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Scaling Effects and Spatio-Temporal Multilevel Dynamics in Epileptic Seizures

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  • Christian Meisel
  • Christian Kuehn

Abstract

Epileptic seizures are one of the most well-known dysfunctions of the nervous system. During a seizure, a highly synchronized behavior of neural activity is observed that can cause symptoms ranging from mild sensual malfunctions to the complete loss of body control. In this paper, we aim to contribute towards a better understanding of the dynamical systems phenomena that cause seizures. Based on data analysis and modelling, seizure dynamics can be identified to possess multiple spatial scales and on each spatial scale also multiple time scales. At each scale, we reach several novel insights. On the smallest spatial scale we consider single model neurons and investigate early-warning signs of spiking. This introduces the theory of critical transitions to excitable systems. For clusters of neurons (or neuronal regions) we use patient data and find oscillatory behavior and new scaling laws near the seizure onset. These scalings lead to substantiate the conjecture obtained from mean-field models that a Hopf bifurcation could be involved near seizure onset. On the largest spatial scale we introduce a measure based on phase-locking intervals and wavelets into seizure modelling. It is used to resolve synchronization between different regions in the brain and identifies time-shifted scaling laws at different wavelet scales. We also compare our wavelet-based multiscale approach with maximum linear cross-correlation and mean-phase coherence measures.

Suggested Citation

  • Christian Meisel & Christian Kuehn, 2012. "Scaling Effects and Spatio-Temporal Multilevel Dynamics in Epileptic Seizures," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-11, February.
    • Handle: RePEc:plo:pone00:0030371
    DOI: 10.1371/journal.pone.0030371
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    References listed on IDEAS

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    1. Manfred G Kitzbichler & Marie L Smith & Søren R Christensen & Ed Bullmore, 2009. "Broadband Criticality of Human Brain Network Synchronization," PLOS Computational Biology, Public Library of Science, vol. 5(3), pages 1-13, March.
    2. Marten Scheffer & Jordi Bascompte & William A. Brock & Victor Brovkin & Stephen R. Carpenter & Vasilis Dakos & Hermann Held & Egbert H. van Nes & Max Rietkerk & George Sugihara, 2009. "Early-warning signals for critical transitions," Nature, Nature, vol. 461(7260), pages 53-59, September.
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    Cited by:

    1. Christian Meisel & Andreas Klaus & Christian Kuehn & Dietmar Plenz, 2015. "Critical Slowing Down Governs the Transition to Neuron Spiking," PLOS Computational Biology, Public Library of Science, vol. 11(2), pages 1-20, February.
    2. Chen, Zheng & Fan, Peiyi & Hou, Xintong & Feng, Guolin & Qian, Zhonghua, 2024. "Effective detection of early warning signal with power spectrum in climate change system," Chaos, Solitons & Fractals, Elsevier, vol. 187(C).
    3. 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.
    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. James Tan & Siew Ann Cheong, 2016. "The Regime Shift Associated with the 2004–2008 US Housing Market Bubble," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-8, September.

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