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
                            
: Fast Na+ channel
: added the 's' attenuation system from hha2.mod
: Kiki Sidiropoulou
: September 27, 2007

NEURON {
	SUFFIX Naf
	USEION na READ ena WRITE ina
	RANGE gnafbar, ina, gna, ar2
}

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

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

PARAMETER {
	v (mV)
	dt (ms)
	gnafbar	= 0 (mho/cm2)
	:gnafbar= 0.086 (mho/cm2) <0,1e9>
	ena = 55 (mV)
	
	:PARAMETERS FOR S ATTENUATION SYSTEM
	taumin = 3 (ms)  :min activation time for "s" attenuation system
        vhalfr = -60 (mV)       :half potential for "s" attenuation system
        vvh=-58		(mV) 
 	vvs = 2 (mV)
	a0r = 0.0003 (/ms)
        b0r = 0.0003 (/ms)
       : a0r = 0.0003 (ms)
        :b0r = 0.0003 (ms)
        zetar = 12    
	zetas = 12   
        gmr = 0.2   
	ar2 = 1.0               :initialized parameter for location-dependent
                                :Na-conductance attenuation, "s", (ar=1 -> zero attenuation)
}
STATE {
	m h s
}
ASSIGNED {
	celsius (degC)
	ina (mA/cm2)
	minf 
	hinf
	sinf 
	mtau (ms)
	htau (ms)
	stau (ms)
	gna (mho/cm2)
	
}



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

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

DERIVATIVE states {
	rate(v, ar2)
	m' = (minf-m)/mtau
	h' = (hinf-h)/htau
	s' = (sinf-s)/stau
}

UNITSOFF

FUNCTION malf( v){ LOCAL va 
	va=v+28
	:va=v+28
	if (fabs(va)<1e-04){
	   malf= -0.2816*(-9.3 + va*0.5)
	   :malf= -0.2816*(-9.3 + va*0.5)
	}else{
	   malf = -0.2816*(v+28)/(-1+exp(-va/9.3))
	}
}


FUNCTION mbet(v(mV))(/ms) { LOCAL vb 
	vb=v+1
	:vb=v+1
	if (fabs(vb)<1e-04){
	    mbet = 0.2464*(6+vb*0.5)
	    :mbet = 0.2464*(6 + vb*0.5)
	}else{
	   mbet = 0.2464*(v+1)/(-1+exp(vb/6))	  :/(-1+exp((v+1)/6))
	}
	}	


FUNCTION half(v(mV))(/ms) { LOCAL vc 
	:vc=v+15.1
	vc=v+40.1	:changed to 40.1 by kiki
	if (fabs(vc)<1e-04){
	   half=0.098*(20 + vc*0.5)
	}else{
	   half=0.098/exp(vc+43.1/20)  :43.1, also spike train attenuation
}
}


FUNCTION hbet(v(mV))(/ms) { LOCAL vd
	:vd=v+13.1
	vd=v+13.1  :decreasing it increases the peak current
	if (fabs(vd)<1e-04){
	   hbet=1.4*(10 + vd*0.5)
	}else{
	   hbet=1.4/(1+exp(-(vd-1.1)/10))  :13.1 increasing it, increases the spike train attenuation and increases spike width
	:changed to 1.1 for faster inactivation
} 
}


:FUNCTIONS FOR S 
FUNCTION alpv(v(mV)) {
         alpv = 1/(1+exp((v-vvh)/vvs))
}


FUNCTION alpr(v(mV)) {       :used in "s" activation system tau

  alpr = exp(1.e-3*zetar*(v-vhalfr)*9.648e4/(8.315*(273.16+celsius))) 
}

FUNCTION betr(v(mV)) {       :used in "s" activation system tau

  betr = exp(1.e-3*zetar*gmr*(v-vhalfr)*9.648e4/(8.315*(273.16+celsius))) 
}



PROCEDURE rate(v (mV),a2) {LOCAL q10, msum, hsum, ma, mb, ha, hb,c
	

	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)

	stau = betr(v)/(a0r*(1+alpr(v))) 
	if (stau<taumin) {stau=taumin} :s activation tau
	c = alpv(v)
	sinf = c+a2*(1-c) 	
}

	
UNITSON