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The Effect of Host Morphology on Network Characteristics and Thermodynamical Properties of Ising Model Defined on the Network of Human Pyramidal Neurons

  • Renato Aparecido Pimentel da Silva
  • Matheus Palhares Viana
  • Luciano da Fontoura Costa
Part of the Communications in Computer and Information Science book series (CCIS, volume 116)

Abstract

The question about the effect of the host (node) morphology on complex network characteristics and properties of dynamical processes defined on networks is addressed. The complex networks are formed by hosts represented by realistic neural cells of complex morphology. The neural cells of different types are randomly placed on a 3-dimensional cubic domain. The connections between nodes established according to overlaps between different nearest-neighbor hosts significantly depend on the host morphology and thus are also random. The influence of host morphology on the following network characteristics has been studied: edge density, clustering coefficient, giant component size, global efficiency, degree entropy, and assortative mixing. The zero-field Ising model has been used as a prototype model to study the effect of the host morphology on dynamical processes defined on the networks of hosts which can be in two states. The mean magnetization, internal energy and spin-cluster size as function of temperature have been numerically studied for several networks composed of hosts of different morphology.

Keywords

Ising Model Neuronal Network Edge Density Morphometric Measurement Giant Component 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Renato Aparecido Pimentel da Silva
    • 1
  • Matheus Palhares Viana
    • 1
  • Luciano da Fontoura Costa
    • 1
    • 2
  1. 1.Instituto de Física de São CarlosUniversidade de São PauloSão CarlosBrazil
  2. 2.Instituto Nacional de Ciência e Tecnologia para Sistemas ComplexosCentro Brasileiro de Pesquisa FísicaRio de JaneiroBrazil

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