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]
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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; 
//Adapted as is from L5 PFC microcircuit used to study persistent activity (Papoutsi et al.2014,2013)
//Accession: 155057

begintemplate INcell

public soma, axon
create soma, axon

proc init () {

create soma, axon

soma {
	nseg=1
	L=53
	diam=42

	insert pas
	cm=1.2            
	g_pas =1/15000   	
	e_pas = -70
	Ra=150

	insert Naf_in
	gnafbar_Naf_in= 0.045*5 

	insert kdr_in
	gkdrbar_kdr_in=0.018

	insert IKs_in	
	gKsbar_IKs_in = 0.000725*0.1	
}

axon {
	nseg=1
	L=113.22
	diam=0.7

	insert pas
	cm=1.2            
	g_pas =1/15000   
	e_pas = -70
	Ra=150
	
	insert Naf_in
	gnafbar_Naf_in=0.045*12

	insert kdr_in
	gkdrbar_kdr_in=0.018
}

	
connect axon(0), soma(0.5)	

ko0_k_ion = 3.82   
ki0_k_ion = 140    
celsius   = 34
}

init()
endtemplate INcell

//Create interneurons
nINcells = 1
objref INcells[nINcells]

for i = 0, nINcells-1 {
INcells[i] = new INcell()
}

//Create list with sections
objref insoma_list

insoma_list = new SectionList()
for i=0, nINcells-1 {
INcells[i].soma insoma_list.append()
}
proc current_balancein() {	
	finitialize($1)
	fcurrent()
	forsec insoma_list {
      		for (x) {
			if (ismembrane("na_ion") && ismembrane("ca_ion") && (ismembrane("k_ion"))){
	    			e_pas(x)=(ina(x)+ik(x)+ica(x)+g_pas(x)*v(x))/g_pas(x) 
			} else if (ismembrane("na_ion") && (ismembrane("k_ion"))) {
	    			e_pas(x)=(ina(x)+ik(x)+g_pas(x)*v(x))/g_pas(x)
			} else {
				e_pas(x)=v(x)
			}
			fcurrent()
		}
	}
}

current_balancein(-70)