CN pyramidal fusiform cell (Kanold, Manis 2001)

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Pyramidal cells in the dorsal cochlear nucleus (DCN) show three characteristic discharge patterns in response tones: pauser, buildup, and regular firing. Experimental evidence suggests that a rapidly inactivating K+ current (I(KIF)) plays a critical role in generating these discharge patterns. To explore the role of I(KIF), we used a computational model based on the biophysical data. The model replicated the dependence of the discharge pattern on the magnitude and duration of hyperpolarizing prepulses, and I(KIF) was necessary to convey this dependence. Experimentally, half-inactivation voltage and kinetics of I(KIF) show wide variability. Varying these parameters in the model ... suggests that pyramidal cells can adjust their sensitivity to different temporal patterns of inhibition and excitation by modulating the kinetics of I(KIF). Overall, I(KIF) is a critical conductance controlling the excitability of DCN pyramidal cells. (See readme.txt and paper for details). Any questions regarding these implementations should be directed to: 2 April 2004 Paul B Manis, Ph.D.
1 . Kanold PO, Manis PB (2001) A physiologically based model of discharge pattern regulation by transient K+ currents in cochlear nucleus pyramidal cells. J Neurophysiol 85:523-38 [PubMed]
2 . Kanold PO, Manis PB (1999) Transient potassium currents regulate the discharge patterns of dorsal cochlear nucleus pyramidal cells. J Neurosci 19:2195-208 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s): Cochlear nucleus pyramidal/fusiform GLU cell;
Channel(s): I K; I h; I Sodium; I Potassium;
Gap Junctions:
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Temporal Pattern Generation; Synaptic Integration;
Implementer(s): Manis, Paul B [PManis at];
Search NeuronDB for information about:  Cochlear nucleus pyramidal/fusiform GLU cell; I K; I h; I Sodium; I Potassium;
// showgate.hoc
// put up a display of all of the gating plots for the pyramidal cell model
// 2/1/2000 P. Manis

minv = -100
maxv = 50
nv = 50

objref sg, sg1, sg2
objref sgna, sgk, sgkif, sgkis, sgkift, sgkist, sgh
objref gt_nah, gt_nam, gt_kdm, gt_kifh, gt_kifm, gt_kism, gt_kish, gt_h
objref gt_kiftm, gt_kifth, gt_kistm, gt_kisth
gt_nah = new Vector(nv)
gt_nam = new Vector(nv)
gt_kdm = new Vector(nv)
gt_kifm = new Vector(nv)
gt_kifh = new Vector(nv)
gt_kism = new Vector(nv)
gt_kish = new Vector(nv)
gt_h = new Vector(nv)
gt_kiftm = new Vector(nv)
gt_kifth = new Vector(nv)
gt_kistm = new Vector(nv)
gt_kisth = new Vector(nv)

proc showgate(){

	sg = new HBox()
	sg.intercept(1) // capture input
	xpanel("Na, Kd, H")
	sg1 = new VBox()
		sgna = new Graph()
		sgna.label(0.05, 0.95,"Na")
		sgna.size(minv, maxv, 0, 1)
		sgk = new Graph()
		sgk.label(0.05, 0.95,"Kd")
		sgk.size(minv, maxv, 0, 1)
		sgh = new Graph()
		sgh.label(0.05, 0.95, "Ih")
		sgh.size(minv, maxv, 0, 1)
		sg1.intercept(0)"Na, Kd, H", 0, 0, 100, 100)
	xpanel("IKif, IKis")
		sg2 = new VBox()
		sgkif = new Graph()
		sgkif.label(0.05, 0.95, "IKif")
		sgkif.size(minv, maxv, 0, 1)
		sgkift = new Graph()
		sgkift.label(0.05, 0.95, "IKif")
		sgkift.size(minv, maxv, 0, 10)
		sgkis = new Graph()
		sgkis.label(0.05,0.95, "IKis")
		sgkis.size(minv, maxv, 0, 1)
		sgkist = new Graph()
		sgkist.label(0.05,0.95, "IKis")
		sgkist.size(minv, maxv, 0, 200)
		sg2.intercept(0)"IKif, IKis", 100, 0, 100, 100)
	sg.intercept(0)"Gating", 200, 100, 300, 400)

	linspace(minv, maxv, nv)
	for i=0,stim_list.size-1 {
		vx = stim_list.x[i]
		gt_nam.x[i] = na_m_pyr(vx)^2
		gt_nah.x[i] = na_h_pyr(vx)
		gt_kdm.x[i] = kd_m_pyr(vx)^2
		gt_kifm.x[i] = kif_m_pyr(vx)^4
		gt_kifh.x[i] = kif_h_pyr(vx)
		gt_kism.x[i] = kis_m_pyr(vx)^4
		gt_kish.x[i] = kis_h_pyr(vx)
		gt_kiftm.x[i] = kif_mt_pyr(vx)
		gt_kifth.x[i] = kif_ht_pyr(vx)
		gt_kistm.x[i] = kis_mt_pyr(vx)
		gt_kisth.x[i] = kis_ht_pyr(vx)
		gt_h.x[i] = kh_m_pyr(vx)
	gt_nam.line(sgna, stim_list, 1, 1)
	gt_nah.line(sgna, stim_list, 2, 1)
	gt_kdm.line(sgk, stim_list, 1, 1)
	gt_h.line(sgh, stim_list, 1, 1)

	gt_kifm.line(sgkif, stim_list, 1, 1)
	gt_kifh.line(sgkif, stim_list, 2, 1)
	gt_kism.line(sgkis, stim_list, 1, 1)
	gt_kish.line(sgkis, stim_list, 2, 1)
	gt_kiftm.line(sgkift, stim_list, 1, 1)
	gt_kifth.line(sgkift, stim_list, 2, 1)
	gt_kistm.line(sgkist, stim_list, 1, 1)
	gt_kisth.line(sgkist, stim_list, 2, 1)



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