A computer simulation study on the effects of stochastic stimulation on the activity of a brain circuit involved in Parkinson's disease

• Grant number: 18/11075-5
• Support Opportunities: Scholarships in Brazil - Master
• Effective date (Start): March 01, 2019
• Effective date (End): October 31, 2020
• Field of knowledge: Engineering - Biomedical Engineering - Bioengineering
• Principal Investigator: Leonardo Abdala Elias
• Grantee: Marcelo Ramos Romano
• Host Institution: Faculdade de Engenharia Elétrica e de Computação (FEEC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil

Abstract

Parkinson's disease (PD) has been postulated to result from degeneration of dopaminergic neurons in the basal ganglia. The main symptoms of this neurodegenerative disease are: tremor, difficulty in the maintenance of posture, and uncoordinated movements. Parkinsonian tremor is thought to emerge from increased cortical oscillations, especially in alpha (8-15Hz) and beta (15-35Hz) bands. The disease is typically controlled by administration of drugs (e.g., levodopa) or by therapies based on the electrical stimulation of deep brain nuclei or the spinal cord. Electrical stimulation techniques adopt periodic signals (electric pulses with a fixed frequency); however, one can hypothesize that random signals can also be used in therapies with the aim of reducing cortical oscillations, thereby decreasing the tremor. This hypothesis raises due to the stochastic resonance phenomenon, which is a beneficial role of the noise applied to the input of physical and biological nonlinear systems. In the present study, a computational model of the motor circuit encompassing the cortex, basal ganglia, and thalamus, that represents an animal model of PD will be used to test the hypothesis presented above. Computer simulations will be carried out with random inputs with the aim of analyzing the effects of stochastic stimulation on the activity of neurons encompassing the motor circuit involved in PD. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

RANIERI, CAETANO M.; PIMENTEL, JHIELSON M.; ROMANO, MARCELO R.; ELIAS, LEONARDO A.; ROMERO, ROSELI A. F.; LONES, MICHAEL A.; ARAUJO, MARIANA F. P.; VARGAS, PATRICIA A.; MOIOLI, RENAN C.. A Data-Driven Biophysical Computational Model of Parkinson's Disease Based on Marmoset Monkeys. IEEE ACCESS, v. 9, p. 122548-122567, 2021. (13/07375-0, 17/02377-5, 18/25902-0, 18/11075-5)