TITLE naf.mod
COMMENT
Regular and fast (as opposed to persistent) sodium current for pyramidal cell and interneurons defined in
Timofeev et. al., 2000, Cerebral Cortex (https://doi.org/10.1093/cercor/10.12.1185)
and Bazhenov et. al. 2002 (J Neuro) and
Chen et. al., 2012, J. Physiol. (doi: https://doi.org/10.1113/jphysiol.2012.227462)
This code is adapted from hh.mod distributed with NEURON source code
ENDCOMMENT
UNITS {
(mA) = (milliamp)
(mV) = (millivolt)
(S) = (siemens)
}
? interface
NEURON {
SUFFIX naf
USEION na READ ena WRITE ina
RANGE gnabar, gna
RANGE minf, hinf, mtau, htau
:THREADSAFE : assigned GLOBALs will be per thread
}
PARAMETER {
gnabar = 0.0015 (S/cm2) <0,1e9>
ena = 50 (mV)
}
STATE {
m h
}
ASSIGNED {
v (mV)
:celsius (degC)
gna (S/cm2)
ina (mA/cm2)
minf hinf
mtau (ms) htau (ms)
}
? currents
BREAKPOINT {
SOLVE states METHOD cnexp
gna = gnabar*m*m*m*h
ina = 2.952882641412121*gna*(v - ena) :2.95 is q_T from Timofeev 2000; also, C++ code prescribe 2.3^((36-23)/10)
}
INITIAL {
rates(v)
m = minf
h = hinf
}
? states
DERIVATIVE states {
rates(v)
m' = (minf-m)/mtau
h' = (hinf-h)/htau
}
? rates
PROCEDURE rates(v(mV)) { :Computes rate and other constants at current v.
:Call once from HOC to initialize inf at resting v.
LOCAL a, b, sum, c, d
UNITSOFF
:"m" sodium activation system
a = 0.182 * vtrap(-(v+25),9)
b = 0.124 * vtrap(v+25,9) :note the lack of a negative sign in the first argument to vtrap
sum = a + b
mtau = 0.3386521313023745/sum :numerator is 1/2.952882641412121
minf = a/sum
:"h" sodium inactivation system
hinf = 1/(1 + exp((v+55)/6.2) )
c = 0.024 * vtrap(-(v+40),5)
d = 0.0091 * vtrap(v+65,5) :this is actually what is implemented in Bazhenov 2002 C++ code (https://modeldb.science/28189?tab=1)
:d = 0.0091 * vtrap(-(v-85),5) :this is what is listed in Timofeev 2000 appendix, as well as in Chen 2012
htau = 0.3386521313023745/(c+d)
}
FUNCTION vtrap(x,y) { :Traps for 0 in denominator of rate eqns.
if (fabs(x/y) < 1e-6) {
vtrap = y*(1 - x/y/2) :derived by Taylor expanding exp to quadratic term, then binomial approximation
}else{
vtrap = x/(exp(x/y) - 1)
}
}
UNITSON