Combining magnetoencephalography with magnetic resonance imaging enhances learning of surrogate-biomarkers

Abstract

Electrophysiological methods, i.e., M/EEG provide unique views into brain health. Yet, when building predictive models from brain data, it is often unclear how electrophysiology should be combined with other neuroimaging methods. Information can be redundant, useful common representations of multimodal data may not be obvious and multimodal data collection can be medically contraindicated, which reduces applicability. Here, we propose a multimodal model to robustly combine MEG, MRI and fMRI for prediction. We focus on age prediction as a surrogate biomarker in 674 subjects from the Cam-CAN dataset. Strikingly, MEG, fMRI and MRI showed additive effects supporting distinct brain-behavior associations. Moreover, the contribution of MEG was best explained by cortical power spectra between 8 and 30 Hz. Finally, we demonstrate that the model preserves benefits of stacking when some data is missing. The proposed framework, hence, enables multimodal learning for a wide range of biomarkers from diverse types of brain signals.

Data availability

We used the publicly available Cam-CAN dataset. All software and code necessary to obtain the derivative data is shared on github: https://github.com/dengemann/meg-mri-surrogate-biomarkers-aging-2020

The following previously published data sets were used

Article and author information

Author details

  1. Denis Alexander Engemann

    Parietal, Inria Saclay, Palaiseau, France
    For correspondence
    denis-alexander.engemann@inria.fr
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7223-1014
  2. Oleh Kozynets

    Parietal, Inria Saclay, Palaiseau, France
    Competing interests
    No competing interests declared.
  3. David Sabbagh

    Parietal, Inria Saclay, Palaiseau, France
    Competing interests
    No competing interests declared.
  4. Guillaume Lemaître

    Parietal, Inria Saclay, Palaiseau, France
    Competing interests
    No competing interests declared.
  5. Gaël Varoquaux

    Parietal, Inria Saclay, Palaiseau, France
    Competing interests
    Gaël Varoquaux, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1076-5122
  6. Franziskus Liem

    Dynamics of Healthy Aging, University of Zürich, Zürich, Switzerland
    Competing interests
    No competing interests declared.
  7. Alexandre Gramfort

    Parietal, Inria Saclay, Palaiseau, France
    Competing interests
    No competing interests declared.

Funding

H2020 European Research Council (SLAB ERC-YStG-676943)

  • Alexandre Gramfort

French National Institute of Computer Science (Medecine Numerique)

  • Denis Alexander Engemann

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Human subjects: This study is conducted in compliance with the Helsinki Declaration. No experiments on living beings were performed for this study. The data that we used was acquired by the Cam-CAN consortium and has been approved by the local ethics committee, Cambridgeshire 2 Research Ethics Committee (reference: 10/H0308/50).

Copyright

© 2020, Engemann et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 5,248
    views
  • 593
    downloads
  • 78
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Denis Alexander Engemann
  2. Oleh Kozynets
  3. David Sabbagh
  4. Guillaume Lemaître
  5. Gaël Varoquaux
  6. Franziskus Liem
  7. Alexandre Gramfort
(2020)
Combining magnetoencephalography with magnetic resonance imaging enhances learning of surrogate-biomarkers
eLife 9:e54055.
https://doi.org/10.7554/eLife.54055

Share this article

https://doi.org/10.7554/eLife.54055

Further reading

    1. Neuroscience
    Ana Maria Ichim, Harald Barzan ... Raul Cristian Muresan
    Review Article

    Gamma oscillations in brain activity (30–150 Hz) have been studied for over 80 years. Although in the past three decades significant progress has been made to try to understand their functional role, a definitive answer regarding their causal implication in perception, cognition, and behavior still lies ahead of us. Here, we first review the basic neural mechanisms that give rise to gamma oscillations and then focus on two main pillars of exploration. The first pillar examines the major theories regarding their functional role in information processing in the brain, also highlighting critical viewpoints. The second pillar reviews a novel research direction that proposes a therapeutic role for gamma oscillations, namely the gamma entrainment using sensory stimulation (GENUS). We extensively discuss both the positive findings and the issues regarding reproducibility of GENUS. Going beyond the functional and therapeutic role of gamma, we propose a third pillar of exploration, where gamma, generated endogenously by cortical circuits, is essential for maintenance of healthy circuit function. We propose that four classes of interneurons, namely those expressing parvalbumin (PV), vasointestinal peptide (VIP), somatostatin (SST), and nitric oxide synthase (NOS) take advantage of endogenous gamma to perform active vasomotor control that maintains homeostasis in the neuronal tissue. According to this hypothesis, which we call GAMER (GAmma MEdiated ciRcuit maintenance), gamma oscillations act as a ‘servicing’ rhythm that enables efficient translation of neural activity into vascular responses that are essential for optimal neurometabolic processes. GAMER is an extension of GENUS, where endogenous rather than entrained gamma plays a fundamental role. Finally, we propose several critical experiments to test the GAMER hypothesis.

    1. Medicine
    2. Neuroscience
    LeYuan Gu, WeiHui Shao ... HongHai Zhang
    Research Article

    The advent of midazolam holds profound implications for modern clinical practice. The hypnotic and sedative effects of midazolam afford it broad clinical applicability. However, the specific mechanisms underlying the modulation of altered consciousness by midazolam remain elusive. Herein, using pharmacology, optogenetics, chemogenetics, fiber photometry, and gene knockdown, this in vivo research revealed the role of locus coeruleus (LC)-ventrolateral preoptic nucleus noradrenergic neural circuit in regulating midazolam-induced altered consciousness. This effect was mediated by α1 adrenergic receptors. Moreover, gamma-aminobutyric acid receptor type A (GABAA-R) represents a mechanistically crucial binding site in the LC for midazolam. These findings will provide novel insights into the neural circuit mechanisms underlying the recovery of consciousness after midazolam administration and will help guide the timing of clinical dosing and propose effective intervention targets for timely recovery from midazolam-induced loss of consciousness.