{"ID":2885972,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.04824","arxiv_id":"2508.04824","title":"Delay-constrained re-entry governs large-scale brain seizures and other network pathologies","abstract":"Re-entry of travelling excitation loops is a long-suspected driver of human seizures, yet how such loops arise in patient brain networks -- and how susceptible they are to targeted disruption -- remains unclear. We reconstruct a millimetre-scale virtual brain from diffusion MRI of a drug-resistant epilepsy patient, embed excitable Epileptor neural fields, and show that realistic cortico-cortical delays are sufficient to generate self-sustaining re-entry. Systematic parameter sweeps reveal a narrow delay-coupling window that predicts oscillation frequency and seizure duration across 184 recorded seizures. Precisely timed biphasic stimuli or sub-millimetre virtual lesions abort re-entry in silico, yielding phase-dependent termination rules validated in intracranial recordings. Our framework exposes delay-constrained re-entry as a generic dynamical mechanism for large-scale brain synchrony and provides a patient-specific testbed for precision neuromodulation and minimally invasive disconnection.","short_abstract":"Re-entry of travelling excitation loops is a long-suspected driver of human seizures, yet how such loops arise in patient brain networks -- and how susceptible they are to targeted disruption -- remains unclear. We reconstruct a millimetre-scale virtual brain from diffusion MRI of a drug-resistant epilepsy patient, emb...","url_abs":"https://arxiv.org/abs/2508.04824","url_pdf":"https://arxiv.org/pdf/2508.04824v1","authors":"[\"Paul Triebkorn\",\"Huifang E. Wang\",\"Marmaduke Woodman\",\"Maxime Guye\",\"Fabrice Bartolomei\",\"Viktor Jirsa\"]","published":"2025-08-06T19:07:39Z","proceeding":"q-bio.NC","tasks":"[\"q-bio.NC\"]","methods":"[\"Diffusion Model\"]","has_code":false}