000171616 001__ 171616
000171616 005__ 20260527123126.0
000171616 0247_ $$2doi$$a10.1098/rspa.2025.0452
000171616 0248_ $$2sideral$$a149404
000171616 037__ $$aART-2026-149404
000171616 041__ $$aeng
000171616 100__ $$aCattell, O.
000171616 245__ $$aUnderstanding tonic–clonic seizure transitions as secondary bifurcations in a neural field model
000171616 260__ $$c2026
000171616 5060_ $$aAccess copy available to the general public$$fUnrestricted
000171616 5203_ $$aEpilepsy is a dynamic complex disease involving a paroxysmal change in the activity of millions of neurons, often resulting in seizures. Tonic–clonic seizures are a particularly important class of these and have previously been theorized to arise in systems with an instability from one temporal rhythm to another via a quasi-periodic transition. We show that a recently introduced class of next-generation neural field models has a sufficiently rich bifurcation structure to support such behaviour. A linear stability analysis of the space-clamped model is used to uncover the conditions for a Hopf–Hopf bifurcation whereby two incommensurate frequencies can be excited. This is used to seed a more exhaustive numerical bifurcation analysis that highlights the preponderance of the model to generate torus bifurcations. Since the neural field model is derived from a biophysically meaningful spiking tissue model, we are able to highlight the neurobiological mechanisms that can underpin tonic–clonic seizures as they relate to levels of excitability, electrical and chemical synaptic coupling and the speed of action potential propagation. We further show how spatio-temporal patterns of activity can evolve in the fully nonlinear regime using direct numerical simulations far from a Turing bifurcation.
000171616 536__ $$9info:eu-repo/grantAgreement/ES/AEI/PID2021-122961NB-I00$$9info:eu-repo/grantAgreement/ES/DGA/E24-20R$$9info:eu-repo/grantAgreement/ES/DGA/E24-23R$$9info:eu-repo/grantAgreement/ES/DGA/LMP94_21$$9info:eu-repo/grantAgreement/ES/MCINN/PID2024-156032NB-I00$$9info:eu-repo/grantAgreement/EUR/MICINN/TED2021-130459B-I00
000171616 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttps://creativecommons.org/licenses/by/4.0/deed.es
000171616 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000171616 700__ $$0(orcid)0000-0002-4802-2511$$aMayora-Cebollero, A.$$uUniversidad de Zaragoza
000171616 700__ $$aO'Dea, R. D.
000171616 700__ $$0(orcid)0000-0002-8089-343X$$aBarrio, R.$$uUniversidad de Zaragoza
000171616 700__ $$aCoombes, S.
000171616 7102_ $$12005$$2595$$aUniversidad de Zaragoza$$bDpto. Matemática Aplicada$$cÁrea Matemática Aplicada
000171616 773__ $$g482, 2338 (2026), 20250452 [28 pp.]$$pProc. - Royal Soc., Math. phys. eng. sci.$$tProceedings - Royal Society. Mathematical, physical and engineering sciences$$x1364-5021
000171616 8564_ $$s4147514$$uhttps://zaguan.unizar.es/record/171616/files/texto_completo.pdf$$yVersión publicada
000171616 8564_ $$s1845719$$uhttps://zaguan.unizar.es/record/171616/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000171616 909CO $$ooai:zaguan.unizar.es:171616$$particulos$$pdriver
000171616 951__ $$a2026-05-27-11:25:00
000171616 980__ $$aARTICLE