Building a Large-Scale Computational Model of a Cortical Neuronal Network

Lucia Zemanová*, Changsong Zhou, Jürgen Kurths

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingChapterpeer-review

2 Citations (Scopus)


We introduce the general framework of the large-scale neuronal model used in the 5th Helmholtz Summer School - Complex Brain Networks. The main aim is to build a universal large-scale model of a cortical neuronal network, structured as a network of networks, which is flexible enough to implement different kinds of topology and neuronal models and which exhibits behavior in various dynamical regimes. First, we describe important biological aspects of brain topology and use them in the construction of a large-scale cortical network. Second, the general dynamical model is presented together with explanations of the major dynamical properties of neurons. Finally, we discuss the implementation of the model into parallel code and its possible modifications and improvements.

Original languageEnglish
Title of host publicationLectures in Supercomputational Neurosciences
Subtitle of host publicationDynamics in Complex Brain Networks
EditorsPeter Graben, Marco Thiel, Changsong Zhou, Jurgen Kurths
PublisherSpringer Berlin Heidelberg
Number of pages16
ISBN (Electronic)9783540731597
ISBN (Print)9783540731580, 9783642092169
Publication statusPublished - 2007

Publication series

NameUnderstanding Complex Systems
ISSN (Print)1860-0832
ISSN (Electronic)1860-0840

Scopus Subject Areas

  • Software
  • Computational Mechanics
  • Artificial Intelligence

User-Defined Keywords

  • Cortical Area
  • Inhibitory Neuron
  • Macaque Monkey
  • Presynaptic Neuron
  • Parallel Code


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