Storing serial order in intrinsic excitability: a working memory model (Conde-Sousa & Aguiar 2013)

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Accession:147461
" … Here we present a model for working memory which relies on the modulation of the intrinsic excitability properties of neurons, instead of synaptic plasticity, to retain novel information for periods of seconds to minutes. We show that it is possible to effectively use this mechanism to store the serial order in a sequence of patterns of activity. … The presented model exhibits properties which are in close agreement with experimental results in working memory. ... "
Reference:
1 . Conde-Sousa E, Aguiar P (2013) A working memory model for serial order that stores information in the intrinsic excitability properties of neurons J Comp Neurosci [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network;
Brain Region(s)/Organism:
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
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Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Working memory;
Implementer(s):
TITLE  NMDA receptor with Ca influx + AMPA receptor

COMMENT
Written by Eduardo Conde-Sousa, FCUP
econdesousa@gmail.com
and 
Paulo Aguiar, FCUP
pauloaguiar@fc.up.pt
in Dec 2011
ENDCOMMENT

NEURON {
		POINT_PROCESS ComboSyn	
		USEION ca WRITE ica	
		USEION mg READ mgo VALENCE 2
		RANGE tau1, tau2, e_AMPA, i_AMPA
		RANGE g_AMPA
		RANGE tau_rise, tau_decay
		RANGE i_NMDA, g_NMDA, e_NMDA, mg, i2, ica, ca_ratio
		RANGE rr
		NONSPECIFIC_CURRENT i
}
   
UNITS {
		(nA) = (nanoamp)
		(mV) = (millivolt)
		(molar) = (1/liter)
		(mM) = (millimolar)
}    
    
PARAMETER {
    tau1      = 0.1   (ms) <1e-9,1e9>
    tau2      = 5     (ms) <1e-9,1e9>
    e_AMPA    = 0	    (mV)
  	tau_rise  = 5.0   (ms)  <1e-9,1e9>  
    tau_decay = 70.0  (ms)  <1e-9,1e9>  
    e_NMDA    = 0.0   (mV)  : synapse reversal potential
    mgo		    = 1.0   (mM)  : external magnesium concentration
    ca_ratio  = 0.1   (1)   : ratio of Ca current to total current, Burnashev/Sakmann J.Phys.1995 485 403-418)
    rr        = 0.839486356
}
    
    
ASSIGNED {
		v		(mV)
		i		(nA)
		i2		(nA)
		g_AMPA  (umho)
		g_NMDA  (umho)
		factor	(1)
		ica		(nA)
		i_NMDA	(nA)
		i_AMPA	(nA)
  	factor_AMPA
  	factor_NMDA
}

STATE {
		A_AMPA (uS)
		B_AMPA (uS)
		A_NMDA (uS)
		B_NMDA (uS)
}


INITIAL{
		LOCAL tp_NMDA, tp_AMPA
		if (tau_rise/tau_decay > .9999) {
				tau_rise = .9999*tau_decay
		}
		A_NMDA = 0
		B_NMDA = 0
		tp_NMDA = (tau_rise*tau_decay)/(tau_decay-tau_rise)*log(tau_decay/tau_rise)
		factor_NMDA = -exp(-tp_NMDA/tau_rise)+exp(-tp_NMDA/tau_decay)
		factor_NMDA = 1/factor_NMDA
		
		if (tau1/tau2 > .9999) {
				tau1 = .9999*tau2
		}
		A_AMPA = 0
		B_AMPA = 0
		tp_AMPA = (tau1*tau2)/(tau2 - tau1) * log(tau2/tau1)
		factor_AMPA = -exp(-tp_AMPA/tau1) + exp(-tp_AMPA/tau2)
		factor_AMPA = 1/factor_AMPA
}


BREAKPOINT {
		SOLVE state METHOD cnexp
		g_NMDA = B_NMDA-A_NMDA
		i2 = g_NMDA*mgblock(v)*(v-e_NMDA)
		ica = ca_ratio*i2
		i_NMDA = (1-ca_ratio)*i2
		g_AMPA = B_AMPA - A_AMPA
		i_AMPA = g_AMPA*(v - e_AMPA)
  	i=i_NMDA+i_AMPA
}


DERIVATIVE state{
		A_NMDA' = -A_NMDA/tau_rise
		B_NMDA' = -B_NMDA/tau_decay
		A_AMPA' = -A_AMPA/tau1
		B_AMPA' = -B_AMPA/tau2
		
}

FUNCTION mgblock(v(mV)) {
		: from Jahr & Stevens 1990
		mgblock = 1 / (1 + exp(0.062 (/mV) * -v) * (mgo / 3.57 (mM)))
}

NET_RECEIVE (weight (uS)){
		A_NMDA = A_NMDA + weight*rr*factor_NMDA
		B_NMDA = B_NMDA + weight*rr*factor_NMDA
		A_AMPA = A_AMPA + weight*(1-rr)*factor_AMPA
		B_AMPA = B_AMPA + weight*(1-rr)*factor_AMPA
}

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