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Doctoral Thesis
DOI
https://doi.org/10.11606/T.3.2017.tde-28062017-095334
Document
Author
Full name
Tiago Guglielmeti Correale
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2017
Supervisor
Committee
Monteiro, Luiz Henrique Alves (President)
Berlinck, José Guilherme de Souza Chaui Mattos
Macau, Elbert Einstein Nehrer
Omar, Nizam
Piqueira, José Roberto Castilho
 
Title in Portuguese
A membrana e seus canais: um modelo computacional de neurônio.
Keywords in Portuguese
Autônomos celulares
Geometria e modelagem computacional
Neurociências
Simulação de sistemas
Abstract in Portuguese
Modelar a dinâmica de neurônios é relevante em estudos de neurociências. Neste trabalho, propõe-se um modelo computacional de neurônio baseado no comportamento dos canais iônicos presentes na sua membrana. O modelo combina elementos microscópicos, como o comportamento dos canais individuais, com elementos macroscópicos, como a tensão ao longo de um trecho de membrana. Simulações foram realizadas com o objetivo de reproduzir dados biológicos e resultados obtidos de modelos teóricos clássicos da área. Foi possível reproduzir com boa concordância o potencial de ação, o fenômeno da adaptação, a curva da corrente de entrada versus a frequência de disparos e o potencial excitatório pós-sináptico.
 
Title in English
The membrane and its channels: a computational neuron model.
Keywords in English
Cellular automaton
Ion channels
Mathematical model
Neurodynamics
Abstract in English
Modelling the dynamics of neurons is relevant in studies on neurosciences. In this work, a computational model of neuron based on the behavior of the ionic channels found in its membrane is proposed. The model comprises microscopic elements, as the behavior of the individual channels, and macroscopic elements, as the tension along a membrane patch. Simulations were performed with the aim of reproducing biological data and results derived from classical theoretical models of the field. It was possible to reproduce with good agreement the action potential, the phenomenon of adaptation, the curve of the input current versus the spike frequency, and the excitatory postsynaptic potential.
 
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Publishing Date
2017-06-29
 
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