Personalized dynamic network models of the human brain as a future tool for planning and optimizing epilepsy therapy

0573600 - ÚI 2024 RIV US eng J - Článek v odborném periodiku
Dallmer-Zerbe, Isa - Jiruška, P. - Hlinka, Jaroslav
Personalized dynamic network models of the human brain as a future tool for planning and optimizing epilepsy therapy.
Epilepsia. Roč. 64, č. 9 (2023), s. 2221-2238. ISSN 0013-9580. E-ISSN 1528-1167
Grant CEP: GA MZd(CZ) NU21-08-00533; GA ČR(CZ) GA18-07908S; GA ČR(CZ) GA21-17564S; GA ČR(CZ) GA21-32608S
Institucionální podpora: RVO:67985807
Klíčová slova: brain stimulation * computational modeling * dynamic systems * epilepsy treatment * surgery
Obor OECD: Neurosciences (including psychophysiology
Impakt faktor: 5.6, rok: 2022
Způsob publikování: Open access
https://doi.org/10.1111/epi.17690

Epilepsy is a common neurological disorder, with one third of patients not responding to currently available antiepileptic drugs. The proportion of pharmacoresistant epilepsies has remained unchanged for many decades. To cure epilepsy and control seizures requires a paradigm shift in the development of new approaches to epilepsy diagnosis and treatment. Contemporary medicine has benefited from the exponential growth of computational modeling, and the application of network dynamics theory to understanding and treating human brain disorders. In epilepsy, the introduction of these approaches has led to personalized epileptic network modeling that can explore the patient's seizure genesis and predict the functional impact of resection on its individual network's propensity to seize. The application of the dynamic systems approach to neurostimulation therapy of epilepsy allows designing stimulation strategies that consider the patient's seizure dynamics and long-term fluctuations in the stability of their epileptic networks. In this article, we review, in a nontechnical fashion suitable for a broad neuroscientific audience, recent progress in personalized dynamic brain network modeling that is shaping the future approach to the diagnosis and treatment of epilepsy.
Trvalý link: https://hdl.handle.net/11104/0344003