PubMed
Summary

We developed a new method to analyze brain activity, successfully distinguishing Multiple Sclerosis patients from healthy individuals using magnetoencephalography. This approach identifies key brain network changes related to the disease.

Keywords:
Amplitude-couplingFunctional connectivityHuman connectome projectMEGMultiple SclerosisMultivariate classificationNeuronal oscillationsPhase-coupling

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Area of Science:

  • Neuroscience
  • Biophysics
  • Medical Imaging

Background:

  • Distinguishing between subject groups in high-dimensional neuroimaging data is challenging.
  • Identifying informative neuronal signals is crucial for accurate classification.
  • Changes in large-scale brain interactions in Multiple Sclerosis (MS) are not well understood, and biomarkers are scarce.

Purpose of the Study:

  • To develop a novel unsupervised, multistage analysis approach for selecting relevant neuronal features.
  • To identify changes in brain-wide electrophysiological coupling in Multiple Sclerosis (MS).
  • To compare brain-wide phase and amplitude coupling in MS patients and healthy controls.

Main Methods:

  • Developed a novel unsupervised multistage analysis combining dimensionality reduction, bootstrap aggregating, and multivariate classification.
  • Utilized magnetoencephalography (MEG) to compare brain-wide phase- and amplitude-coupling of frequency-specific neuronal activity.
  • Compared 17 relapsing-remitting MS patients with 17 healthy controls.

Main Results:

  • Successfully classified MS patients and controls with 84% accuracy using identified changes in brain-wide coupling.
  • Observed both increased and decreased phase- and amplitude-coupling in widespread, bilateral neuronal networks across various frequencies.
  • Classification confidence correlated with behavioral scores of disease severity.

Conclusions:

  • Uncovered systematic alterations in large-scale phase- and amplitude coupling in Multiple Sclerosis.
  • Established a new analytical approach for efficiently contrasting high-dimensional neuroimaging data.
  • Demonstrated the potential of neurophysiological coupling as a biomarker for MS.