Cortico-thalamo-basal circuit model to simulate deep brain stimulation in Parkinson's disease

• Grant number: 24/14847-0
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: October 01, 2024
• End date: July 31, 2025
• Field of knowledge: Engineering - Biomedical Engineering - Bioengineering
• Principal Investigator: Antonio Carlos Roque da Silva Filho
• Grantee: Rafael Fernando Gigante
• Host Institution: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto (FFCLRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil
• Associated research grant: 13/07699-0 - Research, Innovation and Dissemination Center for Neuromathematics - NeuroMat, AP.CEPID

Abstract

Parkinson's disease is a common chronic neurodegenerative disorder that involves various motor and non-motor brain pathways. The central pathology underlying Parkinson's disease is the degeneration of dopaminergic neurons in the basal ganglia, leading to decreased dopamine levels in the body. The reduction in dopamine is associated with the pathological dynamics of the neuronal network related to motor control, which encompasses the cortico-thalamo-basal circuit. In Parkinson's disease, electrophysiological changes in this circuit include alterations in firing rates and increased neuronal synchrony and oscillatory activity in the beta band (~13-35 Hz). These dynamic changes provide a physiological basis for modeling studies. Due to the lack of precise understanding of the causes of Parkinson's disease, the mechanisms by which existing treatments work are not well understood. One such treatment, which has been effectively employed in some cases, is deep brain stimulation. The objective of this work is to reimplement two recently published models, one for the basal ganglia and the other for the thalamo-cortical circuit, and to couple them, resulting in a complete model for the cortico-thalamo-basal circuit. The model will be used to simulate the effects of deep brain stimulation on circuit activity, potentially aiding in the analysis of the dynamic behavior of the Parkinsonian network and in understanding the treatment with deep brain stimulation.