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Nat Commun. 2018 Mar 14;9(1):1088. doi: 10.1038/s41467-018-02973-y.

Predicting the spatiotemporal diversity of seizure propagation and termination in human focal epilepsy.

Author information

1
Department of Neuroscience, Brown University, Providence, RI, 02912, USA.
2
Institute for Brain Science, Brown University, Providence, RI, 02912, USA.
3
Center for Neurorestoration & Neurotechnology, U.S. Department of Veterans Affairs, Providence, RI, 02912, USA.
4
Institut de Neurosciences des Systèmes (INS), Inserm, Aix Marseille Univ, Marseille, 13005, France.
5
CNRS, CRMBM UMR 7339, Aix Marseille Univ, Marseille, 13005, France.
6
Department of Neuroscience, Brown University, Providence, RI, 02912, USA. wilson_truccolo@brown.edu.
7
Institute for Brain Science, Brown University, Providence, RI, 02912, USA. wilson_truccolo@brown.edu.
8
Center for Neurorestoration & Neurotechnology, U.S. Department of Veterans Affairs, Providence, RI, 02912, USA. wilson_truccolo@brown.edu.

Abstract

Recent studies have shown that seizures can spread and terminate across brain areas via a rich diversity of spatiotemporal patterns. In particular, while the location of the seizure onset area is usually invariant across seizures in an individual patient, the source of traveling (2-3 Hz) spike-and-wave discharges during seizures can either move with the slower propagating ictal wavefront or remain stationary at the seizure onset area. Furthermore, although many focal seizures terminate synchronously across brain areas, some evolve into distinct ictal clusters and terminate asynchronously. Here, we introduce a unifying perspective based on a new neural field model of epileptic seizure dynamics. Two main mechanisms, the co-existence of wave propagation in excitable media and coupled-oscillator dynamics, together with the interaction of multiple time scales, account for the reported diversity. We confirm our predictions in seizures and tractography data obtained from patients with pharmacologically resistant epilepsy. Our results contribute toward patient-specific seizure modeling.

PMID:
29540685
PMCID:
PMC5852068
DOI:
10.1038/s41467-018-02973-y
[Indexed for MEDLINE]
Free PMC Article

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