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;
// assume AII has Quadroni's Type B morphology
// assign soma & dendrites anatomical properties 
xopen("morph.hoc")

CM = 1  	// uF/cm2
RA        = 150

proc define_AII() {

	ctyp = 1	//Type B cell flag, for parameter assignments

	// assign soma's biophysical properties, copy to dendrites 
   	biophysics()

	typeB_slow()

	init()
}

proc 	biophysics() {

	geom_nseg()

	v0 = -52
	v_init = v0
	ca_init = 1e-5

	forall {

		// set passive params
		Ra = RA
		cm = CM	
	
		// insert channels
		insert pas
		insert fn
		insert ka
		insert kca
		insert cahi
		insert nap
	
		// insert calcium handling
			insert cad
			Kp_cad = 0.05
			Rca_cad = 0.0186

		// params for channel kinetics, see Av-Ron & Vidal 1999
		vhm_fn = -33
		am_fn = 0.055
		an_fn = 0.055
		vhn_fn = -35
		lamb_fn = 0.2

		vhb_ka = -70
		ab_ka = -0.1
		btau_ka = 10

		vhx_cahi = -30
		ax_cahi = 0.08
		Kc_cahi = 1
		xtau_cahi = 10

		vha_ka = -40
		aa_ka = 0.05

		Kd_kca = 0.0005

		vhp_nap = -56
		ap_nap = 0.075
		ptau_nap = 5


		// set maximal conductances for AII 
		gkbar_fn = 0.0026
		g_pas = 0.0003
		gbar_kca = 0.001316
		gnabar_fn = 0.010
		gbar_cahi = 0.00025
		gbar_ka = 0
		gbar_nap = 5e-7
	}
	

	// reversal potentials
	forall {
	    e_pas = -50
	    ena = 55
	    ek  = -80
	}

}

// apply the d_lambda rule for setting number of segments
proc geom_nseg() {
	soma area(0.5)	// make sure diam reflects 3d points
	forall { nseg = int((L/(0.1*lambda_f(100))+0.9)/2)*2 + 1 }
}

proc typeB_slow() {

	forall {
		Kp_cad = 0.05
		Rca_cad = 0.0125
		gkbar_fn = 0.004
		g_pas = 0.0003
		gbar_kca = 0.001
		gnabar_fn = 0.010
		gbar_cahi = 0.00025
		gbar_ka = 1e-9
		gbar_nap = 0.00005
	}
	
}

define_AII()