Purkinje neuron network (Zang et al. 2020)

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Accession:266799
Both spike rate and timing can transmit information in the brain. Phase response curves (PRCs) quantify how a neuron transforms input to output by spike timing. PRCs exhibit strong firing-rate adaptation, but its mechanism and relevance for network output are poorly understood. Using our Purkinje cell (PC) model we demonstrate that the rate adaptation is caused by rate-dependent subthreshold membrane potentials efficiently regulating the activation of Na+ channels. Then we use a realistic PC network model to examine how rate-dependent responses synchronize spikes in the scenario of reciprocal inhibition-caused high-frequency oscillations. The changes in PRC cause oscillations and spike correlations only at high firing rates. The causal role of the PRC is confirmed using a simpler coupled oscillator network model. This mechanism enables transient oscillations between fast-spiking neurons that thereby form PC assemblies. Our work demonstrates that rate adaptation of PRCs can spatio-temporally organize the PC input to cerebellar nuclei.
Reference:
1 . Zang Y, Hong S, De Schutter E (2020) Firing rate-dependent phase responses of Purkinje cells support transient oscillations. Elife [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Realistic Network;
Brain Region(s)/Organism: Cerebellum;
Cell Type(s): Cerebellum Purkinje GABA cell;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON; MATLAB;
Model Concept(s): Phase Response Curves; Action Potentials; Spatio-temporal Activity Patterns; Synchronization; Action Potential Initiation; Oscillations;
Implementer(s): Zang, Yunliang ; Hong, Sungho [shhong at oist.jp];
Search NeuronDB for information about:  Cerebellum Purkinje GABA cell;
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PRC_network_code
figure1
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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)
}







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