NETMORPH: A Framework for the Stochastic Generation of Large Scale Neuronal Networks With Realistic Neuron Morphologies-Reference-Cited by-同舟云学术

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

Published:2009-08-12 Issue:3 Volume:7 Page:195-210
ISSN:1539-2791
Container-title:Neuroinformatics
language:en
Short-container-title:Neuroinform

Author:

Koene Randal A.,Tijms Betty,van Hees Peter,Postma Frank,de Ridder Alexander,Ramakers Ger J. A.,van Pelt Jaap,van Ooyen Arjen

Publisher

Springer Science and Business Media LLC

Subject

Information Systems,General Neuroscience,Software

Link

http://link.springer.com/content/pdf/10.1007/s12021-009-9052-3.pdf

Reference79 articles.

1. Aeschlimann, M. (2000). Biophysical models of axonal pathfinding. Ph.D. thesis, University of Lausanne.

2. Ascoli, G., & Krichmar, J. (2000). L-neuron: a modeling tool for the efficient generation and parsimonious description of dendritic morphology. Neurocomputing, 32–33, 1003–1011.

3. Ascoli, G., Krichmar, J., Nasuto, S., & Senft, S. (2001a). Generation, description and storage of dendritic morphology data. Philosophical Transactions of the Royal Society of London B, 356, 1131–1145.

4. Ascoli, G., Krichmar, J., Scorcioni, R., Nasuto, S., & Senft, S. (2001b). Computer generation and quantitative morphometric analysis of virtual neurons. Anatomy and Embryology, 204, 283–301.

5. Bamburg, J. (2003). Introduction to cytoskeletal dynamics and pathfinding of neuronal growth cones. Journal of Histochemistry & Cytochemistry, 51(4), 407–409.

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