Voltage- and Branch-specific Climbing Fiber Responses in Purkinje Cells (Zang et al 2018)

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Accession:243446
"Climbing fibers (CFs) provide instructive signals driving cerebellar learning, but mechanisms causing the variable CF responses in Purkinje cells (PCs) are not fully understood. Using a new experimentally validated PC model, we unveil the ionic mechanisms underlying CF-evoked distinct spike waveforms on different parts of the PC. We demonstrate that voltage can gate both the amplitude and the spatial range of CF-evoked Ca2+ influx by the availability of K+ currents. ... The voltage- and branch-specific CF responses can increase dendritic computational capacity and enable PCs to actively integrate CF signals."
Reference:
1 . Zang Y, Dieudonné S, De Schutter E (2018) Voltage- and Branch-Specific Climbing Fiber Responses in Purkinje Cells Cell Reports 24(6):1536-1549 [PubMed]
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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: Cerebellum;
Cell Type(s): Cerebellum Purkinje GABA cell;
Channel(s): Ca pump; I K; I K,Ca; I Na,p; I h;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Action Potential Initiation; Active Dendrites; Synaptic Integration; Dendritic Action Potentials; Detailed Neuronal Models;
Implementer(s): Zang, Yunliang ;
Search NeuronDB for information about:  Cerebellum Purkinje GABA cell; I Na,p; I K; I h; I K,Ca; Ca pump;
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purkinje_pub
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ih.mod *
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TITLE Voltage-gated potassium channel from Kv3 subunits
COMMENT
Voltage-gated potassium channel with high threshold and fast activation/deactivation kinetics

KINETIC SCHEME: Hodgkin-Huxley (n^4)
n'= alpha * (1-n) - betha * n
g(v) = gbar * n^4 * ( v-ek )

The rate constants of activation (alpha) and deactivation (beta) were approximated by:

alpha(v) = ca * exp(-(v+cva)/cka)
beta(v) = cb * exp(-(v+cvb)/ckb)

Parameters can, cvan, ckan, cbn, cvbn, ckbn are given in the CONSTANT block.
Values derive from least-square fits to experimental data of G/Gmax(v) and taun(v) in Martina et al. J Neurophysiol 97:563-571, 2007
Model includes a calculation of Kv gating current

Reference: Akemann et al., Biophys. J. (2009) 96: 3959-3976
Notice that there is another set of data related with Kv3 by McKay and Turner European Journal of Neuroscience, Vol. 20, pp. 729–739, 2004
in that paper, the activation threshold of Kv3 is much lower.
Laboratory for Neuronal Circuit Dynamics
RIKEN Brain Science Institute, Wako City, Japan
http://www.neurodynamics.brain.riken.jp

Date of Implementation: April 2007
Contact: akemann@brain.riken.jp

ENDCOMMENT


NEURON {
	SUFFIX Kv3
	USEION k READ ek WRITE ik
	RANGE gbar, g, ik,vshift
	GLOBAL ninf, tau
:    THREADSAFE
}

UNITS {
	(mV) = (millivolt)
	(mA) = (milliamp)
	(nA) = (nanoamp)
	(pA) = (picoamp)
	(S)  = (siemens)
	(mS) = (millisiemens)
	(nS) = (nanosiemens)
	(pS) = (picosiemens)
	(um) = (micron)
	(molar) = (1/liter)
	(mM) = (millimolar)		
}

CONSTANT {
	e0 = 1.60217646e-19 (coulombs)
	q10 = 2.7

	ca = 0.22 (1/ms)
	cva = 16 (mV)
	cka = -26.5 (mV)
	cb = 0.22 (1/ms)
	cvb = 16 (mV)
	ckb = 26.5 (mV)
	
	zn = 1.9196 (1)		: valence of n-gate
}

PARAMETER {
	vshift = 0
	gbar = 0.005 (S/cm2)   <0,1e9>
}

ASSIGNED {
	celsius (degC)
	v (mV)
	
	ik (mA/cm2)
 
	ek (mV)
	g (S/cm2)
	qt (1)

	ninf (1)
	tau (ms)
	alpha (1/ms)
	beta (1/ms)
}

STATE { n }

INITIAL {
	qt = q10^((celsius-22 (degC))/10 (degC))
	rateConst(v)
	n = ninf
}

BREAKPOINT {
	SOLVE state METHOD cnexp
      g = gbar * n^4 
	ik = g * (v - ek)

}

DERIVATIVE state {
	rateConst(v)
	n' = alpha * (1-n) - beta * n
}

PROCEDURE rateConst(v (mV)) {
	alpha = qt * alphaFkt(v)
	beta = qt * betaFkt(v)
	ninf = alpha / (alpha + beta) 
	tau = 1 / (alpha + beta)
}

FUNCTION alphaFkt(v (mV)) (1/ms) {
	alphaFkt = ca * exp(-(v+cva+vshift)/cka)
}

FUNCTION betaFkt(v (mV)) (1/ms) {
	betaFkt = cb * exp(-(v+cvb+vshift)/ckb)
}