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

 Download zip file   Auto-launch 
Help downloading and running models
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;
/
KonstantoudakiEtAl2014
experiment
data
ampa.mod *
ampain.mod *
cadyn.mod *
cadynin.mod *
cal.mod *
calc.mod *
calcb.mod *
can.mod *
cancr.mod *
canin.mod *
car.mod *
cat.mod *
catcb.mod *
gabaa.mod *
gabaain.mod *
gabab.mod *
h.mod *
hcb.mod *
hin.mod *
ican.mod *
iccb.mod *
iccr.mod *
icin.mod *
iks.mod *
ikscb.mod *
ikscr.mod *
iksin.mod *
kadist.mod *
kadistcr.mod *
kadistin.mod *
kaprox.mod *
kaproxcb.mod *
kaproxin.mod *
kca.mod *
kcain.mod *
kct.mod *
kctin.mod *
kdr.mod *
kdrcb.mod *
kdrcr.mod *
kdrin.mod *
naf.mod *
nafcb.mod *
nafcr.mod *
nafin.mod *
nafx.mod *
nap.mod *
netstim.mod *
NMDA.mod *
NMDAIN.mod *
sinclamp.mod *
cb.hoc
cr.hoc
ExperimentControl.hoc *
final.hoc
incell.hoc
net.hoc
pfc_pc_temp.hoc
run
run_orig
                            
: Persistent Na+ channel

NEURON {
	SUFFIX Nap
	USEION na READ ena WRITE ina
	RANGE gnapbar, ina, gna
	RANGE DA_alphamshift,DA_betamshift
	RANGE DA_alphahfactor, DA_betahfactor
}

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

INDEPENDENT {t FROM 0 TO 1 WITH 1 (ms)}

PARAMETER {
	v (mV)
	dt (ms)
	gnapbar= 0.0022 (mho/cm2) <0,1e9>
	ena = 55 (mV)
	DA_alphamshift=0 : 2 for 100% DA, 0 otherwise
	DA_betamshift=0  : 5 for 100% DA,0 otherwise
	DA_alphahfactor=0: -.8e-5 for DA, 0 otherwise
	DA_betahfactor=0 : 0.014286-0.02 for DA, 0 otherwise
}

STATE {
	m h
}

ASSIGNED {
	ina (mA/cm2)
	minf hinf 
	mtau (ms)
	htau (ms)
	gna (mho/cm2)
	
}

INITIAL {
	rate(v)
	m = minf
	h = hinf
}

BREAKPOINT {
	SOLVE states METHOD cnexp
	gna = gnapbar*m*h
	ina = gna*(v-55)
	
}

DERIVATIVE states {
	rate(v)
	m' = (minf-m)/mtau
	h' = (hinf-h)/htau
}

UNITSOFF

FUNCTION malf( v){ LOCAL va 
	va=v+12+DA_alphamshift
	if (fabs(va)<1e-04){
	 va = va + 0.00001 }
	malf = (-0.2816*va)/(-1+exp(-va/9.3))
	
}


FUNCTION mbet(v(mV))(/ms) { LOCAL vb 
	vb=v-15+DA_betamshift
	if (fabs(vb)<1e-04){
	    vb = vb + 0.00001 }

	mbet = (0.2464*vb)/(-1+exp(vb/6))

}	


FUNCTION half(v(mV))(/ms) { LOCAL vc 
	vc=v+42.8477
	if (fabs(vc)<1e-04){
	   vc=vc+0.00001 }
        half= (2.8e-5+DA_alphahfactor)*(exp(-vc/4.0248))

}


FUNCTION hbet(v(mV))(/ms) { LOCAL vd
	vd=v-413.9284
	if (fabs(vd)<1e-04){
	vd=vd+0.00001 }
        hbet= (0.02+DA_betahfactor)/(1+exp(-vd/148.2589))
 
}




PROCEDURE rate(v (mV)) {LOCAL msum, hsum, ma, mb, ha, hb
	ma=malf(v) mb=mbet(v) ha=half(v) hb=hbet(v)
	
	msum = ma+mb
	minf = ma/msum
	mtau = 1/msum
	
	
	hsum = ha+hb
	hinf = ha/hsum
	htau = 1/hsum
}

	
UNITSON