CA1 pyramidal neuron: synaptically-induced bAP predicts synapse location (Sterratt et al. 2012)

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Accession:144490
This is an adaptation of Poirazi et al.'s (2003) CA1 model that is used to measure BAP-induced voltage and calcium signals in spines after simulated Schaffer collateral synapse stimulation. In the model, the peak calcium concentration is highly correlated with soma-synapse distance under a number of physiologically-realistic suprathreshold stimulation regimes and for a range of dendritic morphologies. There are also simulations demonstrating that peak calcium can be used to set up a synaptic democracy in a homeostatic manner, whereby synapses regulate their synaptic strength on the basis of the difference between peak calcium and a uniform target value.
Reference:
1 . Sterratt DC, Groen MR, Meredith RM, van Ooyen A (2012) Spine calcium transients induced by synaptically-evoked action potentials can predict synapse location and establish synaptic democracy PLoS Comput Biol 8(6):e1002545 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s): Hippocampus CA1 pyramidal cell;
Channel(s): I Na,t; I L high threshold; I T low threshold; I A; I K; I M; I Mixed; I R; I_AHP;
Gap Junctions:
Receptor(s): AMPA; NMDA;
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Dendritic Action Potentials; Synaptic Plasticity;
Implementer(s): Sterratt, David ; Groen, Martine R [martine.groen at gmail.com];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal cell; AMPA; NMDA; I Na,t; I L high threshold; I T low threshold; I A; I K; I M; I Mixed; I R; I_AHP;
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bpap
CA1_multi
mechanism
cad.mod *
cagk.mod *
cal.mod *
calH.mod *
car.mod *
cat.mod *
d3.mod *
gabaa.mod *
gabab.mod *
glutamate.mod *
h.mod *
hha_old.mod *
hha2.mod *
kadist.mod *
kaprox.mod *
kca.mod *
km.mod *
nap.mod *
nmda.mod *
somacar.mod *
mosinit.hoc.old *
mosinit.poirazi.hoc *
                            
TITLE Ca L-type channel with high treshold of activation
: inserted in distal dendrites to account for distally
: restricted initiation of Ca++ spikes
: uses channel conductance (not permeability)
: written by Yiota Poirazi, 1/8/00 poirazi@LNC.usc.edu

NEURON {
	SUFFIX calH
	USEION ca READ eca WRITE ica
        RANGE gcalbar, m, h
	RANGE inf, fac, tau
}

UNITS {
	(mA) = (milliamp)
	(mV) = (millivolt)
}

INDEPENDENT {t FROM 0 TO 1 WITH 1 (ms)}

PARAMETER {          : parameters that can be entered when function is called in cell-setup
        v               (mV)
        celsius = 34	(degC)
	dt              (ms)
        gcalbar = 0     (mho/cm2) : initialized conductance
	eca = 140       (mV)      : Ca++ reversal potential
        }

STATE {	m h }                     : unknown activation and inactivation parameters to be solved in the DEs  

ASSIGNED {                        : parameters needed to solve DE
	ica (mA/cm2)
        inf[2]
	fac[2]
	tau[2]
}

BREAKPOINT {
	SOLVE states
	ica = gcalbar*m*m*m*h*(v - eca)       
	}

INITIAL {
        m = 0    : initial activation parameter value
	h = 1    : initial inactivation parameter value
        states()
	ica = gcalbar*m*m*m*h*(v - eca) : initial Ca++ current value
     	}

PROCEDURE calcg() {
	mhn(v*1(/mV))
	m = m + fac[0]*(inf[0] - m)
	h = h + fac[1]*(inf[1] - h)
	}	

PROCEDURE states() {	: exact when v held constant
	calcg()
	VERBATIM
	return 0;
	ENDVERBATIM
}

FUNCTION varss(v, i) {
	if (i==0) { 
             varss = 1 / (1 + exp((v+37)/(-1)))  : Ca activation 
	}
	else if (i==1) { 
             varss = 1 / (1 + exp((v+41)/(0.5))) : Ca inactivation 
	}
}

FUNCTION vartau(v, i) {
	if (i==0) {
           vartau = 3.6  : activation variable time constant
        }
	else if (i==1) {
:           vartau = 25   : inactivation variable time constant
           vartau = 29   : inactivation variable time constant
        }
}	

PROCEDURE mhn(v) {LOCAL a, b :rest = -70
:      TABLE inf, fac DEPEND dt, celsius FROM -100 TO 100 WITH 200
	FROM i=0 TO 1 {
		tau[i] = vartau(v,i)
		inf[i] = varss(v,i)
		fac[i] = (1 - exp(-dt/tau[i]))
	}
}
















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