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
                            
COMMENT
km.mod
Potassium channel, Hodgkin-Huxley style kinetics
Based on I-M (muscarinic K channel)
Slow, noninactivating
Author: Zach Mainen, Salk Institute, 1995, zach@salk.edu

ENDCOMMENT

NEURON {
	  SUFFIX km
	  USEION k READ ek WRITE ik
	  RANGE n, gk, gbar, gmax
	  RANGE ninf, ntau
	  GLOBAL Ra, Rb
	  GLOBAL q10, temp, tadj, vmin, vmax
}

UNITS {
	  (mA) = (milliamp)
	  (mV) = (millivolt)
	  (pS) = (picosiemens)
	  (um) = (micron)
} 

PARAMETER {
	  v 		        (mV)
	  gbar = 10   	(pS/um2)              : 0.03 mho/cm2
	  tha  = -30	  (mV)                  : v 1/2 for inf
	  qa   = 9	    (mV)                  : inf slope		
	  Ra   = 0.001	(/ms/mV)              : max act rate  (slow)
	  Rb   = 0.001	(/ms/mV)              : max deact rate  (slow)
	  celsius		    (degC)
	  temp = 23	    (degC)                : original temp 	
	  q10  = 2.3                          : temperature sensitivity
	  vmin = -120	  (mV)
	  vmax = 100	  (mV)
} 


ASSIGNED {
	  a		 (/ms)
	  b		 (/ms)
	  ik 	 (mA/cm2)
	  gk	 (pS/um2)
	  ek   (mV)
	  ninf
	  ntau (ms)	
	  tadj
    gmax (mho/cm2)
}


STATE { n }

INITIAL { 
	  trates(v)
	  n = ninf
    gk = tadj*gbar*n
    gmax = (1e-4) * gk
}

BREAKPOINT {
    SOLVE states METHOD cnexp
	  gk = tadj*gbar*n
	  ik = (1e-4) * gk * (v - ek)
    if (((1e-4) * gk) > gmax) {
        gmax = (1e-4) * gk
    }
} 

LOCAL nexp

DERIVATIVE states {   
    trates(v)     
    n' =  (ninf-n)/ntau*tadj
}

PROCEDURE trates(v (mV)) {  :Computes rate and other constants at current v.
    :Call once from HOC to initialize inf at resting v.
    TABLE ninf, ntau
	  DEPEND celsius, temp, Ra, Rb, tha, qa
	  FROM vmin TO vmax WITH 199
    
	  rates(v): not consistently executed from here if usetable_hh == 1
    tadj = q10^((celsius - temp)/10(degC))  :temperature adjastment
}


PROCEDURE rates(v (mV)) {  :Computes rate and other constants at current v.
    :Call once from HOC to initialize inf at resting v.
    
    a =  Ra * (v - tha) / (1 - exp(-(v - tha)/qa))
    b = -Rb * (v - tha) / (1 - exp((v - tha)/qa))
    ntau = 1/(a+b)
	  ninf = a*ntau
}


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