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KV1 channel governs cerebellar output to thalamus (Ovsepian et al. 2013)

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Accession:150024
The output of the cerebellum to the motor axis of the central nervous system is orchestrated mainly by synaptic inputs and intrinsic pacemaker activity of deep cerebellar nuclear (DCN) projection neurons. Herein, we demonstrate that the soma of these cells is enriched with KV1 channels produced by mandatory multi-merization of KV1.1, 1.2 alpha andKV beta2 subunits. Being constitutively active, the K+ current (IKV1) mediated by these channels stabilizes the rate and regulates the temporal precision of self-sustained firing of these neurons. ... Through the use of multi-compartmental modelling and ... the physiological significance of the described functions for processing and communication of information from the lateral DCN to thalamic relay nuclei is established.
Reference:
1 . Ovsepian SV, Steuber V, Le Berre M, O'Hara L, O'Leary VB, Dolly JO (2013) A defined heteromeric KV1 channel stabilizes the intrinsic pacemaking and regulates the output of deep cerebellar nuclear neurons to thalamic targets. J Physiol 591:1771-91 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Channel/Receptor;
Brain Region(s)/Organism:
Cell Type(s): Cerebellum deep nucleus neuron;
Channel(s): I Na,p; I Na,t; I L high threshold; I T low threshold; I K; I h; I CAN; I_Ks;
Gap Junctions:
Receptor(s): AMPA; NMDA;
Gene(s): Kv1.1 KCNA1; Kv1.2 KCNA2;
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Bursting; Ion Channel Kinetics; Active Dendrites; Detailed Neuronal Models; Intrinsic plasticity; Rebound firing;
Implementer(s): Steuber, Volker [v.steuber at herts.ac.uk]; Luthman, Johannes [jwluthman at gmail.com];
Search NeuronDB for information about:  AMPA; NMDA; I Na,p; I Na,t; I L high threshold; I T low threshold; I K; I h; I CAN; I_Ks;
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CNModel_May2013
readme.txt
CaConc.mod *
CaHVA.mod *
CalConc.mod *
CaLVA.mod *
DCNsyn.mod *
DCNsynGABA.mod *
DCNsynNMDA.mod *
fKdr.mod *
GammaStim.mod *
h.mod *
Ifluct8.mod *
NaF.mod *
NaP.mod *
pasDCN.mod *
SK.mod *
sKdr.mod *
TNC.mod *
DCN_cip_axis_main.hoc
DCN_cip_fi_main.hoc
DCN_mechs1.hoc *
DCN_mechs2.hoc
DCN_morph.hoc *
DCN_params.hoc
DCN_params_axis.hoc
DCN_params_fi_init.hoc
DCN_params_rebound.hoc
DCN_rebound_main.hoc
DCN_recording.hoc
DCN_spontact_loop_main.hoc
                            
COMMENT by Johannes Luthman: 
Based on NEURON 6.0's built-in exp2syn.mod.
Changes made to the original: 
* tau1 renamed tauRise; tau2, tauFall
* restructuring of NEURON block
* microsiemens changed to siemens for consistency with the other NMODLs.


Original comment: 
Two state kinetic scheme synapse described by rise time tauRise,
and decay time constant tauFall. The normalized peak condunductance is 1.
Decay time MUST be greater than rise time.

The solution of A->G->bath with rate constants 1/tauRise and 1/tauFall is
 A = a*exp(-t/tauRise) and
 G = a*tauFall/(tauFall-tauRise)*(-exp(-t/tauRise) + exp(-t/tauFall))
	where tauRise < tauFall

If tauFall-tauRise -> 0 then we have a alphasynapse.
and if tauRise -> 0 then we have just single exponential decay.

The factor is evaluated in the
initial block such that an event of weight 1 generates a
peak conductance of 1.

Because the solution is a sum of exponentials, the
coupled equations can be solved as a pair of independent equations
by the more efficient cnexp method.

ENDCOMMENT

NEURON {
	POINT_PROCESS DCNsyn
	NONSPECIFIC_CURRENT i
	RANGE g, i, e, tauRise, tauFall
}

UNITS {
	(nA) = (nanoamp)
	(mV) = (millivolt)
}

PARAMETER {
	tauRise = 1 (ms)
	tauFall = 1 (ms)
	e = 0 (mV)
}

ASSIGNED {
	v (mV)
	i (nA)
	g (microsiemens)
	factor
}

STATE {
	A (microsiemens)
	B (microsiemens)
}

INITIAL {
	LOCAL tp
	if (tauRise/tauFall > .9999) {
		tauRise = .9999*tauFall
	}
	A = 0
	B = 0
	tp = (tauRise*tauFall)/(tauFall - tauRise) * log(tauFall/tauRise)
	factor = -exp(-tp/tauRise) + exp(-tp/tauFall)
	factor = 1/factor
}

BREAKPOINT {
	SOLVE state METHOD cnexp
	g = B - A
	i = g*(v - e)
}

DERIVATIVE state {
	A' = -A/tauRise
	B' = -B/tauFall
}

NET_RECEIVE(weight (microsiemens)) {
	state_discontinuity(A, A + weight*factor)
	state_discontinuity(B, B + weight*factor)
}

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