Multilayer brain networks can identify the epileptogenic zone and seizure dynamics

  1. Hossein Shahabi  Is a corresponding author
  2. Dileep R Nair
  3. Richard M Leahy
  1. University of Southern California, United States
  2. Cleveland Clinic Neurological Institute, United States

Abstract

Seizure generation, propagation, and termination occur through spatiotemporal brain networks. In this paper, we demonstrate the significance of large-scale brain interactions in high-frequency (80-200 Hz) for identification of the epileptogenic zone (EZ) and seizure evolution. To incorporate the continuity of neural dynamics, here we have modeled brain connectivity constructed from stereoelectroencephalography (SEEG) data during seizures using multilayer networks. After introducing a new measure of brain connectivity for temporal networks, named multilayer eigenvector centrality (mlEVC), we applied a consensus hierarchical clustering on the developed model to identify the epileptogenic zone (EZ) as a cluster of nodes with distinctive brain connectivity in the ictal period. Our algorithm could successfully predict electrodes inside the resected volume as EZ for 88% of participants, who all were seizure-free for at least 12 months after surgery. Our findings illustrated significant and unique desynchronization between EZ and the rest of the brain in early to mid-seizure. We showed that aging and duration of epilepsy intensify this desynchronization, which can be the outcome of abnormal neuroplasticity. Additionally, we illustrated that seizures evolve with various network topologies, confirming the existence of different epileptogenic networks in each patient. Our findings suggest not only the importance of early intervention in epilepsy but the possible factor which correlates with disease severity. Moreover, by analyzing the propagation patterns of different seizures, we asserted the necessity of collecting sufficient data for identifying the epileptogenic networks.

Data availability

The results and codes generated during the current study are available in the following repository, https://data.mendeley.com/datasets/t8bvh5m8bp/1DOI: 10.17632/t8bvh5m8bp.1

Article and author information

Author details

  1. Hossein Shahabi

    Signal and Image Processing Institute, University of Southern California, Los Angeles, United States
    For correspondence
    hshahabi@usc.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3600-8007
  2. Dileep R Nair

    Epilepsy Center, Cleveland Clinic Neurological Institute, Cleveland, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Richard M Leahy

    Signal and Image Processing Institute, University of Southern California, Los Angeles, United States
    Competing interests
    The authors declare that no competing interests exist.

Funding

National Institute of Neurological Disorders and Stroke (R01NS089212)

  • Dileep R Nair
  • Richard M Leahy

National Institute of Biomedical Imaging and Bioengineering (R01EB026299)

  • Richard M Leahy

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

Reviewing Editor

  1. Alex Fornito, Monash University, Australia

Ethics

Human subjects: This retrospective study was approved by the institutional review board at the Cleveland Clinic. Single pulse electrical stimulation induced cortico-cortical evoked potentials are collected as a part of the routine clinical care of patients undergoing SEEG at Cleveland Clinic. The ictal data is also collected during the presurgical SEEG evaluation. The full procedure for participant selection and data recording is described in our previous work(Grinenko et al., 2018).

Version history

  1. Received: March 18, 2021
  2. Accepted: March 16, 2023
  3. Accepted Manuscript published: March 17, 2023 (version 1)
  4. Version of Record published: March 31, 2023 (version 2)

Copyright

© 2023, Shahabi 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.

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  1. Hossein Shahabi
  2. Dileep R Nair
  3. Richard M Leahy
(2023)
Multilayer brain networks can identify the epileptogenic zone and seizure dynamics
eLife 12:e68531.
https://doi.org/10.7554/eLife.68531

Share this article

https://doi.org/10.7554/eLife.68531

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