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Critical slowing down as a biomarker for seizure susceptibility

Author

Listed:
  • Matias I. Maturana

    (The University of Melbourne
    Seer Medical)

  • Christian Meisel

    (University Clinic Carl Gustav Carus
    Boston Children’s Hospital)

  • Katrina Dell

    (The University of Melbourne)

  • Philippa J. Karoly

    (The University of Melbourne)

  • Wendyl D’Souza

    (The University of Melbourne)

  • David B. Grayden

    (The University of Melbourne)

  • Anthony N. Burkitt

    (The University of Melbourne)

  • Premysl Jiruska

    (Charles University
    Czech Academy of Sciences)

  • Jan Kudlacek

    (Charles University
    Czech Academy of Sciences
    Czech Technical University in Prague)

  • Jaroslav Hlinka

    (Institute of Computer Science of the Czech Academy of Sciences
    National Institute of Mental Health)

  • Mark J. Cook

    (The University of Melbourne
    The University of Melbourne)

  • Levin Kuhlmann

    (The University of Melbourne
    Monash University
    Swinburne University of Technology)

  • Dean R. Freestone

    (Seer Medical)

Abstract

The human brain has the capacity to rapidly change state, and in epilepsy these state changes can be catastrophic, resulting in loss of consciousness, injury and even death. Theoretical interpretations considering the brain as a dynamical system suggest that prior to a seizure, recorded brain signals may exhibit critical slowing down, a warning signal preceding many critical transitions in dynamical systems. Using long-term intracranial electroencephalography (iEEG) recordings from fourteen patients with focal epilepsy, we monitored key signatures of critical slowing down prior to seizures. The metrics used to detect critical slowing down fluctuated over temporally long scales (hours to days), longer than would be detectable in standard clinical evaluation settings. Seizure risk was associated with a combination of these signals together with epileptiform discharges. These results provide strong validation of theoretical models and demonstrate that critical slowing down is a reliable indicator that could be used in seizure forecasting algorithms.

Suggested Citation

  • Matias I. Maturana & Christian Meisel & Katrina Dell & Philippa J. Karoly & Wendyl D’Souza & David B. Grayden & Anthony N. Burkitt & Premysl Jiruska & Jan Kudlacek & Jaroslav Hlinka & Mark J. Cook & L, 2020. "Critical slowing down as a biomarker for seizure susceptibility," Nature Communications, Nature, vol. 11(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-15908-3
    DOI: 10.1038/s41467-020-15908-3
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    Cited by:

    1. Gregory Lepeu & Ellen Maren & Kristina Slabeva & Cecilia Friedrichs-Maeder & Markus Fuchs & Werner J. Z’Graggen & Claudio Pollo & Kaspar A. Schindler & Antoine Adamantidis & Timothée Proix & Maxime O., 2024. "The critical dynamics of hippocampal seizures," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    2. An, Sufang & An, Feng & Gao, Xiangyun & Wang, Anjian, 2023. "Early warning of critical transitions in crude oil price," Energy, Elsevier, vol. 280(C).
    3. Romain Bocher, 2022. "VIX Fractal Compression Pattern and Markets Vulnerability: An Interdisciplinary Approach," Post-Print hal-04188990, HAL.
    4. Annika Hagemann & Jens Wilting & Bita Samimizad & Florian Mormann & Viola Priesemann, 2021. "Assessing criticality in pre-seizure single-neuron activity of human epileptic cortex," PLOS Computational Biology, Public Library of Science, vol. 17(3), pages 1-18, March.
    5. Tirabassi, Giulio & Masoller, Cristina, 2022. "Correlation lags give early warning signals of approaching bifurcations," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).

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