NeuGen: A tool for the generation of realistic morphology of cortical neurons and neural networks in 3D

J. P. Eberhard*, A. Wanner, Gabriel Wittum

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

45 Scopus citations

Abstract

We introduce the software package NeuGen for the efficient generation of anatomically accurate synthetic neurons and neural networks. NeuGen generates non-identical neurons of morphological classes of the cortex, e.g., pyramidal cells and stellate neurons, and synaptically connected neural networks in 3D. It is based on sets of descriptive and iterative rules which represent the axonal and dendritic geometry of neurons by inter-correlating morphological parameters. The generation algorithm stochastically samples parameter values from distribution functions induced by experimental data. The generator is adequate for the geometric modelling and for the construction of the morphology. The generated neurons can be exported into a 3D graphic format for visualization and into multi-compartment files for simulations with the program NEURON. NeuGen is intended for scientists aiming at simulations of realistic networks in 3D. The software includes a graphical user interface and is available at http://neugen.uni-hd.de.

Original languageEnglish (US)
Pages (from-to)327-342
Number of pages16
JournalNeurocomputing
Volume70
Issue number1-3
DOIs
StatePublished - Dec 1 2006

Keywords

  • 3D geometry
  • Cortical neural network
  • Modelling neural morphology
  • NeuGen
  • Stochastic generation

ASJC Scopus subject areas

  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence

Fingerprint

Dive into the research topics of 'NeuGen: A tool for the generation of realistic morphology of cortical neurons and neural networks in 3D'. Together they form a unique fingerprint.

Cite this