TY - JOUR T1 - Failure of Adaptive Self-Organized Criticality during Epileptic Seizure Attacks A1 - Meisel, Christian A1 - Storch, Alexander A1 - Hallmeyer-Elgner, Susanne A1 - Bullmore, Ed A1 - Gross, Thilo Y1 - 2012/01/05 N2 - 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. JF - PLOS Computational Biology JA - PLOS Computational Biology VL - 8 IS - 1 UR - https://doi.org/10.1371/journal.pcbi.1002312 SP - e1002312 EP - PB - Public Library of Science M3 - doi:10.1371/journal.pcbi.1002312 ER -