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: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 GLU 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 GLU 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
datastore
pars
plots
poirazi-nmda-car
tests
validation-plots
README.txt
ampa_forti.mod
cacum.mod
cad.mod *
cagk.mod
cal.mod
calH.mod
car.mod
car_mag.mod
cat.mod
d3.mod *
h.mod
hha_old.mod
hha2.mod
kadist.mod
kaprox.mod
kca.mod
km.mod
nap.mod
nmda_andr.mod
somacar.mod
binaverages.m
bpap-cell.hoc
bpap-data.hoc
bpap-dendburst.hoc
bpap-graphics.hoc
bpap-gui.hoc
bpap-gui.ses
bpap-pars.hoc
bpap-record.hoc
bpap-run.hoc
bpap-scaling.hoc
bpap-sims.hoc
bpap-sims-cell1.hoc
bpap-sims-cell2.hoc
bpap-sims-scaling.hoc
bpap-somainj.hoc
bpap-spiketrain.hoc
ca1_mrg_cell1.hoc
ca1_mrg_cell2.hoc
ca1_poirazi.hoc
ChannelBlocker.hoc
CrossingFinder.hoc
epspsizes.hoc
figure-example.R
figures.R
figures-common.R
FileUtils.hoc
FormatFile.hoc
ghk.inc
GraphUtils.hoc
Integrator.hoc
Makefile
mosinit.hoc
NmdaAmpaSpineSynStim.hoc
NmdaAmpaSynStim.hoc
ObjectClass.hoc
plotscalingresults_pergroup1.m
plotscalingresults5.m
PointProcessDistributor.hoc
ReferenceAxis.hoc
removezeros.m
RPlot.hoc
scaling_plots.m
Segment.hoc
SimpleSpine.hoc
Spine.hoc
TreePlot.hoc
TreePlotArray.hoc
triexpsyn.inc
units.inc
utils.hoc
validate-bpap.hoc
VarList.hoc
VCaGraph.hoc
                            
TITLE t-type calcium channel with high threshold for activation
: used in somatic and dendritic regions 
: it calculates I_Ca using channel permeability instead of conductance

UNITS {
	  (mA) = (milliamp)
	  (mV) = (millivolt)
    (molar) = (1/liter)
    (mM) = (millimolar)
    FARADAY = (faraday) (coulomb)
    R = (k-mole) (joule/degC)
}


PARAMETER {           :parameters that can be entered when function is called in cell-setup 
	  v             (mV)
    tBase = 23.5  (degC)
	  celsius = 22  (degC)
	  gcatbar = 0   (mho/cm2)  : initialized conductance
	  ki = 0.001    (mM)
	  cai = 5.e-5   (mM)       : initial internal Ca++ concentration
	  cao = 2       (mM)       : initial external Ca++ concentration
    tfa = 1                  : activation time constant scaling factor
    tfi = 0.68               : inactivation time constant scaling factor
    eca = 140                : Ca++ reversal potential
}

NEURON {
	  SUFFIX cat
	  USEION ca READ cai,cao 
    USEION Ca WRITE iCa VALENCE 2
    : The T-current does not activate calcium-dependent currents.
    : The construction with dummy ion Ca prevents the updating of the 
    : internal calcium concentration. 
    RANGE gcatbar, hinf, minf, taum, tauh, iCa, gmax
}

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

ASSIGNED {     : parameters needed to solve DE
	  iCa  (mA/cm2)
    gcat (mho/cm2) 
    gmax (mho/cm2) 
    minf
    hinf
    taum (ms)
    tauh (ms)
}

INITIAL {
    :        tadj = 3^((celsius-tBase)/10)   : assume Q10 of 3
    rates(v)
    m = minf
    h = hinf
	  gcat = gcatbar*m*m*h*h2(cai)
    gmax = gcat
}

BREAKPOINT {
	  SOLVE states METHOD cnexp
	  gcat = gcatbar*m*m*h*h2(cai) : maximum channel permeability
	  iCa = gcat*ghk(v,cai,cao)    : dummy calcium current induced by this channel
    if (gcat > gmax) {
        gmax = gcat
    }
}

FUNCTION h2(cai(mM)) {
	  h2 = ki/(ki+cai)
}

FUNCTION ghk(v(mV), ci(mM), co(mM)) (mV) { LOCAL nu,f
    f = KTF(celsius)/2
    nu = v/f
    ghk=-f*(1. - (ci/co)*exp(nu))*efun(nu)
}

FUNCTION KTF(celsius (degC)) (mV) {   : temperature-dependent adjustment factor
    KTF = ((25(mV)/293.15(degC))*(celsius + 273.15(degC)))
}

FUNCTION efun(z) {
	  if (fabs(z) < 1e-4) {
		    efun = 1 - z/2
	  }else{
		    efun = z/(exp(z) - 1)
	  }
}

FUNCTION alph(v(mV)) (/ms) {
	  alph = 1.6e-4(/ms)*exp(-(v+57(mV))/19(mV))
}

FUNCTION beth(v(mV)) (/ms) {
	  beth = 1(/ms)/(exp((-v+15(mV))/10(mV))+1.0)
}

FUNCTION alpm(v(mV)) (/ms) {
	  alpm = 0.1967(/ms)*(-1.0(/mV)*v+19.88)/(exp((-1.0*v+19.88(mV))/10.0(mV))-1.0)
}

FUNCTION betm(v(mV)) (/ms) {
	  betm = 0.046(/ms)*exp(-v/22.73(mV))
}

:if state_cagk is called from hoc, garbage or segmentation violation will
:result because range variables won't have correct pointer.  This is because
: only BREAKPOINT sets up the correct pointers to range variables.
DERIVATIVE states {     : exact when v held constant; integrates over dt step
    rates(v)
    m' = (minf - m)/taum
    h' = (hinf - h)/tauh
}

PROCEDURE rates(v (mV)) { :callable from hoc
    LOCAL a
    TABLE taum, minf, tauh, hinf FROM -150 TO 150 WITH 300
    a = alpm(v)
    taum = 1/(tfa*(a + betm(v))) : estimation of activation tau
    minf =  a/(a+betm(v))        : estimation of activation steady state
    a = alph(v)
    tauh = 1/(tfi*(a + beth(v))) : estimation of inactivation tau
    hinf = a/(a+beth(v))         : estimation of inactivation steady state
}

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