/* Author: Xu Zhang @UConn, Jul., 2018
Neurons in the dentate nucleus (DCN and NO)
DCN: deep cerebellar neuron (glutamatergic), projects onto the TC neuron (Vim)
NO: nucleo-olivary neuron (GABAergic), projects onto ION cells
Modified from Johannes Luthman et al., 2011
*/
// To execute this script individually, please specify the following 4 variables, e.g.:
// DCNrnd = 103 // rng seed
// NOrnd = 104
// noiseSwitch=1
// dt = 0.0125
// Create DCN cell
create DCNcell[5] // Large DCN output cell
create NOcell[5] // Nucleo-olivary cell
proc DCNmechs() {
setParams()
setBiophysics()
insertChannels()
fixCaIons()
}
proc setParams() {
// Set the temperature of the simulation. The model has been titrated to reproduce
// in vivo like firing at celsius = 37.0 (default), while the original GENESIS
// DCN model was constructed with temp = 32 deg celsius.
celsius = 36.0 // Modified by Xu Zhang
TempOrigDCN = 32.0
// TempAnchisi = the temperature in the middle of the given range of room temperature
// recording in Anchisi D, Scelfo B, Tempia F (2001) Postsynaptic currents in deep
// cerebellar nuclei. J Neurophysiol 85:323-331.
TempAnchisi = 24.0
Q10channelGating = 3.0 // Middle of experimentally shown range (2-4) of ion channel gating,
// see Hille 3rd ed (2001), p.51.
Q10synapseGating = 2.0 // (Silver et al., 1996; Otis and Mody, 1992) Synaptic Q10s are given
// for GABA and excitatory synapses in Otis and Mody (1992), and Silver et al. (1996),
// respectively (full references below), with both giving Q10s in the region of 2.
Q10conductances = 1.4 // The middle of the range (1.2-1.5) given in Hille 3rd ed (2001)
// for ion channel conductances (p.51). Also, eg Milburn et al (1995)
// Receptors Channels 3:201-211: The conductance increases steeply with temperature,
// with Q10 ranging from 1.4 to 1.5? However, also note Cao XJ, Oertel D (2005)
// J Neurophysiol 94:821-832. They get the results that some conductances have a
// Q10 of 2 while other channel conductances don't change at all by changing
// temp (Q10=1).
Q10CaConc = 2.0 // Guesswork: I assume that calcium concentration changes due to a
// combination of diffusion (Q10 of ca 1.4) and pumping action (Q10 of enzymatic
// reactions = ca 3)
QdTsynapseTausAnchisi = Q10synapseGating^((celsius - TempAnchisi) / 10.0)
QdTconductanceAnchisi = Q10conductances^((celsius - TempAnchisi) / 10.0)
QdTchannelGating = Q10channelGating^((celsius - TempOrigDCN) / 10.0)
QdTsynapseTaus = Q10synapseGating^((celsius - TempOrigDCN) / 10.0)
QdTconductances = Q10conductances^((celsius - TempOrigDCN) / 10.0)
QdTCaConc = Q10CaConc^((celsius - TempOrigDCN) / 10.0)
// Reversal potentials in mV
SodiumRevPot = 71-10 // Modified by Xu Zhang
PotassiumRevPot = -90+20 // Modified by Xu Zhang
GABARevPot = -75
ExcitSynRevPot = 0
hRevPot = -45
TNCrevPot = -35
// Non-synaptic channel conductances
gNaFsoma = 2.5e-2*QdTconductances/1.5 // Modified by Xu Zhang
gNaPsoma = 8e-4*QdTconductances
gfKdrsoma = 1.5e-2*QdTconductances
gsKdrsoma = 1.25e-2*QdTconductances
gSKsoma = 2.2e-4*QdTconductances
permCaLVAsoma = 1.77e-5*QdTconductances
permCaHVAsoma = 7.5e-6*QdTconductances
tauCaConcSoma = 70/QdTCaConc
kCaCaConcSoma = 3.45e-7
gHsoma = 2e-4*QdTconductances
gTNCsoma = 3e-5*QdTconductances
}
proc setBiophysics() {
// insert biophysics common to all compartments
for i = 0,4 {
DCNcell[i] {
// Passive electrical parameters.
Ra = 35.4 // ohm * cm
cm = 1 // microfarad / cm2
// Modified by Xu Zhang
L = 65 // um
diam = 20.248 // um
PASSCOND = 2.81e-5*QdTconductances // S/cm2 passive conductance
SHELLTHICK = 0.2 // um, the thickness of the calcium-containing shell defined by CaConc.mod.
insert dcnpas
gbar_dcnpas = PASSCOND
}
NOcell[i] {
// Passive electrical parameters.
Ra = 35.4 // 2093.6 // ohm * cm
cm = 1 // 0.2838 // microfarad / cm2
// Modified by Xu Zhang
// Note: the geometry is not realistic, the L here is set only to match the I-f experimental data from Najac & Raman, 2015
L = 200 // um
diam = 14.8843 // um
PASSCOND = 2.81e-5*QdTconductances // 4.2362e-5*QdTconductances // S/cm2 passive conductance
insert dcnpas
gbar_dcnpas = PASSCOND
}
}
}
proc insertChannels() {
// For each type of compartment, insert NMODL mechanisms
// (ion channels and ca-concentration).
