Compartmentalization of GABAergic inhibition by dendritic spines (Chiu et al. 2013)

 Download zip file   Auto-launch 
Help downloading and running models
Accession:143604
A spiny dendrite model supports the hypothesis that only inhibitory inputs on spine heads, not shafts, compartmentalizes inhibition of calcium signals to spine heads as seen in paired inhibition with back-propagating action potential experiments on prefrontal cortex layer 2/3 pyramidal neurons in mouse (Chiu et al. 2013).
Reference:
1 . Chiu CQ, Lur G, Morse TM, Carnevale NT, Ellis-Davies GC, Higley MJ (2013) Compartmentalization of GABAergic inhibition by dendritic spines. Science 340:759-62 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Synapse; Dendrite;
Brain Region(s)/Organism: Neocortex;
Cell Type(s): Neocortex V1 L2/6 pyramidal intratelencephalic GLU cell;
Channel(s): I Na,t; I L high threshold; I K;
Gap Junctions:
Receptor(s): GabaA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Dendritic Action Potentials; Influence of Dendritic Geometry;
Implementer(s): Carnevale, Ted [Ted.Carnevale at Yale.edu]; Morse, Tom [Tom.Morse at Yale.edu];
Search NeuronDB for information about:  Neocortex V1 L2/6 pyramidal intratelencephalic GLU cell; GabaA; I Na,t; I L high threshold; I K;
/
singleDendrite
mod
ca.mod
ca_a1g.mod
ca_a1h.mod *
cad.mod
constant.mod
distr.mod *
exp2syncur.mod
exp2synsat.mod
im.mod *
kca.mod *
km.mod *
kv.mod
multiclamp.mod
na.mod
zoidsyn.mod *
                            
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 -> 0 then we have a alphasynapse.
and if tau1 -> 0 then we have just single exponential decay.

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.

20120413 TMM modified to include conductance saturation: the
conductance, g, will not exceed "saturation"; however when simulated
past saturation, g will take longer to drop back below saturation.

ENDCOMMENT

NEURON {
	POINT_PROCESS Exp2SynSat
	RANGE tau1, tau2, e, i, saturation
	NONSPECIFIC_CURRENT i

	RANGE g
}

UNITS {
	(nA) = (nanoamp)
	(mV) = (millivolt)
	(uS) = (microsiemens)
}

PARAMETER {
	tau1=.1 (ms) <1e-9,1e9>
	tau2 = 10 (ms) <1e-9,1e9>
	e=0	(mV)
        saturation (uS) : assign in hoc (typical real synapse 
                        : value 0.0004 = 0.4 nS)
}

ASSIGNED {
	v (mV)
	i (nA)
	g (uS)
	factor
}

STATE {
	A (uS)
	B (uS)
}

INITIAL {
	LOCAL tp
	if (tau1/tau2 > .9999) {
		tau1 = .9999*tau2
	}
	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
	g = B - A
        if (g>saturation) {
              g = saturation
        }
	i = g*(v - e)
}

DERIVATIVE state {
	A' = -A/tau1
	B' = -B/tau2
}

NET_RECEIVE(weight (uS)) {
	A = A + weight*factor
	B = B + weight*factor
}

Loading data, please wait...