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]
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 *
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
                            
:  iC   fast Ca2+/V-dependent K+ channel

NEURON {
	SUFFIX iCcr
	USEION k READ ki, ko WRITE ik
	USEION ca READ cai
        RANGE ik, gk, gkcbar
}

UNITS {
        (mM) = (milli/liter)
	(mA) = (milliamp)
	(mV) = (millivolt)
	
}

INDEPENDENT {t FROM 0 TO 1 WITH 1 (ms)}
PARAMETER {
	v		(mV)
        dt              (ms)
	cai		(mM)
	gkcbar= 0.0022	(mho/cm2)
  
}


STATE {
	c
}

ASSIGNED {
	ik (mA/cm2)
	cinf 
	ctau (ms)
	gk (mho/cm2)
	ek (mV)
	ki (mM)
	ko (mM)

}


INITIAL {
	rate()
	c = cinf
}


BREAKPOINT {
	SOLVE states METHOD cnexp
	gk = gkcbar*c*c
	ek = 25 * log(ko/ki)        
	ik = gk*(v-ek)
}



DERIVATIVE states {
        rate()
	c' = (cinf-c)/ctau
}

UNITSOFF


FUNCTION calf(v (mV), cai (mM)) (/ms) { LOCAL vs, va

           vs=v+40*log10(1000*cai)  :1000*cai
	   va=vs+18
	   if (fabs(va)<1e-04){  va=va+0.0001 }
	   calf = (-0.00642*vs-0.1152)/(-1+exp(-va/12))
}



FUNCTION cbet(v (mV), cai (mM))(/ms) { LOCAL vs, vb 

	  vs=v+40*log10(cai*1000)
	  vb=vs+152
	  if (fabs(vb)<1e-04){ vb=vb+0.0001 }
	  cbet = 1.7*exp(-vb/30)

}	



UNITSON

PROCEDURE rate() {LOCAL  csum, ca, cb

	ca=calf(v, cai) cb=cbet(v, cai)
		
	csum = ca+cb
	cinf = ca/csum
	if ((1/csum)>1.1) { ctau = 1 / csum}
	else { ctau = 1.1 }
		
}
	






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