Model of peripheral nerve with ephaptic coupling (Capllonch-Juan & Sepulveda 2020)

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Accession:263988
We built a computational model of a peripheral nerve trunk in which the interstitial space between the fibers and the tissues is modelled using a resistor network, thus enabling distance-dependent ephaptic coupling between myelinated axons and between fascicles as well. We used the model to simulate a) the stimulation of a nerve trunk model with a cuff electrode, and b) the propagation of action potentials along the axons. Results were used to investigate the effect of ephaptic interactions on recruitment and selectivity stemming from artificial (i.e., neural implant) stimulation and on the relative timing between action potentials during propagation.
Reference:
1 . Capllonch-Juan M, Sepulveda F (2020) Modelling the effects of ephaptic coupling on selectivity and response patterns during artificial stimulation of peripheral nerves. PLoS Comput Biol 16:e1007826 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Extracellular; Axon;
Brain Region(s)/Organism:
Cell Type(s): Myelinated neuron;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON; Python;
Model Concept(s): Ephaptic coupling; Stimulus selectivity;
Implementer(s):
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publication_data
dataset_04__eph_stim_vs_dist
fig9b
code
data
models
settings
src
x86_64
AXNODE.mod *
aaa_info_dataset
algebra.py *
analysis.py *
anatomy.py *
biophysics.py *
circlepacker.py *
contourhandler.py *
electrodes.py *
fill_nerve.py *
geometry.py *
get_extstim.py *
read_results.py *
sim_launcher.py *
simcontrol.py *
tessellations.py *
tools.py *
visualisation.py *
vm_vs_t.py
workspace.py *
                            
Nerve 2.
Code for the simulation where the ephaptic influence of one axon is measured against the inter-axonal distance.