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The corresponding page is
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Efficient simulation of 3D reaction-diffusion in models of neurons (McDougal et al, 2022)
 
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Model Information
Model File
Citations
Accession:
267018
Validation, visualization, and analysis scripts for NEURON's 3D reaction-diffusion support.
Reference:
1 .
McDougal RA, Conte C, Eggleston L, Newton AJH, Galijasevic H (2022) Efficient Simulation of 3D Reaction-Diffusion in Models of Neurons and Networks
Front. Neuroinform.
Model Information
(Click on a link to find other models with that property)
Model Type:
Brain Region(s)/Organism:
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment:
NEURON;
Python;
Model Concept(s):
Methods;
Reaction-diffusion;
Implementer(s):
/
code
swc
readme.html
rxdsyn.mod
070314F_11.ASC
3d-convergence.py
analyze_cylinder_convergence.py
Cell280MathModel017.vcml
comparison-to-truth.py
conservation_of_mass.py
conservation_tests.py
cylinder_convergence.py
diffusion-3d-comparison.py
do_timings.py
fig1b.py
Figure1A_3Dwave_time_contour.py
GenerateBnWpng.py
get_timings.py
morph_volume_analysis_truebound.py
plot_simple_geometry_convergence.py
plot_thread_scaling.py
plot_wave_time_3d.py
response_to_currents.py
rxdsyn-test.py
segment-alignment.py
simple_geometry_convergence.py
thread_scaling.py
time_discretization.py
TrueBoundVolumesData.xlsx
volume_functions_truebound.py
wave_time_3d.py
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