A model for focal seizure onset, propagation, evolution, and progression.

TitleA model for focal seizure onset, propagation, evolution, and progression.
Publication TypeJournal Article
Year of Publication2020
AuthorsLiou J-Y, Smith EH, Bateman LM, Bruce SL, McKhann GM, Goodman RR, Emerson RG, Schevon CA, Abbott LF
Date Published2020 Mar 23

We developed a neural network model that can account for major elements common to human focal seizures. These include the tonic-clonic transition, slow advance of clinical semiology and corresponding seizure territory expansion, widespread EEG synchronization, and slowing of the ictal rhythm as the seizure approaches termination. These were reproduced by incorporating usage-dependent exhaustion of inhibition in an adaptive neural network that receives global feedback inhibition in addition to local recurrent projections. Our model proposes mechanisms that may underline common EEG seizure onset patterns and status epilepticus, and postulates a role for synaptic plasticity in the emergence of epileptic foci. Complex patterns of seizure activity and bi-stable seizure end-points arise when stochastic noise is included. With the rapid advancement of clinical and experimental tools, we believe that this model can provide a roadmap and potentially an in silico testbed for future explorations of seizure mechanisms and clinical therapies.

Alternate JournalElife
PubMed ID32202494
PubMed Central IDPMC7089769
Grant ListR01-NS084142 / NS / NINDS NIH HHS / United States
NeuroNex Award DBI-1707398 / / National Science Foundation /
R01-NS095368 / NS / NINDS NIH HHS / United States
R01-NS110669 / NS / NINDS NIH HHS / United States