TITLE High voltage activated calcium current (CaHVA) of deep cerebellar nucleus (DCN) neuron
COMMENT
Translated from GENESIS by Johannes Luthman and Volker Steuber.
This mechanism and the other calcium channel (CaLVA.mod) are the only channel
mechanisms of the DCN model that use the GHK mechanism to calculate reversal
potential. Thus, extracellular Ca concentration is of importance and shall be
set from hoc.
Calcium entering the neuron through this channel is kept track of by CaConc.mod
and affects the conductance of the SK.mod channel mechanism.
ENDCOMMENT
NEURON {
SUFFIX dcnCaHVA
USEION ca READ cai, cao WRITE ica
RANGE perm, ica, m, cai
GLOBAL qdeltat
}
UNITS {
(mA) = (milliamp)
(mV) = (millivolt)
(molar) = (1/liter)
(mM) = (millimolar)
}
PARAMETER {
qdeltat = 1
perm = 7.5e-6 (cm/seconds)
}
ASSIGNED {
v (mV)
cai (mM)
cao (mM)
ica (mA/cm2)
minf (1)
taum (ms)
celsius (degC)
T (kelvin)
A (1)
}
STATE {
m
}
INITIAL {
T = 273.15 + celsius
rate(v)
m = minf
}
BREAKPOINT {
SOLVE states METHOD cnexp
A = getGHKexp(v)
: "4.47814e6 * v / T" in the following is the simplification of the GHK
: current equation's (z^2 * F^2 * (0.001) * v) / (R * T). [*(0.001) is to get
: volt from NEURON's mV.] Together with the simplification in getGHKexp()
: (below), this speeds up the whole DCN simulation (without synapses) by 8%.
: The division of the calcium concentrations (mM) by 1000 gives molar as
: required by the GHK current equation.
ica = perm * m*m*m * (4.47814e6 * v / T) * ((cai/1000) - (cao/1000) * A) / (1 - A)
}
DERIVATIVE states {
rate(v)
m' = (minf - m)/taum
}
PROCEDURE rate(v(mV)) {
TABLE minf, taum FROM -150 TO 100 WITH 300
if(fabs(v + 34.5) < 1e-6) {
minf = 1 / (1 + exp((v + 34.50001) / -9))
} else {
minf = 1 / (1 + exp((v + 34.5) / -9))
}
taum = 1 / ((31.746 * ((exp((v - 5) / -13.89) + 1) ^ -1)) + (3.97e-4 * (v + 8.9)) * ((exp((v + 8.9) / 5) - 1) ^ -1))
taum = taum / qdeltat
}
FUNCTION getGHKexp(v(mV)) {
TABLE DEPEND T FROM -150 TO 100 WITH 300
getGHKexp = exp(-23.20764929 * v / T): =the calculated values of
: getGHKexp = exp((-z * F * (0.001) * v) / (R * T)).
}