// The qdeltat variable is GLOBAL in the NMODLs, meaning that it only needs to be
// specified once for each mechanism, here in the DCNcell (which contains a copy of
// each mechanism).
for i = 0,4 {
DCNcell[i] {
insert dcnNaF
gbar_dcnNaF = gNaFsoma
qdeltat_dcnNaF = QdTchannelGating
insert dcnNaP
gbar_dcnNaP = gNaPsoma
qdeltat_dcnNaP = QdTchannelGating
// ena = SodiumRevPot
ena = SodiumRevPot
insert dcnfKdr
gbar_dcnfKdr = gfKdrsoma
qdeltat_dcnfKdr = QdTchannelGating
insert dcnsKdr
gbar_dcnsKdr = gsKdrsoma
qdeltat_dcnsKdr = QdTchannelGating
insert dcnSK
gbar_dcnSK = gSKsoma
qdeltat_dcnSK = QdTchannelGating
// ek = PotassiumRevPot
ek = PotassiumRevPot
insert dcnh
gbar_dcnh = gHsoma
qdeltat_dcnh = QdTchannelGating
eh_dcnh = hRevPot
insert dcnTNC
gbar_dcnTNC = gTNCsoma
eTNC_dcnTNC = TNCrevPot
// calcium channels - they use the Goldman-Hodgkin-Katz (GHK) current equation
// and so don't have a set reversal potential.
insert dcnCaLVA
perm_dcnCaLVA = permCaLVAsoma
qdeltat_dcnCaLVA = QdTchannelGating
insert dcnCaHVA
perm_dcnCaHVA = permCaHVAsoma
qdeltat_dcnCaHVA = QdTchannelGating
// insert a hypothetical shell below the membrane of the cell to keep track of the
// calcium entering the cell through the CaHVA and CaLVA channels, respectively.
// The resulting calcium concentration is used to calculate the current flow through
// through those channels.
// For the CaHVA channel:
insert dcnCaConc
tauCa_dcnCaConc = tauCaConcSoma
kCa_dcnCaConc = kCaCaConcSoma
// For the DCNcell, the calculation of shell thickness is different from
// the dendrites since it is a sphere in GENESIS and a cylinder
// in NEURON. See how it's done in GENESIS file cn_comp_dj10.g and
// divide that expression by the surface area of the NEURON DCNcell to get
// the following expression:
depth_dcnCaConc = SHELLTHICK - 2*SHELLTHICK^2/diam + \
4*SHELLTHICK^3/(3*diam^2) // =0.196215
// For the CaLVA channel:
insert dcnCalConc
tauCal_dcnCalConc = tauCaConcSoma
kCal_dcnCalConc = kCaCaConcSoma
depth_dcnCalConc = SHELLTHICK - 2*SHELLTHICK^2/diam + \
4*SHELLTHICK^3/(3*diam^2) // =0.196215
}
NOcell[i] {
insert dcnNaF
gbar_dcnNaF = gNaFsoma
qdeltat_dcnNaF = QdTchannelGating
ena = SodiumRevPot
insert dcnfKdr
gbar_dcnfKdr = gfKdrsoma
qdeltat_dcnfKdr = QdTchannelGating
insert dcnsKdr
gbar_dcnsKdr = gsKdrsoma*2
qdeltat_dcnsKdr = QdTchannelGating
ek = PotassiumRevPot
}
}
} // end proc insertChannels()
proc fixCaIons() {
// Set some specifications for the Ca and Cal ions. The following ion_style
// statements don't affect the behaviour of the model but compared to not giving
// them, speed up the simulation ca 5%, probably due to preventing eca from being
// calculated each dt. ion_style has to be set for each compartment where the Ca ion
// is used but gives no error when set for those compartments that don't use the ion.
forall {
ion_style("ca_ion", 2, 0, 0, 0, 1)
}
forall {
ion_style("cal_ion", 2, 0, 0, 0, 1)
}
// Set the extracellular calcium concentrations (mM):
cao0_ca_ion = 2
calo0_cal_ion = 2
}
DCNmechs()
// Membrane noise in DCN
objref DCN_noisc, DCNnoise[5]
DCN_noisc = new Random(DCNrnd)
DCN_noisc.normal(0, 5e-2)
for i = 0,4 {
DCNcell[i] DCNnoise[i] = new NoisyCurrent(0.2)
DCN_noisc.play(&DCNnoise[i].noise)
}
// Membrane noise in NO
objref NO_noisc, NOnoise[5]
NO_noisc = new Random(NOrnd)
NO_noisc.normal(0, 2e-2)
for i = 0,4 {
NOcell[i] NOnoise[i] = new NoisyCurrent(0.2)
NO_noisc.play(&NOnoise.noise)
}
// Offset Current: keep spontaneous firing rate at ~50Hz as described in Najac & Raman, 2015
objref ocDCN[5]
for i = 0,4 {
DCNcell[i] ocDCN[i] = new IClamp(0.5)
ocDCN[i].amp = -5.3e-2
ocDCN[i].del = 0
ocDCN[i].dur = 1e10
}
// Offset Current: keep spontaneous firing rate at ~20Hz as described in Najac & Raman, 2015
objref ocNO[5]
for i = 0,4 {
NOcell[i] ocNO[i] = new IClamp(0.5)
ocNO[i].amp = -3e-2
ocNO[i].del = 0
ocNO[i].dur = 1e10
}