SCZ-associated variant effects on L5 pyr cell NN activity and delta osc. (Maki-Marttunen et al 2018)

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Accession:237469
" … Here, using computational modeling, we show that a common biomarker of schizophrenia, namely, an increase in delta-oscillation power, may be a direct consequence of altered expression or kinetics of voltage-gated ion channels or calcium transporters. Our model of a circuit of layer V pyramidal cells highlights multiple types of schizophrenia-related variants that contribute to altered dynamics in the delta frequency band. Moreover, our model predicts that the same membrane mechanisms that increase the layer V pyramidal cell network gain and response to delta-frequency oscillations may also cause a decit in a single-cell correlate of the prepulse inhibition, which is a behavioral biomarker highly associated with schizophrenia."
Reference:
1 . Mäki-Marttunen T, Krull F, Bettella F, Hagen E, Næss S, Ness TV, Moberget T, Elvsåshagen T, Metzner C, Devor A, Edwards AG, Fyhn M, Djurovic S, Dale AM, Andreassen OA, Einevoll GT (2019) Alterations in Schizophrenia-Associated Genes Can Lead to Increased Power in Delta Oscillations. Cereb Cortex 29:875-891 [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: Neocortex;
Cell Type(s):
Channel(s): Ca pump; I A, slow; I h; I K; I K,Ca; I K,leak; I L high threshold; I M; I Na,p; I Na,t; I T low threshold;
Gap Junctions: Gap junctions;
Receptor(s): AMPA; NMDA; Gaba;
Gene(s): Cav1.2 CACNA1C; Cav1.3 CACNA1D; Cav3.3 CACNA1I; HCN1; Kv2.1 KCNB1; Nav1.1 SCN1A; PMCA ATP2B2;
Transmitter(s): Glutamate; Gaba;
Simulation Environment: NEURON; Python; LFPy;
Model Concept(s): Schizophrenia; Oscillations;
Implementer(s): Maki-Marttunen, Tuomo [tuomo.maki-marttunen at tut.fi];
Search NeuronDB for information about:  AMPA; NMDA; Gaba; I Na,p; I Na,t; I L high threshold; I T low threshold; I K; I K,leak; I M; I h; I K,Ca; I A, slow; Ca pump; Gaba; 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 both for BAC firing and Current Step 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 = 0.0000338 
  	decay_CaDynamics_E2 = 460.0 
  	gamma_CaDynamics_E2 = 0.000501 
  	gCa_LVAstbar_Ca_LVAst = 0.00343 
  	gCa_HVAbar_Ca_HVA = 0.000992 
  	gSKv3_1bar_SKv3_1 = 0.693 
  	gSK_E2bar_SK_E2 = 0.0441 
  	gK_Tstbar_K_Tst = 0.0812 
  	gK_Pstbar_K_Pst = 0.00223 
  	gNap_Et2bar_Nap_Et2 = 0.00172 
  	gNaTa_tbar_NaTa_t = 2.04 
  }

	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 = 122 
    gamma_CaDynamics_E2 = 0.000509 
    gSK_E2bar_SK_E2 = 0.0012 
  	gSKv3_1bar_SKv3_1 = 0.000261 
  	gNaTa_tbar_NaTa_t = 0.0213 
  	gImbar_Im = 0.0000675 
  	g_pas = 0.0000589 
	}
	$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",3,1.000000,0.010000,685.000000,885.000000,0.0187000000) 
	$o1.distribute_channels("apic","gCa_HVAbar_Ca_HVA",3,1.000000,0.100000,685.000000,885.000000,0.0005550000) 
	
  forsec $o1.basal {
		cm = 2
		insert Ih
		gIhbar_Ih = 0.0002
  	g_pas = 0.0000467 
	}

  forsec $o1.axonal {
  	g_pas = 0.0000325 
	}
}

endtemplate L5PCbiophys

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