Modelling the role of tissue heterogeneity in epileptic rhythms.
Epileptic seizure activity manifests as complex spatio-temporal dynamics on the clinically relevant macroscopic scale. These dynamics are known to arise from spatially heterogeneous tissue, but the relationship between specific spatial abnormalities and epileptic rhythm generation is not well understood. We formulate a simplified macroscopic modelling framework with which to study the role of spatial heterogeneity in the generation of epileptiform spatio-temporal rhythms. We characterize the overall model dynamics in terms of spontaneous activity and excitability and demonstrate normal and abnormal spreading of activity. We introduce a means to systematically investigate the topology of abnormal sub-networks and explore its impact on spontaneous and stimulus-evoked rhythmic dynamics. This computationally efficient framework complements results from detailed biophysical models, and allows the testing of specific hypotheses about epileptic dynamics on the macroscopic scale.
Doctoral Training Centre, Integrative Systems Biology, Manchester Interdisciplinary Biocentre, University of Manchester, Manchester M1 7DN, UK.
Marc
M
Goodfellow
Peter Neal
PN
Taylor
Yujiang
Y
Wang
Daniel James
DJ
Garry
Gerold
G
Baier
D001921:Brain / Q000166:cytology / Q000503:physiopathology*; D058256:Brain Waves / Q000502:physiology; D004827:Epilepsy / Q000503:physiopathology*; D006801:Humans; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology; D009928:Organ Specificity