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Intelligent Control to Suppress Epileptic Seizures in the Amygdala: In Silico Investigation Using a Network of Izhikevich Neurons




Tekijätda Silva Lima, Gabriel; Rosa Cota, Vinícius; Moreira Bessa, Wallace

KustantajaInstitute of Electrical and Electronics Engineers (IEEE)

Julkaisuvuosi2025

JournalIEEE Transactions on Neural Systems and Rehabilitation Engineering

Tietokannassa oleva lehden nimiIEEE Transactions on Neural Systems and Rehabilitation Engineering

Vuosikerta33

Aloitussivu868

Lopetussivu880

ISSN1534-4320

eISSN1558-0210

DOIhttps://doi.org/10.1109/TNSRE.2025.3543756

Verkko-osoitehttps://doi.org/10.1109/tnsre.2025.3543756

Rinnakkaistallenteen osoitehttps://research.utu.fi/converis/portal/detail/Publication/485075013


Tiivistelmä

Closed-loop electricalstimulation of brain structures is one of the most promising techniques to suppress epileptic seizures in drug-resistant refractory patients who are also ineligible to ablative neurosurgery. In this work, an intelligent controller is presented to block the aberrant activity of a network of Izhikevich neurons of three different types, used here to model the electrical activity of the basolateral amygdala during ictogenesis, i.e. its transition from asynchronous to hypersynchronous state. A Lyapunov-based nonlinear scheme is used as the main framework for the proposed controller. To avoid the issue of accessing each neuron individually, local field potentials are used to gain insight into the overall state of the Izhikevich network. Artificial neural networks are integrated into the control scheme to manage unknown dynamics and disturbances caused by brain electrical activity that are not accounted for in the model. Four different cases of ictogenesis induction were tested. The results show the efficacy of the proposed control strategy to suppress epileptic seizures and suggest its capability to address both patient-specific and patient-to-patient variability.


Ladattava julkaisu

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Last updated on 2025-12-03 at 10:52