A model of slow motor unit (Kim, 2017)

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Accession:235769
Cav1.3 channels in motoneuron dendrites are actively involved during normal motor activities. To investigate the effects of the activation of motoneuron Cav1.3 channels on force production, a model motor unit was built based on best-available data. The simulation results suggest that force potentiation induced by Cav1.3 channel activation is strongly modulated not only by firing history of the motoneuron but also by length variation of the muscle as well as neuromodulation inputs from the brainstem.
Reference:
1 . Kim H (2017) Muscle length-dependent contribution of motoneuron Cav1.3 channels to force production in model slow motor unit. J Appl Physiol (1985) 123:88-105 [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): Spinal cord lumbar motor neuron alpha ACh cell; Skeletal muscle cell;
Channel(s): I Calcium; I Potassium; I Sodium; I_AHP;
Gap Junctions:
Receptor(s):
Gene(s): Cav1.3 CACNA1D;
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Active Dendrites;
Implementer(s): Kim, Hojeong [hojeong.kim03 at gmail.com];
Search NeuronDB for information about:  Spinal cord lumbar motor neuron alpha ACh cell; I Sodium; I Calcium; I Potassium; I_AHP;
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Kim2017
fig4
Ca_conc.mod *
CaL.mod *
CaN.mod *
KCa.mod *
KDr.mod *
module1_2.mod *
module3.mod *
Naf.mod *
Nap.mod *
RampIClamp.mod
Xm.mod *
add_hil_is.hoc *
add_muscle_unit.hoc *
add_pics_istim.hoc
CaL_PICs.hoc *
fig4.ses
fixnseg.hoc *
mem_mechanism_acti.hoc *
mem_mechanism_muscle.hoc *
mem_mechanism_pass.hoc *
motor_unit.hoc
v_e_moto6_export.hoc *
Xm.hoc *
                            
//-----------------------------------------------------------------------------------------------------------//
// Localization of synaptic inputs and Ca-PIC channels over dendrites at the similar distance from the soma  //					
//-----------------------------------------------------------------------------------------------------------//

// global constants
v_init=-70
num_row=10000										
max_dist=0											
j=0 												
END_SIM_TIME=10000
tstop=END_SIM_TIME									
STIM_DUR_TIME = 60									
vd_mean_600 = 0
FREQ = 250 				  							
REF = 0.5 

// global variables
objref iCaL[num_row]
objref iSyn[num_row]

// localization of Ca-PIC channels and synaptic inputs at the similar Dpath
proc loc_dend(){local i, init, end, err_dist, err_min, x_min 

	init=0										
	end=0											
	err_dist=0										
	err_min=0										
	x_min=0	

	// calculate the longest path length from the soma
	forall {
		//nseg *= 3									
		soma distance(0, 0)							
		for(x){
			if (max_dist < distance(x)) {					
			max_dist = distance(x)
			}
		}
		err_min=max_dist								
	}
	
	// set the specific Dpath
	i = 600 											 
  	forall {
		init = distance(0)				     
		end  = distance(1)				     
		if (init<=i && i<end) {				 
			for(x) {
				err_dist=abs(i-distance(x))	 
				if (err_min > err_dist) {	 
					err_min=err_dist
					x_min=x
				}	
			}
			if(x_min==0){x_min=0.0001}
			if(x_min==1){x_min=0.9999}
			
			iCaL[j] = new CaL(x_min)
			iCaL[j].gcalbar=1.37 * area(x_min) * (10^-4)^2 * 10^3 //600um [mS/cm2]
			
			iSyn[j] = new RampSyn(x_min)
			iSyn[j].gmax=1.244 * area(x_min) * (10^-4)^2 * 10^3 //600um [mS/cm2]
			
			j=j+1						 
			err_min=max_dist			  
		}
	}
}

loc_dend()

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