NETMORPH: A Framework for the Stochastic Generation of Large Scale Neuronal Networks With Realistic Neuron Morphologies

We present a simulation framework, called NETMORPH, for the developmental generation of 3D large-scale neuronal networks with realistic neuron morphologies. In NETMORPH, neuronal morphogenesis is simulated from the perspective of the individual growth cone. For each growth cone in a growing axonal o...

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Bibliographic Details
Published in:Neuroinformatics (Totowa, N.J.) N.J.), 2009-09, Vol.7 (3), p.195-210
Main Authors: Koene, Randal A., Tijms, Betty, van Hees, Peter, Postma, Frank, de Ridder, Alexander, Ramakers, Ger J. A., van Pelt, Jaap, van Ooyen, Arjen
Format: Article
Language:English
Subjects:
Algorithms
Bioinformatics
Biomedical and Life Sciences
Biomedicine
Computational Biology - methods
Computational Biology/Bioinformatics
Computer Appl. in Life Sciences
Computer Simulation
Dendrites - physiology
Dendrites - ultrastructure
Growth Cones - physiology
Growth Cones - ultrastructure
Image Cytometry - methods
Mathematical Computing
Nerve Net - cytology
Nerve Net - physiology
Neural Pathways - cytology
Neural Pathways - physiology
Neurology
Neurons - cytology
Neurons - physiology
Neurosciences
Software
Stochastic Processes
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Summary:We present a simulation framework, called NETMORPH, for the developmental generation of 3D large-scale neuronal networks with realistic neuron morphologies. In NETMORPH, neuronal morphogenesis is simulated from the perspective of the individual growth cone. For each growth cone in a growing axonal or dendritic tree, its actions of elongation, branching and turning are described in a stochastic, phenomenological manner. In this way, neurons with realistic axonal and dendritic morphologies, including neurite curvature, can be generated. Synapses are formed as neurons grow out and axonal and dendritic branches come in close proximity of each other. NETMORPH is a flexible tool that can be applied to a wide variety of research questions regarding morphology and connectivity. Research applications include studying the complex relationship between neuronal morphology and global patterns of synaptic connectivity. Possible future developments of NETMORPH are discussed.
ISSN:1539-2791
1559-0089
DOI:10.1007/s12021-009-9052-3