Submyelin Potassium accumulation in Subthalamic neuron (STN) axons (Bellinger et al. 2008)

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Accession:121253
"To better understand the direct effects of DBS (Deep brain stimulation) on central neurons, a computational model of a myelinated axon has been constructed which includes the effects of K+ accumulation within the peri-axonal space. Using best estimates of anatomic and electrogenic model parameters for in vivo STN axons, the model predicts a functional block along the axon due to K+ accumulation in the submyelin space. ... These results suggest that therapeutic DBS of the STN likely results in a functional block for many STN axons, although a subset of STN axons may also be activated at the stimulating frequency. "
Reference:
1 . Bellinger SC, Miyazawa G, Steinmetz PN (2008) Submyelin potassium accumulation may functionally block subsets of local axons during deep brain stimulation: a modeling study. J Neural Eng 5:263-74 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Axon;
Brain Region(s)/Organism:
Cell Type(s): Subthalamus nucleus projection neuron;
Channel(s): I Na,p; I K; I Sodium; I_Ks; Na/K pump;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Axonal Action Potentials; Action Potentials; Deep brain stimulation; Sodium pump; Depolarization block;
Implementer(s): Bellinger, Steven [Steve.Bellinger at asu.edu];
Search NeuronDB for information about:  I Na,p; I K; I Sodium; I_Ks; Na/K pump;
proc modelInputDefaults() {
	deffiberDiameter = 2	//fiber diameter
	defxElec = 0		//electrode position (um)
	defyElec = 50	
	defzElec = 0
	defrho = 350			//resistivity (ohm cm)
	} 

proc globalParameters() {
	v_init=-70
	ki0_k_ion=106
	ko0_k_ion=3
	celsius=36
	
//resolution
	temporal_factor = 1    			//1: dt = 0.0125, 2: dt = 0.00625
	spatial_factor = 1				//Multiplier for the number of sections used in the model. 1: 231 sections total
	spatial_factor_sections = 23	//should be an odd number so that v.(0.5) is always computed. nseg for segments is modified in buildall()

//topological
	nodeSections = 21 * spatial_factor	// nodes of Ranvier
	masSections = 42 * spatial_factor	// MAS
	psSections = 42 * spatial_factor	// PS
	iSections = 126 * spatial_factor	// IS
	totalSections = 231 * spatial_factor
	

//morphological
	masLength=3
	nodeLength=1
	nodalGap=1.9
	space_p1=0.0025
	space_p2=0.008
	
	space_i=space_p2
	space_n=0.002
	defspace_1=space_p1
	defspace_2=space_p2

//electrical  	
	rhoa=70
	mycm=0.1
	mygm=0.001
	defgkfbar = 0.03

	defINaKmax = 0.00246
	
	defKmnai = 27.9
	defKmko = 5.3
	}

proc dependent_var() {

	fiberDiameter = deffiberDiameter

	if (fiberDiameter==2) {axonDiameter=1.6 nodeDiameter=1.4 masDiameter=1.4 psDiameter=1.6 internodalLength=200.1 psLength=10 numberOfLamella=30}
	if (fiberDiameter==5.7) {axonDiameter=3.4 nodeDiameter=1.9 masDiameter=1.9 psDiameter=3.4 internodalLength=500 psLength=35 numberOfLamella=80}
	if (fiberDiameter==7.3) {axonDiameter=4.6 nodeDiameter=2.4 masDiameter=2.4 psDiameter=4.6 internodalLength=750 psLength=38 numberOfLamella=100}
	if (fiberDiameter==8.7) {axonDiameter=5.8 nodeDiameter=2.8 masDiameter=2.8 psDiameter=5.8 internodalLength=1000 psLength=40 numberOfLamella=110}
	if (fiberDiameter==10.0) {axonDiameter=6.9 nodeDiameter=3.3 masDiameter=3.3 psDiameter=6.9 internodalLength=1150 psLength=46 numberOfLamella=120}
	if (fiberDiameter==11.5) {axonDiameter=8.1 nodeDiameter=3.7 masDiameter=3.7 psDiameter=8.1 internodalLength=1250 psLength=50 numberOfLamella=130}
	if (fiberDiameter==12.8) {axonDiameter=9.2 nodeDiameter=4.2 masDiameter=4.2 psDiameter=9.2 internodalLength=1350 psLength=54 numberOfLamella=135}
	if (fiberDiameter==14.0) {axonDiameter=10.4 nodeDiameter=4.7 masDiameter=4.7 psDiameter=10.4 internodalLength=1400 psLength=56 numberOfLamella=140}
	if (fiberDiameter==15.0) {axonDiameter=11.5 nodeDiameter=5.0 masDiameter=5.0 psDiameter=11.5 internodalLength=1450 psLength=58 numberOfLamella=145}
	if (fiberDiameter==16.0) {axonDiameter=12.7 nodeDiameter=5.5 masDiameter=5.5 psDiameter=12.7 internodalLength=1500 psLength=60 numberOfLamella=150}

	Rpn0=(rhoa*10000*.01)/(PI*((((nodeDiameter/2)+space_n)^2)-((nodeDiameter/2)^2)))
	Rpn1=(rhoa*10000*.01)/(PI*((((masDiameter/2)+space_p1)^2)-((masDiameter/2)^2)))
	Rpn2=(rhoa*10000*.01)/(PI*((((psDiameter/2)+space_p2)^2)-((psDiameter/2)^2)))
	Rpx=(rhoa*10000*.01)/(PI*((((axonDiameter/2)+space_i)^2)-((axonDiameter/2)^2)))
	
	isLength=(internodalLength-nodeLength-(2*masLength)-(2*psLength))/6

	//Scale all segment lengths for the spatial_factor
	isLength = isLength / spatial_factor
	psLength = psLength / spatial_factor
	masLength = masLength / spatial_factor
	nodeLength = nodeLength / spatial_factor

	}

modelInputDefaults()
globalParameters()
dependent_var()

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