A Systems-Level Approach to Human Epileptic Seizures |
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Authors: | Christian Rummel Marc Goodfellow Heidemarie Gast Martinus Hauf Frédérique Amor Alexander Stibal Luigi Mariani Roland Wiest Kaspar Schindler |
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Affiliation: | 1. Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland 2. Systems Biology Doctoral Training Centre, Manchester Institute of Biotechnology, The University of Manchester, Manchester, UK 3. Centre for Interdisciplinary Computational and Dynamical Analysis (CICADA), School of Mathematics, The University of Manchester, Manchester, UK 4. qEEG group, Department of Neurology, Inselspital, Bern University Hospital and University of Bern, Bern, Switzerland 5. Department of Neurosurgery, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland 6. Department of Neurosurgery, Basel University Hospital, University of Basel, Basel, Switzerland
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Abstract: | Epileptic seizures are due to the pathological collective activity of large cellular assemblies. A better understanding of this collective activity is integral to the development of novel diagnostic and therapeutic procedures. In contrast to reductionist analyses, which focus solely on small-scale characteristics of ictogenesis, here we follow a systems-level approach, which combines both small-scale and larger-scale analyses. Peri-ictal dynamics of epileptic networks are assessed by studying correlation within and between different spatial scales of intracranial electroencephalographic recordings (iEEG) of a heterogeneous group of patients suffering from pharmaco-resistant epilepsy. Epileptiform activity as recorded by a single iEEG electrode is determined objectively by the signal derivative and then subjected to a multivariate analysis of correlation between all iEEG channels. We find that during seizure, synchrony increases on the smallest and largest spatial scales probed by iEEG. In addition, a dynamic reorganization of spatial correlation is observed on intermediate scales, which persists after seizure termination. It is proposed that this reorganization may indicate a balancing mechanism that decreases high local correlation. Our findings are consistent with the hypothesis that during epileptic seizures hypercorrelated and therefore functionally segregated brain areas are re-integrated into more collective brain dynamics. In addition, except for a special sub-group, a highly significant association is found between the location of ictal iEEG activity and the location of areas of relative decrease of localised EEG correlation. The latter could serve as a clinically important quantitative marker of the seizure onset zone (SOZ). |
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