Modèles bio-mathématiques neuro-inspirés intégrant la neuroplasticité induite par la stimulation électrique cérébrale

Epilepsy affects approximately 1% of the global population, and approximately 30% of epilepsy patients suffer from drug-resistant epilepsy (DRE). Electrical stimulation techniques—including deep brain stimulation (DBS) and transcranial direct current stimulation (tDCS)—have emerged as alternative therapeutic strategies for such patients. However, the mechanisms by which these interventions produce beneficial effects remain poorly understood. Computational modeling has become a valuable tool for understanding the mechanisms underlying such neurological disorders. The primary aim of this thesis is to develop computational models to enhance our understanding of the post-stimulation effects of electrical neuromodulation, particularly the neuroplastic changes it induces. To this end, we have developed a novel thalamocortical neural mass model that incorporates short-term synaptic plasticity and extrasynaptic receptor activation. This model explains the frequency-dependent suppression of interictal activity observed in focal cortical dysplasia following thalamic stimulation. In addition, we have investigated the effects of direct current stimulation (DCS) through neural mass modeling, examining how stimulation influences neuroplastic changes for different interictal spiking frequencies in epileptogenic networks. In summary, this work proposes potential mechanisms underlying the therapeutic effects of electrical stimulation and presents a modeling framework for studying the neuroplastic responses associated with such interventions in epilepsy.