Chacacterization, modeling and computacional simulation on dynamics of neural cells connections and growth

Author(s)

Andrea Gomes Campos Bianchi

• Document type: Doctoral Thesis
• Press: São Carlos.
• Institution: Universidade de São Paulo (USP). Instituto de Física de São Carlos (IFSC/BT)
• Defense date: 2003-05-20

Examining board members

Luciano da Fontoura Costa; André Carlos Ponce de Leon Ferreira de Carvalho; Osame Kinouchi Filho; João Carlos Setubal; Antonio Carlos Roque da Silva Filho

• Advisor: Luciano da Fontoura Costa

Abstract

In this thesis we report the investigation and simulation of dynamic models of neural growing, and their characterization using shape features, considering the form function relationship and neuromorphometry. The thesis begins by presenting an overview about neuroscience, neural cell biology and the biological factors that affects the neuron form developments, followed by the presentation of computational neuronal models based on electrophisiological measures and development models of internal structures as actin and microtubules. Special attention is devoted to a neuron growth model based on calcium as a morphogen, whose main characteristic is its electric activity at the membrane. Regarding mathematical models of neural development, two different approaches of contour evolutions are presented, Level Set Methods and Active Contours. Some neuromorphometric measures are implemented and discussed as features for classification and neural evolution, including the multiscale fractal dimension, and dendrite measurements are obtained by using neuron skeletons. In agreement with biological form influences, some hypotheses about development of neuron growth are proposed based on evolution rules, such as: normal evolution (based in normal velocity), convolution, thin plate splines and actin polimerization. A new approach about neuron development is also proposed: a contour based technique that makes use of active contour formulation, Snake Balloon, where the membrane velocity and direction suffers influences of internal and external factors, such as electrical field with diferent geometries, and contour curvature. Both hypotheses are in accordance with the biological factors that influences the neuron form. The simulation produces similar neuron-like structures, even with ramification of certain dendrites (AU)