L5 PFC pyramidal neurons (Papoutsi et al. 2017)

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Accession:230811
" ... Here, we use a modeling approach to investigate whether and how the morphology of the basal tree mediates the functional output of neurons. We implemented 57 basal tree morphologies of layer 5 prefrontal pyramidal neurons of the rat and identified morphological types which were characterized by different response features, forming distinct functional types. These types were robust to a wide range of manipulations (distribution of active ionic mechanisms, NMDA conductance, somatic and apical tree morphology or the number of activated synapses) and supported different temporal coding schemes at both the single neuron and the microcircuit level. We predict that the basal tree morphological diversity among neurons of the same class mediates their segregation into distinct functional pathways. ..."
Reference:
1 . Papoutsi A, Kastellakis G, Poirazi P (2017) Basal tree complexity shapes functional pathways in the prefrontal cortex. J Neurophysiol 118:1970-1983 [PubMed]
Citations  Citation Browser
Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism: Prefrontal cortex (PFC);
Cell Type(s): Neocortex L5/6 pyramidal GLU cell;
Channel(s): I A; I h; I L high threshold; I T low threshold; I N; I R; I K,Ca; I_AHP; I_Ks; I Na,p; I Na,t; I K;
Gap Junctions:
Receptor(s): AMPA; NMDA; GabaA; GabaB;
Gene(s):
Transmitter(s): Glutamate; Gaba;
Simulation Environment: NEURON;
Model Concept(s): Active Dendrites; Detailed Neuronal Models;
Implementer(s): Papoutsi, Athanasia [athpapoutsi at gmail.com];
Search NeuronDB for information about:  Neocortex L5/6 pyramidal GLU cell; GabaA; GabaB; AMPA; NMDA; I Na,p; I Na,t; I L high threshold; I N; I T low threshold; I A; I K; I h; I K,Ca; I_Ks; I R; I_AHP; Gaba; Glutamate;
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PapoutsiEtAl2017
mod_files
ampa.mod
ampain.mod
cad.mod
cal.mod
can.mod *
car.mod *
cat.mod *
gabaa.mod *
gabaain.mod
gabab.mod *
h.mod
iks_in.mod
kadist.mod *
kca.mod *
kct.mod *
kd.mod
kdr_in.mod
kdrD.mod *
naf.mod
naf_in.mod
nap.mod *
NMDA.mod
NMDA_syn.mod
vecstim.mod
                            
: Persistent Na+ channel

NEURON {
	SUFFIX nap
	:SUFFIX Nap
	USEION na READ ena WRITE ina
	RANGE gnabar, ina, gna
	: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)
	gnabar= 0.0022 (mho/cm2) <0,1e9>
	: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 = gnabar*m*h
	: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