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Unverified Commit 1a9e3d5f authored by Thorsten Hater's avatar Thorsten Hater Committed by GitHub
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Add Allen Institute's Exp2Syn to Arbor. (#2293)

Add the Allen Institute flavoured Exp2Syn to the Allen catalogue.
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......@@ -11,7 +11,7 @@ make_catalogue(
make_catalogue(
NAME allen
MOD CaDynamics Ca_HVA Ca_LVA Ih Im Im_v2 K_P K_T Kd Kv2like Kv3_1 NaTa NaTs NaV Nap SK
MOD CaDynamics Ca_HVA Ca_LVA Ih Im Im_v2 K_P K_T Kd Kv2like Kv3_1 NaTa NaTs NaV Nap SK Exp2Syn
VERBOSE ${ARB_CAT_VERBOSE}
ADD_DEPS ON)
......
COMMENT
Two state kinetic scheme synapse described by rise time tau1,
and decay time constant tau2. The normalized peak condunductance is 1.
Decay time MUST be greater than rise time.
The solution of A->G->bath with rate constants 1/tau1 and 1/tau2 is
A = a*exp(-t/tau1) and
G = a*tau2/(tau2-tau1)*(-exp(-t/tau1) + exp(-t/tau2))
where tau1 < tau2
If tau2-tau1 is very small compared to tau1, this is an alphasynapse with time constant tau2.
If tau1/tau2 is very small, this is single exponential decay with time constant tau2.
The factor is evaluated in the initial block
such that an event of weight 1 generates a
peak conductance of 1.
Because the solution is a sum of exponentials, the
coupled equations can be solved as a pair of independent equations
by the more efficient cnexp method.
ENDCOMMENT
NEURON {
POINT_PROCESS Exp2Syn
RANGE tau1, tau2, erev
NONSPECIFIC_CURRENT i
}
UNITS {
(nA) = (nanoamp)
(mV) = (millivolt)
(uS) = (microsiemens)
}
PARAMETER {
v (mV)
tau1 = 0.1 (ms) <1e-9,1e9>
tau2 = 10 (ms) <1e-9,1e9>
erev = 0 (mV)
}
ASSIGNED {
factor
}
STATE {
A (uS)
B (uS)
}
INITIAL {
LOCAL tp
: NOTE Arbor doesn't allow this, so removed for now
:if (tau1 > 0.9999*tau2) { tau1 = 0.9999*tau2 }
:if (tau1 < 1e-9*tau2) { tau1 = tau2*1e-9 }
A = 0
B = 0
tp = (tau1*tau2)/(tau2 - tau1) * log(tau2/tau1)
factor = -exp(-tp/tau1) + exp(-tp/tau2)
factor = 1/factor
}
BREAKPOINT {
SOLVE state METHOD cnexp
LOCAL g
g = B - A
i = g*(v - erev)
}
DERIVATIVE state {
A' = -A/tau1
B' = -B/tau2
}
NET_RECEIVE(weight (uS)) {
A = A + weight*factor
B = B + weight*factor
}
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