AP shape and parameter constraints in optimization of compartment models (Weaver and Wearne 2006)

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Accession:87473
"... We construct an objective function that includes both time-aligned action potential shape error and errors in firing rate and firing regularity. We then implement a variant of simulated annealing that introduces a recentering algorithm to handle infeasible points outside the boundary constraints. We show how our objective function captures essential features of neuronal firing patterns, and why our boundary management technique is superior to previous approaches."
Reference:
1 . Weaver CM, Wearne SL (2006) The role of action potential shape and parameter constraints in optimization of compartment models Neurocomputing 69:1053-1057
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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:
Cell Type(s): Vestibular neuron;
Channel(s): I Na,p; I Na,t; I A; I K,Ca;
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Parameter Fitting; Methods;
Implementer(s): Weaver, Christina [christina.weaver at fandm.edu];
Search NeuronDB for information about:  I Na,p; I Na,t; I A; I K,Ca;
proc reset_testcell() {
	biophysics()
	typeB_slow()
	ca_init = 1e-4
	cainf_cad = 1e-4
	v_init = -52
	ek = -80
}

proc 	deep_singleAHP() {

	reset_testcell()

	gnabar_fn = 0.018
	gbar_ka   = 0.0071
	gbar_cahi = 0.001
	gbar_nap  = 1e-9
	Kp_cad = 1
	Rca_cad = 5

}

proc single_spike() {
	reset_testcell()
	Kp_cad  = 0.025
	Rca_cad = 0.00625
}

proc slower_FR() {
	reset_testcell()
	Kp_cad  = 0.0325
	Rca_cad = 0.008125
}

proc higher_FR() {
	reset_testcell()
	Kp_cad  = 0.1
	Rca_cad = 0.025
}

proc shallow_AHP() {
	reset_testcell()
	gnabar_fn = 0.02
}

proc no_spikes() {
	reset_testcell()
	gbar_kca *= 2
}

proc burst_example() {
        reset_testcell()
	gnabar_fn = 0.01
	gkbar_fn = 0.004
	//kca, cahi different from default
	gbar_kca = 0.00025
	gbar_cahi = 0.001
	gbar_ka = 1e-9
	gbar_nap = 5e-5
	Kp_cad = 0.05
	Rca_cad = 0.0125

}



/*** Av-Ron's Minimal Cell Model ***/
proc setMCM() {

	gbar_nap = 0
	gbar_cahi = 0
	gbar_kca = 0
	gbar_ka = 1e-9

	v_init = -56

	gkbar_fn = 0.010
	vhm_fn = -31
	am_fn = 0.065
	vhn_fn = -46
	an_fn = 0.055
	lamb_fn = 0.08
	gnabar_fn = 0.120
	g_pas = 0.0003
	ena = 55
	ek = -72
	e_pas = -50

}

proc setburst() {

	setMCM() 

	simp_cahi = 1
	gkbar_fn = 0.005
	gbar_kca = 0.0005
	Kd_kca = 0.0005
	gbar_cahi = 0.0002
	
	ek = -72
	eca = 124
	vrest_cahi = 124

	Kp_cad = 0.0005
	Rca_cad = 0.003
	cainf_cad = 1e-5
	
	vhx_cahi = -40
	ax_cahi = 0.2
	xtau_cahi = 50

	simp_cahi=0
}

proc adapting() {
	reset_testcell()
	Kp_cad  = 0.04
	Rca_cad = 0.0005
	gbar_kca = .0003
}

proc burst_cond() {
        reset_testcell()
	gbar_nap = 0
	gbar_ka = 1e-9
	gnabar_fn = 0.1
	gkbar_fn = 0.005
	gbar_kca = 0.0005
	gbar_cahi = 0.0002
	
	Kp_cad = 0.05
	Rca_cad = 0.03
	cainf_cad = 1e-5
}