COMMENT
This T-type calcium current was originally reported in Wang XJ et al 1991
This file supplies a version of this current identical to Quadroni and Knopfel 1994
except for gbar and Erev (see notes below).
ENDCOMMENT
NEURON {
SUFFIX lva
: NONSPECIFIC_CURRENT i
USEION ca WRITE ica
RANGE Erev,g, gbar, i
RANGE k, alpha_1, alpha_2, beta_1, beta_2, V_s
GLOBAL mytaum, myminf
}
UNITS {
(S) = (siemens)
(mV) = (millivolt)
(mA) = (milliamp)
}
PARAMETER {
gbar = 0.4e-3 (S/cm2) < 0, 1e9 > : Quadroni and Knopfel use 166e-6
Erev = 120 (mV) : orig from Wang XJ et al 1991 was 120
: note: Quadroni and Knopfel 1994 table 1 use 80 instead
V_s = 0 (mV) : used to describe effect of changing extracellular [Ca]
: 0 corresponds to [Ca]outside = 3 mM (p 841)
}
ASSIGNED {
ica (mA/cm2)
i (mA/cm2)
v (mV)
g (S/cm2)
k
alpha_1 (1)
alpha_2 (1)
beta_1 (1)
beta_2 (1)
mytaum (ms)
myminf (1)
}
STATE { m h d }
BREAKPOINT {
SOLVE states METHOD cnexp
g = gbar * m^3 * h
ica = g * (v - Erev)
i = ica : used only to display the value of the current (section.i_lva(0.5))
}
INITIAL {
LOCAL C, E
: assume that v has been constant for a long time
: (derivable from rate equations in DERIVATIVE block at equilibrium)
rates(v)
m = minf(v)
: h and d are intertwined so more complex than above equilib state for m
C = beta_1 / alpha_1
E = alpha_2 / beta_2
h = E / (E * C + E + C)
d = 1 - (1 + C) * h
}
DERIVATIVE states{
rates(v)
m' = (minf(v) - m)/taum(v) : alpham(v) * (1 - m) - betam(v) * m
h' = alpha_1 * (1 - h - d) - beta_1 * h
d' = beta_2 * (1 - h - d) - alpha_2 * d
}
FUNCTION minf(Vm (mV)) (1) {
minf = 1.0 / (1.0 + exp(-(Vm + V_s + 63)/7.8))
myminf = minf
}
FUNCTION taum(Vm (mV)) (ms) {
taum = (1.7 + exp( -(Vm + V_s + 28.8)/13.5 )) / (1.0 + exp( -(Vm + V_s + 63)/7.8) )
mytaum = taum
}
PROCEDURE rates(Vm(mV)) { LOCAL tau_2
k = (0.25 + exp((Vm + V_s + 83.5)/6.3))^0.5 - 0.5
tau_2 = 240.0 / (1 + exp((Vm + V_s + 37.4)/30)) : same as tau2 p 842 equation (15)
alpha_1 = exp( -(Vm + V_s +160.3)/17.8 ) : p 842 equation (14)
beta_1 = k * alpha_1
alpha_2 = 1.0 / ( tau_2 * (1.0 + k) )
beta_2 = k * alpha_2
}