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
mod
BK_Slow.mod *
CaP.mod *
capmax.mod *
CaT.mod *
cdp_AIS.mod *
cdp_smooth.mod *
cdp_soma.mod *
cdp_spiny.mod *
distr.mod
ih.mod *
Kv1.mod *
kv3.mod *
kv4f.mod *
kv4s.mod *
mslo.mod *
nap.mod *
narsg.mod *
peak.mod *
pkjlk.mod *
SK2.mod *
syn2.mod *
                            
: this model is built-in to neuron with suffix syn2

COMMENT
synaptic current with exponential rise and decay conductance defined by
        i = g * (v - e)      i(nanoamps), g(micromhos);
        where
         g = 0 for t < onset and
         g=amp*((1-exp(-(t-onset)/tau0))-(1-exp(-(t-onset)/tau1)))
          for t > onset
ENDCOMMENT
					       
INDEPENDENT {t FROM 0 TO 1 WITH 1 (ms)}

NEURON {
	POINT_PROCESS syn2
	RANGE onset, tau0, tau1, gmax, e, i, myv
	NONSPECIFIC_CURRENT i
}
UNITS {
	(nA) = (nanoamp)
	(mV) = (millivolt)
	(umho) = (micromho)
}

PARAMETER {
	onset=0  (ms)
	tau0=0.2 (ms)
	tau1=3.0 (ms)
	gmax=0 	 (umho)
	e=0	 (mV)
	v	 (mV)
}

ASSIGNED { i (nA)  g (umho) myv (mV)}

LOCAL   a[2]
LOCAL   tpeak
LOCAL   adjust
LOCAL   amp

BREAKPOINT {
	myv = v
        g = cond(t)
	i = g*(v - e)
}

FUNCTION myexp(x) {
	if (x < -100) {
	myexp = 0
	}else{
	myexp = exp(x)
	}
}

FUNCTION cond(x) {
	tpeak=tau0*tau1*log(tau0/tau1)/(tau0-tau1)
	adjust=1/((1-myexp(-tpeak/tau0))-(1-myexp(-tpeak/tau1)))
	amp=adjust*gmax
	if (x < onset) {
		cond = 0
	}else{
		a[0]=1-myexp(-(x-onset)/tau0)
		a[1]=1-myexp(-(x-onset)/tau1)
		cond = amp*(a[0]-a[1])
	}
}