TY - JOUR
T1 - Coalescence and fragmentation of cortical networks during focal seizures
AU - Kramer, Mark A.
AU - Eden, Uri T.
AU - Kolaczyk, Eric D.
AU - Zepeda, Rodrigo
AU - Eskandar, Emad N.
AU - Cash, Sydney S.
PY - 2010/7/28
Y1 - 2010/7/28
N2 - Epileptic seizures reflect a pathological brain state characterized by specific clinical and electrical manifestations. The proposed mechanisms are heterogeneous but united by the supposition that epileptic activity is hypersynchronous across multiple scales, yet principled and quantitative analyses of seizure dynamics across space and throughout the entire ictal period are rare. To more completely explore spatiotemporal interactions during seizures, we examined electrocorticogram data from a population of male and femalehumanpatients with epilepsy and from these data constructed dynamic network representations using statistically robust measures.Wefound that these networks evolved through a distinct topological progression during the seizure. Surprisingly, the overall synchronization changed only weakly, whereas the topology changed dramatically in organization. A large subnetwork dominated the network architecture at seizure onset and preceding termination but, between, fractured into smaller groups.Commonnetwork characteristics appeared consistently for a population of subjects, and, for each subject, similar networks appeared from seizure to seizure. These results suggest that, at the macroscopic spatial scale, epilepsy is not so much a manifestation of hypersynchrony but instead of network reorganization.
AB - Epileptic seizures reflect a pathological brain state characterized by specific clinical and electrical manifestations. The proposed mechanisms are heterogeneous but united by the supposition that epileptic activity is hypersynchronous across multiple scales, yet principled and quantitative analyses of seizure dynamics across space and throughout the entire ictal period are rare. To more completely explore spatiotemporal interactions during seizures, we examined electrocorticogram data from a population of male and femalehumanpatients with epilepsy and from these data constructed dynamic network representations using statistically robust measures.Wefound that these networks evolved through a distinct topological progression during the seizure. Surprisingly, the overall synchronization changed only weakly, whereas the topology changed dramatically in organization. A large subnetwork dominated the network architecture at seizure onset and preceding termination but, between, fractured into smaller groups.Commonnetwork characteristics appeared consistently for a population of subjects, and, for each subject, similar networks appeared from seizure to seizure. These results suggest that, at the macroscopic spatial scale, epilepsy is not so much a manifestation of hypersynchrony but instead of network reorganization.
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U2 - 10.1523/JNEUROSCI.6309-09.2010
DO - 10.1523/JNEUROSCI.6309-09.2010
M3 - Article
C2 - 20668192
AN - SCOPUS:77955348210
SN - 0270-6474
VL - 30
SP - 10076
EP - 10085
JO - Journal of Neuroscience
JF - Journal of Neuroscience
IS - 30
ER -