Pyramidal neuron, fast, regular, and irregular spiking interneurons (Konstantoudaki et al 2014)

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Accession:168310
This is a model network of prefrontal cortical microcircuit based primarily on rodent data. It includes 16 pyramidal model neurons, 2 fast spiking interneuron models, 1 regular spiking interneuron model and 1 irregular spiking interneuron model. The goal of the paper was to use this model network to determine the role of specific interneuron subtypes in persistent activity
Reference:
1 . Konstantoudaki X, Papoutsi A, Chalkiadaki K, Poirazi P, Sidiropoulou K (2014) Modulatory effects of inhibition on persistent activity in a cortical microcircuit model. Front Neural Circuits 8:7 [PubMed]
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type: Realistic Network; Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s): Neocortex fast spiking (FS) interneuron; Neocortex spiking regular (RS) neuron; Neocortex spiking low threshold (LTS) neuron; Neocortex spiking irregular interneuron;
Channel(s): I Na,p; I Na,t; I L high threshold; I T low threshold; I A; I K; I h; I_Ks; I_KD;
Gap Junctions:
Receptor(s): GabaA; GabaB; AMPA; NMDA;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Synchronization; Active Dendrites;
Implementer(s): Sidiropoulou, Kyriaki [sidirop at imbb.forth.gr]; Konstantoudaki, Xanthippi [xeniakons at gmail.com];
Search NeuronDB for information about:  GabaA; GabaB; AMPA; NMDA; I Na,p; I Na,t; I L high threshold; I T low threshold; I A; I K; I h; I_Ks; I_KD; Gaba; Glutamate;
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KonstantoudakiEtAl2014
experiment
data
ampa.mod *
ampain.mod *
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hin.mod *
ican.mod *
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iccr.mod *
icin.mod *
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NMDA.mod *
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sinclamp.mod *
cb.hoc
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final.hoc
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pfc_pc_temp.hoc
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run_orig
                            
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 distal region kinetics
: used only in locations > 100 microns from the soma
:
: modified to work with CVode by Carl Gold, 8/10/03
:  Updated by Maria Markaki  12/02/03

NEURON {
	SUFFIX kad
	USEION k READ ki, ko WRITE ik 		:Changed from READ ek, 23/04/2010,Nassi
        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 = -1     (mV)       :activation half-potential (-1), change for pfc, activation at -40
        vhalfl = -56    (mV)       :inactivation half-potential
       a0n = 0.1       (/ms)      :parameters used
       : a0l = 0.05       (/ms)      :parameters used
        zetan = -1.8    (1)        :in calculation of
        zetal = 3       (1) 
	:zetal = 3       (1)        :steady state values
        gmn   = 0.39    (1)        :and time constants
	:gmn   = 0.39    (1)        :and time constants, original
        gml   = 1       (1)
	lmin  = 2       (ms)
	nmin  = 0.1     (ms)
:	nmin  = 0.2     (ms)	:suggested
	pw    = -1      (1)
	tq    = -40     (mV)
	qq    = 5       (mV)
	q10   = 5                :temperature sensitivity
}


ASSIGNED {    :parameters needed to solve DE
	v               (mV)
        ek              (mV)
	celsius  	(degC)
	ik              (mA/cm2)
        ninf
        linf      
        taul            (ms)
        taun            (ms)
        gka             (mho/cm2)
	ki		(mM)
	ko		(mM)
}


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

: Solve qt once in initial block
LOCAL qt

INITIAL {    :initialize the following parameter using rates()
        qt = q10^((celsius-24)/10(degC))       : temperature adjustment factor
	rates(v)
	n=ninf
	l=linf
}

BREAKPOINT {
	SOLVE states METHOD cnexp
	ek=25 * log(ko/ki)		:Changed, added, 23/04/2010, Nassi
	ik = gkabar*n*l*(v-ek)
}


DERIVATIVE states {     : exact when v held constant; integrates over dt step
        rates(v)          : do this here
        n' = (ninf - n)/taun
        l' = (linf - l)/taul
}



PROCEDURE rates(v (mV)) {		 :callable from hoc
	LOCAL a

        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 = 6 (ms)
	taul = 0.26(ms/mV)*(v+50)               : inactivation variable time constant (0.26)
	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
}