Amyloid-beta effects on release probability and integration at CA3-CA1 synapses (Romani et al. 2013)

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Accession:147757
The role of amyloid beta (Aß) in brain function and in the pathogenesis of Alzheimer’s disease remains elusive. Recent publications reported that an increase in Aß concentration perturbs presynaptic release in hippocampal neurons, in particular by increasing release probability of CA3-CA1 synapses. The model predics how this alteration can affect synaptic plasticity and signal integration. The results suggest that the perturbation of release probability induced by increased Aß can significantly alter the spike probability of CA1 pyramidal neurons and thus contribute to abnormal hippocampal function during Alzheimer’s disease.
Reference:
1 . Romani A, Marchetti C, Bianchi D, Leinekugel X, Poirazi P, Migliore M, Marie H (2013) Computational modeling of the effects of amyloid-beta on release probability at hippocampal synapses. Front Comput Neurosci 7:1 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell; Synapse;
Brain Region(s)/Organism: Hippocampus;
Cell Type(s): Hippocampus CA1 pyramidal GLU cell;
Channel(s): I Na,t; I A; I K; I M; I h; I Calcium; I_AHP;
Gap Junctions:
Receptor(s): AMPA;
Gene(s):
Transmitter(s): Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Synaptic Plasticity; Short-term Synaptic Plasticity; Facilitation; Depression; Synaptic Integration; Aging/Alzheimer`s;
Implementer(s): Bianchi, Daniela [danielabianchi12 -at- gmail.com]; Romani, Armando [romani.armando -at- gmail.com];
Search NeuronDB for information about:  Hippocampus CA1 pyramidal GLU cell; AMPA; I Na,t; I A; I K; I M; I h; I Calcium; I_AHP; Glutamate;
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RomaniEtAl2013
experiment
cad.mod *
cagk.mod *
cal.mod *
calH.mod *
car.mod *
cat.mod *
d3.mod *
h.mod *
kadist.mod *
kaprox.mod *
kca.mod *
kdr.mod *
km.mod *
na3.mod *
na3dend.mod *
na3notrunk.mod *
nap.mod *
nax.mod *
netstimmm.mod *
somacar.mod *
tmgsyn.mod
vecevent.mod
cell-setup.hoc
createNewSyn4.hoc
loadBasicModel.hoc
mosinit.hoc
session.ses
simulation.hoc
                            
TITLE K-A channel from Klee Ficker and Heinemann
: modified by Brannon and Yiota Poirazi (poirazi@LNC.usc.edu)
: to account for Hoffman et al 1997 proximal region kinetics
: used only in soma and sections located < 100 microns from the soma


NEURON {
	SUFFIX kap
	USEION k READ ek WRITE ik
        RANGE gkabar,gka, ik
        GLOBAL ninf,linf,taul,taun,lmin
}

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

}


PARAMETER {                       :parameters that can be entered when function is called in cell-setup

       	gkabar = 0      (mho/cm2) :initialized conductance
        vhalfn = 11     (mV)      :activation half-potential
        vhalfl = -56    (mV) 	  :inactivation half-potential
        a0n = 0.05      (/ms)     :parameters used
        zetan = -1.5    (1)       :in calculation of
        zetal = 3       (1)       :steady state values
        gmn = 0.55      (1)       :and time constants
        gml = 1         (1)
	lmin = 2        (ms)
	nmin = 0.1      (ms)
	pw = -1         (1)
	tq = -40	(mV)
	qq = 5		(mV)
	q10 = 5                   :temperature sensitivity
}



 
ASSIGNED {       :parameters needed to solve DE
	v               (mV)
        ek              (mV)      :K reversal potential  (reset in cell-setup.hoc)
	celsius         (degC)
	ik              (mA/cm2)
        ninf
        linf      
        taul            (ms)
        taun            (ms)
       gka

}


STATE {          :the unknown parameters to be solved in the DEs 
	n l
}

LOCAL qt

INITIAL {		:initialize the following parameter using rates()
      rates(v)
	n = ninf
	l = linf
      gka = gkabar*n*l
	ik = gka*(v-ek)

}

BREAKPOINT {
	SOLVE states METHOD cnexp
:	ik = gkabar*n*l*(v+70)
      gka = gkabar*n*l
	ik = gka*(v-ek)
}

DERIVATIVE states {
	rates(v)
        n' = (ninf - n)/taun
        l' = (linf - l)/taul
}



PROCEDURE rates(v (mV)) {                  :callable from hoc
       
	LOCAL a,qt
        qt = q10^((celsius-24)/10)       : temprature adjastment factor
        a = alpn(v)
        ninf = 1/(1 + a)                   : activation variable steady state value
        taun = betn(v)/(qt*a0n*(1+a))      : activation variable time constant
	if (taun<nmin) {taun=nmin}         : time constant not allowed to be less than nmin
        
	a = alpl(v)
        linf = 1/(1+ a)                    : inactivation variable steady state value
	taul = 0.26(ms/mV)*(v+50)               : inactivation variable time constant
	if (taul<lmin) {taul=lmin}         : time constant not allowed to be less than lmin

}

FUNCTION alpn(v(mV)) { LOCAL zeta 
  zeta = zetan+pw/(1+exp((v-tq)/qq))
UNITSOFF
  alpn = exp(1.e-3*zeta*(v-vhalfn)*9.648e4/(8.315*(273.16+celsius))) 
UNITSON
}

FUNCTION betn(v(mV)) { LOCAL zeta
  zeta = zetan+pw/(1+exp((v-tq)/qq))
UNITSOFF
  betn = exp(1.e-3*zeta*gmn*(v-vhalfn)*9.648e4/(8.315*(273.16+celsius))) 
UNITSON
}

FUNCTION alpl(v(mV)) {
UNITSOFF
  alpl = exp(1.e-3*zetal*(v-vhalfl)*9.648e4/(8.315*(273.16+celsius))) 
UNITSON
}

FUNCTION betl(v(mV)) {
UNITSOFF
  betl = exp(1.e-3*zetal*gml*(v-vhalfl)*9.648e4/(8.315*(273.16+celsius))) 
UNITSON
}


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