Identification of glial cells from artificial neural networks

• Grant number: 23/09094-0
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: October 01, 2023
• End date: December 16, 2024
• Field of knowledge: Physical Sciences and Mathematics - Probability and Statistics - Applied Probability and Statistics
• Principal Investigator: Ricardo Felipe Ferreira
• Grantee: João Pedro Pirola
• Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
• Associated scholarship(s): 23/15585-6 - The link between individual glial cells and synaptic transmission, BE.EP.IC

Abstract

Artificial neural networks are statistical models used for the analysis of complex data. In the last decade, computational advances have made neural networks re-emerge as a powerful tool for solving classification and regression problems. In neuroscience, identifying the effect of glial cells on neuronal spoking is extremely difficult, but it is important to elucidate brain functioning and even benefit the prognosis of pathologies such as Alzheimer's disease. In this sense, neural networks have great potential to help this type of study. In this research project, it is intended to provide student with the opportunity to carry out an in-depth theoretical and applied study, at undergraduate level, of the statistical theory of neural networks, followed by its application in identifying the effects of glial cells on neuronal firing.