Cerebellar nuclear neuron (Sudhakar et al., 2015)

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Accession:185513
"... In this modeling study, we investigate different forms of Purkinje neuron simple spike pause synchrony and its influence on candidate coding strategies in the cerebellar nuclei. That is, we investigate how different alignments of synchronous pauses in synthetic Purkinje neuron spike trains affect either time-locking or rate-changes in the downstream nuclei. We find that Purkinje neuron synchrony is mainly represented by changes in the firing rate of cerebellar nuclei neurons. ..."
Reference:
1 . Sudhakar SK, Torben-Nielsen B, De Schutter E (2015) Cerebellar Nuclear Neurons Use Time and Rate Coding to Transmit Purkinje Neuron Pauses. PLoS Comput Biol 11:e1004641 [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 deep nucleus neuron;
Channel(s): I Na,p; I T low threshold; I h; I Sodium;
Gap Junctions:
Receptor(s): NMDA; Glutamate; Gaba;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Rate-coding model neurons; Rebound firing;
Implementer(s):
Search NeuronDB for information about:  NMDA; Glutamate; Gaba; I Na,p; I T low threshold; I h; I Sodium; Gaba; Glutamate;
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SudhakarEtAl2015
readme.html
CaConc.mod *
CaHVA.mod *
CaL.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
vecevent.mod *
cellids.dat
cellids_n.dat
datasp_ex1.dat
datasp1.dat
DCN_init_model1.hoc
DCN_init_model2.hoc
DCN_init_model2_highgain.hoc
DCN_init_model2_lowgain.hoc
DCN_init_model2_medgain.hoc
DCN_init_model3.hoc
DCN_mechs1.hoc *
DCN_mechs2.hoc
DCN_morph.hoc *
DCN_params.hoc
l_ex1.dat
l1.dat
model1_params.hoc
model2_params.hoc
model2_params_highgain.hoc
model2_params_lowgain.hoc
model2_params_medgain.hoc
model3_params.hoc
mosinit.hoc
pausebeg.dat
pausebeg_n.dat
screenshot.png
                            
TITLE Intracellular calcium concentration in deep cerebellar nucleus (DCN) neuron
COMMENT
    This mechanism keeps track of intracellular calcium entering the cell through
    the CaHVA channel. The calcium concentration is for a hypothetical shell
    below the membrane of the cell, and affects the conductance level of the SK.mod
    channel mechanism. In addition, it affects the conductance of the CaHVA channel
    which uses the GHK equation to calculate current flow.
    Translated from GENESIS by Johannes Luthman and Volker Steuber.
ENDCOMMENT

NEURON {
    SUFFIX CaConc
    USEION ca READ ica WRITE cai
    RANGE cai, kCa, depth
    GLOBAL tauCa
}

UNITS {
    (molar) = (1 / liter)
    (mM) = (millimolar)
    (mV) = (millivolt)
    (mA) = (milliamp)
    PI = (pi) (1)
}

PARAMETER {
    : qdeltat has been skipped here and is used via the division of this NMODL's
    : tauCa when it's inserted (in hoc).

    : kCa in the following is given for the soma and shall be adjusted
    : from hoc when the CaConc model is inserted in a dendrite: 1.04e-6
    : in the dendritic compartments units. kCa is here given as 1 / coulombs
    : instead of moles / coulomb as in the GENESIS code since mole
    : in NEURON simply equals the number 6.022 * 10e23
    kCa = 3.45e-7 (1/coulomb)
    tauCa = 70 (ms)
    caiBase = 50e-6 (mM) : the assumed resting level of intracellular calcium
    depth = 0.2 (micron)
}

ASSIGNED {
    C (kilo / m3 / s)
    D (kilo / m3 / s)
    ica (mA/cm2)
}

STATE {
    cai (mM)
}

INITIAL {
    cai = caiBase
}

BREAKPOINT {
    SOLVE states METHOD cnexp
}

DERIVATIVE states {
    C = (cai - caiBase) / tauCa
	D = - kCa / depth * ica * (1e4)
    cai' = D - C
}