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Brain computational models based on neurodynamical populations at mesoscopic level

Grant number: 12/09268-3
Support type:Scholarships abroad - Research
Effective date (Start): February 01, 2013
Effective date (End): October 15, 2013
Field of knowledge:Physical Sciences and Mathematics - Computer Science
Principal Investigator:João Luís Garcia Rosa
Grantee:João Luís Garcia Rosa
Host: Robert Kozma
Home Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
Local de pesquisa : University of Memphis (U of M), United States  


Current neural network models are far beyond the physiology of cerebral cortex neurons. Brain models based on neurodynamics consider neurons asdynamical systems. And as such, they seek to understand and represent the reasons why neurons are excitable cells. The microscopic current from each neuron sums with currents from other neurons, which causes a macroscopic potential difference, measured with the electroencephalogram (EEG). EEG records the activity patterns of mesoscopic neuron populations. A good neuronal model must reproduce the dynamics of neurons: in this approach, the information processing depends not only on the electrophysiological properties of neurons, but also on their dynamical properties. (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)
GARCIA ROSA, JOAO LUIS; PIAZENTIN, DENIS R. M. A new cognitive filtering approach based on Freeman K3 Neural Networks. APPLIED INTELLIGENCE, v. 45, n. 2, p. 363-382, SEP 2016. Web of Science Citations: 3.

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