Emergent network topology at seizure onset in humans

被引:202
作者
Kramer, Mark A. [1 ]
Kolaczyk, Eric D. [2 ]
Kirsch, Heidi E. [3 ]
机构
[1] Boston Univ, Ctr BioDynam, Boston, MA 02215 USA
[2] Boston Univ, Dept Math & Stat, Boston, MA 02215 USA
[3] Univ Calif San Francisco, Dept Neurol, San Francisco, CA 94143 USA
关键词
seizures; electrocorticogram; oscillations; correlation structure; network analysis; multivariate time series analysis;
D O I
10.1016/j.eplepsyres.2008.02.002
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Epilepsy-the world's most common serious brain disorder-is defined by recurrent unprovoked seizures that result from complex interactions between distributed neural populations. We explore some macroscopic characteristics of emergent ictal networks by considering intracranial recordings from human subjects with intractable epilepsy. For each seizure, we compute a simple measure of Linear coupling between all electrode pairs (more than 2400) to define networks of interdependent electrodes during preictal and ictal time intervals. We analyze these networks by applying traditional measures from network analysis and identify statistically significant global and Local changes in network topology. We find at seizure onset a diffuse breakdown in global coupling, and local changes indicative of increased throughput of specific cortical and subcortical regions. We conclude that network analysis yields measures to summarize the complicated coupling topology emergent at seizure onset. Using these measures, we can identify spatially localized brain regions that may facilitate seizures and may be potential targets for focal therapies. (c) 2008 Elsevier B.V. All rights reserved.
引用
收藏
页码:173 / 186
页数:14
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