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Failure of Adaptive Self-Organized Criticality during Epileptic Seizure Attacks

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  • Christian Meisel
  • Alexander Storch
  • Susanne Hallmeyer-Elgner
  • Ed Bullmore
  • Thilo Gross

Abstract

Critical dynamics are assumed to be an attractive mode for normal brain functioning as information processing and computational capabilities are found to be optimal in the critical state. Recent experimental observations of neuronal activity patterns following power-law distributions, a hallmark of systems at a critical state, have led to the hypothesis that human brain dynamics could be poised at a phase transition between ordered and disordered activity. A so far unresolved question concerns the medical significance of critical brain activity and how it relates to pathological conditions. Using data from invasive electroencephalogram recordings from humans we show that during epileptic seizure attacks neuronal activity patterns deviate from the normally observed power-law distribution characterizing critical dynamics. The comparison of these observations to results from a computational model exhibiting self-organized criticality (SOC) based on adaptive networks allows further insights into the underlying dynamics. Together these results suggest that brain dynamics deviates from criticality during seizures caused by the failure of adaptive SOC. Author Summary: Over the recent years it has become apparent that the concept of phase transitions is not only applicable to the systems classically considered in physics. It applies to a much wider class of complex systems exhibiting phases, characterized by qualitatively different types of long-term behavior. In the critical states, which are located directly at the transition, small changes can have a large effect on the system. This and other properties of critical states prove to be advantageous for computation and memory. It is therefore suspected that also cerebral neural networks operate close to criticality. This is supported by the in vitro and in vivo measurements of power-laws of certain scaling relationships that are the hallmarks of phase transitions. While critical dynamics is arguably an attractive mode of normal brain functioning, its relation to pathological brain conditions is still unresolved. Here we show that brain dynamics deviates from a critical state during epileptic seizure attacks in vivo. Furthermore, insights from a computational model suggest seizures to be caused by the failure of adaptive self-organized criticality, a mechanism of self-organization to criticality based on the interplay between network dynamics and topology.

Suggested Citation

  • Christian Meisel & Alexander Storch & Susanne Hallmeyer-Elgner & Ed Bullmore & Thilo Gross, 2012. "Failure of Adaptive Self-Organized Criticality during Epileptic Seizure Attacks," PLOS Computational Biology, Public Library of Science, vol. 8(1), pages 1-8, January.
  • Handle: RePEc:plo:pcbi00:1002312
    DOI: 10.1371/journal.pcbi.1002312
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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.
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    Cited by:

    1. 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.
    2. Jasleen Gundh & Awaneesh Singh & R K Brojen Singh, 2015. "Ordering Dynamics in Neuron Activity Pattern Model: An Insight to Brain Functionality," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-16, October.
    3. Forough Habibollahi & Brett J. Kagan & Anthony N. Burkitt & Chris French, 2023. "Critical dynamics arise during structured information presentation within embodied in vitro neuronal networks," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    4. Bruno Del Papa & Viola Priesemann & Jochen Triesch, 2017. "Criticality meets learning: Criticality signatures in a self-organizing recurrent neural network," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-21, May.
    5. Rodrigo P. Rocha & Loren Koçillari & Samir Suweis & Michele Filippo De Grazia & Michel Thiebaut Schotten & Marco Zorzi & Maurizio Corbetta, 2022. "Recovery of neural dynamics criticality in personalized whole-brain models of stroke," Nature Communications, Nature, vol. 13(1), pages 1-18, December.

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