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

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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.
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;
Gap Junctions:
Simulation Environment: NEURON; Python;
Model Concept(s): Ephaptic coupling; Stimulus selectivity;
anatomy.json *
container.json *
electrodes.json *
settings.json *
tissues.json *
			"use contours": "load file",
			"use internal topology": "load file",
			"contours file": "./data/load/created_nerve_contour.csv",
			"internal topology file": "./data/load/created_nerve_internal_topology.json",
			"contours point reduction": 11,
			"contours generation":
					"filename": "created_nerve_contour.csv",
							"diameter": 150.0,
							"center": [0.0, 0.0]
							"number": 1,
							"diameters": [149.0],
							"centers": [[0.0, 0.0]]
			"fibers distribution":
					"filename": "created_nerve_internal_topology.csv",
					"axon placements":
							"number": 1,
							"locations": [[0.0, 0.0], [100.0, 0.0], [150.0, 0.0], [220.0, 0.0]],
							"radii": [5.0, 5.0, 5.0, 5.0],
									"type": "uniform",
									"avg. radius": 3.65,
									"gamma shape": 2.5,
									"min radius": 3.5,
									"max radius": 3.5,
									"max axons per fascicle": 50,
									"max iterations": 1e4
							"minimum separation": 1.0
					"min NAELC density": 1.0e-3
	"length": 6.0e4,
					"internodal length to fiberD ratio": "given by data regressions",
					"nodes misalignement": 0.5