Layer 5 Pyramidal Neuron (Shai et al., 2015)

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Accession:180373
This work contains a NEURON model for a layer 5 pyramidal neuron (based on Hay et al., 2011) with distributed groups of synapses across the basal and tuft dendrites. The results of that simulation are used to fit a phenomenological model, which is also included in this file.
Reference:
1 . Shai AS, Anastassiou CA, Larkum ME, Koch C (2015) Physiology of layer 5 pyramidal neurons in mouse primary visual cortex: coincidence detection through bursting. PLoS Comput Biol 11:e1004090 [PubMed]
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:
Cell Type(s): Neocortex V1 L6 pyramidal corticothalamic cell;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s): Glutamate;
Simulation Environment: NEURON; MATLAB;
Model Concept(s): Dendritic Action Potentials; Active Dendrites;
Implementer(s):
Search NeuronDB for information about:  Neocortex V1 L6 pyramidal corticothalamic cell; Glutamate;
// Author: Etay Hay, 2011
//    Models of Neocortical Layer 5b Pyramidal Cells Capturing a Wide Range of
//    Dendritic and Perisomatic Active Properties
//    (Hay et al., PLoS Computational Biology, 2011) 
//
// Model of L5 Pyramidal Cell, constrained for BAC Firing

begintemplate L5PCbiophys
public biophys

proc biophys() {
	forsec $o1.all {
	  insert pas
		cm = 1
		Ra = 100
		e_pas = -90
	}

  forsec $o1.somatic {
	  insert Ca_LVAst 
	  insert Ca_HVA 
	  insert SKv3_1 
	  insert SK_E2 
	  insert K_Tst 
	  insert K_Pst 
	  insert Nap_Et2 
	  insert NaTa_t
		insert CaDynamics_E2
		insert Ih
		ek = -85
		ena = 50
		gIhbar_Ih = 0.0002
    g_pas = 0.0000344 
  	decay_CaDynamics_E2 = 486.0 
  	gamma_CaDynamics_E2 = 0.000549 
  	gCa_LVAstbar_Ca_LVAst = 0.00432 
  	gCa_HVAbar_Ca_HVA = 0.000567 
  	gSKv3_1bar_SKv3_1 = 0.766 
  	gSK_E2bar_SK_E2 = 0.0556 
  	gK_Tstbar_K_Tst = 0.0326 
  	gK_Pstbar_K_Pst = 0.000547 
  	gNap_Et2bar_Nap_Et2 = 0.00496 
  	gNaTa_tbar_NaTa_t = 1.71 
  }

	forsec $o1.apical {
		cm = 2
		insert Ih
  	insert SK_E2 
  	insert Ca_LVAst 
  	insert Ca_HVA 
  	insert SKv3_1 
  	insert NaTa_t 
  	insert Im 
  	insert CaDynamics_E2
		ek = -85
		ena = 50
    decay_CaDynamics_E2 = 88.9 
    gamma_CaDynamics_E2 = 0.0005 
    gSK_E2bar_SK_E2 = 0.00186 
  	gSKv3_1bar_SKv3_1 = 0.000298 
  	gNaTa_tbar_NaTa_t = 0.0211 
  	gImbar_Im = 0.00006 
  	g_pas = 0.0000447 
	}
	$o1.distribute_channels("apic","gIhbar_Ih",2,-0.8696,3.6161,0.0,2.0870,0.00020000000) 
	$o1.distribute_channels("apic","gCa_LVAstbar_Ca_LVAst",3,1.000000,0.010000,685.000000,885.000000,0.0198000000) 
	$o1.distribute_channels("apic","gCa_HVAbar_Ca_HVA",3,1.000000,0.100000,685.000000,885.000000,0.0004370000) 
	
  forsec $o1.basal {
		cm = 2
		insert Ih
		gIhbar_Ih = 0.0002
  	g_pas = 0.0000535 
	}

  forsec $o1.axonal {
  	g_pas = 0.000045 
	}
}

endtemplate L5PCbiophys

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