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Computational study of hippocampus-cortical-thalamic interactions: simulating oscillatory activity

Grant number: 18/08556-1
Support type:Scholarships abroad - Research Internship - Doctorate
Effective date (Start): September 10, 2018
Effective date (End): September 09, 2019
Field of knowledge:Engineering - Biomedical Engineering
Principal Investigator:Antonio Carlos Roque da Silva Filho
Grantee:Renan Oliveira Shimoura
Supervisor abroad: Markus Diesmann
Home Institution: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto (FFCLRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil
Local de pesquisa : Forschungszentrum Jülich, Germany  
Associated to the scholarship:17/07688-9 - Computational study of hippocampal-cortical-thalamic interactions: simulating patterns of synaptic plasticity and oscillatory activity, BP.DR

Abstract

The triangular system involving the hippocampus, the prefrontal cortex (PFC), and limbic thalamus is related, in its healthy functioning, with working memory and the alternation between states of consciousness. Dysfunctions in this circuit can lead to psychiatric disorders, cognitive deficits, and amplification of epileptic seizures. Computer simulations and mathematical analysis can contribute to improve our knowledge of the dynamical aspects of this circuit. The goal of this project is to achieve skills on the developing of large-scale network simulations and to gain a mathematical understanding on oscillatory phenomena that can emerge from the network activity. Specifically, the objective is to build a large-scale multilayered cortical model with heterogeneous neuronal populations connected with a thalamic network. The cortical network will be based on a model being developed by the German group, which will be adapted to represent the brain region of interest and to receive inputs similar to hippocampal efferent projections. The candidate will gain knowledge on computational methods used to run large-scale network simulations capable of being parallelized on computer clusters and will learn mathematical approaches to analyze networks dynamics, which will be valuable to the continuation of his PhD project after his return and to his future career.