| Grant number: | 13/25667-8 |
| Support Opportunities: | Scholarships in Brazil - Doctorate (Direct) |
| Start date: | April 01, 2014 |
| End date: | December 31, 2018 |
| Field of knowledge: | Engineering - Biomedical Engineering - Bioengineering |
| Principal Investigator: | Antonio Carlos Roque da Silva Filho |
| Grantee: | Rodrigo Felipe de Oliveira Pena |
| Host Institution: | Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto (FFCLRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil |
| Associated research grant: | 11/50151-0 - Dynamical phenomena in complex networks: fundamentals and applications, AP.TEM |
| Associated scholarship(s): | 15/09916-3 - Analysis of the dynamics of cortical models with heterogeneous cell populations, BE.EP.DD |
Abstract The objective of this project is to construct a computational model of the cerebral cortex to simulate the generation and propagation of epileptiform and study the mechanisms responsible for these phenomena with use of dynamical systems tools. The model will incorporate details in microscopic scale, describing neurons of different electrophysiological behavior and the synaptic couplings among them in a local circuit (module), and in macroscopic scale, describing a modular interconnected network that constitutes the large scale structure of the cortex. Each module will be made of excitatory and inhibitory neurons connected according to experimental evidences on mammalian cortical microcircuitry. The neurons will be arranged in layers, each one containing cell subpopulations with specific electrophysiological characteristics based on experimental evidence on the cortex. The different neuronal spiking behaviors will be reproduced with the use of Izhikevich's model. The macroscopic structure of the network will be hierarchical and modular, based on experimental evidence. The network will be stimulated by different stimulation protocols in order to generate regular and epileptiform activity. The hypothesis adopted is that each neuronal subpopulation has intrinsic parameters which, combined with microscopic and macroscopic structural characteristics of the network may influence the generation and propagation of an epileptiform activity in the network. Mean-field equations will be derived for the neuronal subpopulations and he modules, which will be used in an analytical study of the dynamics of the epileptiform activity. The proposed measures to characterize the results will be based on global and local electrical activity of the network in order to make possible a direct comparison with published electroencephalographic recordings. (AU) | |
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