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Continuous time stochastic model for neurite branching (van Elburg 2011)
 
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Model Information
Model File
Citations
Accession:
129071
"In this paper we introduce a continuous time stochastic neurite branching model closely related to the discrete time stochastic BES-model. The discrete time BES-model is underlying current attempts to simulate cortical development, but is difficult to analyze. The new continuous time formulation facilitates analytical treatment thus allowing us to examine the structure of the model more closely. ..."
Reference:
1 .
van Elburg R (2011) Stochastic Continuous Time Neurite Branching Models with Tree and Segment Dependent Rates
Journal of Theoretical Biology
276(1)
:159-173
[
PubMed
]
Model Information
(Click on a link to find other models with that property)
Model Type:
Axon;
Dendrite;
Brain Region(s)/Organism:
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment:
C or C++ program;
MATLAB;
Model Concept(s):
Development;
Implementer(s):
van Elburg, Ronald A.J. [R.van.Elburg at ai.rug.nl];
Download the displayed file
/
ContinuousTimeDendriticBranchingModel
figures
mat-files
mexhandle
readme.html
cBEModel.m
mexSDependenceCalculator.cpp
mexSDependenceCalculator.mexglx
ObjectHandle.h
plotBEModelCurves.m
SDependenceCalculation.m
SDependenceCalculator.cpp
SDependenceCalculator.h
SDependenciesPlot.m
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