ModelDB is moving. Check out our new site at https://modeldb.science. The corresponding page is https://modeldb.science/266850.

A model for a nociceptor terminal and terminal tree (Barkai et al., 2020)

 Download zip file 
Help downloading and running models
Accession:266850
This model was used to study how the architecture of the nociceptor terminal tree affects the input-output relation of the primary nociceptive neurons. The model shows that the input-output properties of the nociceptive neurons depend on the length, the axial resistance, and location of individual terminals and that activation of multiple terminals by a capsaicin-like current allows summation of the responses from individual terminals, thus leading to increased nociceptive output.
Reference:
1 . Barkai O, Butterman R, Katz B, Lev S, Binshtok AM (2020) The Input-Output Relation of Primary Nociceptive Neurons is Determined by the Morphology of the Peripheral Nociceptive Terminals. J Neurosci 40:9346-9363 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type:
Brain Region(s)/Organism:
Cell Type(s): Dorsal Root Ganglion (DRG) cell;
Channel(s): I Potassium; I Calcium; I Sodium; I h;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Action Potentials; Axonal Action Potentials; Nociception;
Implementer(s):
Search NeuronDB for information about:  I h; I Sodium; I Calcium; I Potassium;
TITLE Ornstein-Uhlenbeck process 

NEURON {
	SUFFIX OU
	RANGE i, D, tau, bias
	NONSPECIFIC_CURRENT i
}

UNITS { (mA) = (milliamp) }

PARAMETER {
	bias = 0 (mA/cm2)
	D = 0.0005      (/ms)
	tau = 1 	(ms)
}

ASSIGNED { 
	i (mA/cm2)
	noise (mA/cm2)
	dt (ms)
}

STATE { n (mA/cm2) }

BREAKPOINT {
	SOLVE kin METHOD cnexp
	i = bias + n
}

DERIVATIVE kin {
	noise = 1(mA/cm2) * normrand(0,D/sqrt(dt))
	n' = (-n + noise)/tau
}







Loading data, please wait...