A model of stimulus induced epileptic spike-wave discharges
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Taylor_et_al2013.pdf
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Author(s)
Taylor, Peter N.
Baier, Gerold
Cash, Sydney S.
Dauwels, Justin
Slotine, Jean-Jacques E
Wang, Yujiang
Date Issued
2013
Journal
2013 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Taylor, Peter N., Gerold Baier, Sydney S. Cash, Justin Dauwels, Jean-Jacques Slotine, and Yujiang Wang. “A Model of Stimulus Induced Epileptic Spike-Wave Discharges.” 2013 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB) (April 2013). doi:10.1109/ccmb.2013.6609165.
Version
Author's final manuscript
Abstract
Recent clinical and experimental evidence suggests that the spike-wave discharges (SWD) of absence seizures result from local activity within a hyperexcitable cortical region with rapid generalization through thalamocortical networks. The cortical focus is said to react more strongly to stimulation than other areas. We seek to develop a model which is in agreement with these recent experimental findings and suggest a possible explanation. In this study we extend an existing neural field model of thalamocortical interaction to account for multiple cortical regions which are connected according connectivity inferred from a clinically diagnosed epileptic patient. We stimulate at different model electrodes and investigate the resulting seizure duration. We observe that stimulation of only a small subset (11%) of model electrodes can lead to the rapid generalisation of SWD via both corticocortical and thalamocortical pathways. We find that the resulting model dynamics (seizure duration) varies significantly dependent upon the nodes stimulated and the amplitude of the stimulus. Our model indicates that heterogeneities in corticocortical connectivity could serve as a possible reason for the cortical focus and provides a platform for in silico hypothesis generation in complement to in vivo hypothesis validation. © 2013 IEEE.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
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DOI of Published Version
https://doi.org/10.1109/CCMB.2013.6609165
