Simulations of motor unit discharge patterns (Powers et al. 2011)

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Accession:143671
" ... To estimate the potential contributions of PIC (Persistent Inward Current) activation and synaptic input patterns to motor unit discharge patterns, we examined the responses of a set of cable motoneuron models to different patterns of excitatory and inhibitory inputs. The models were first tuned to approximate the current- and voltage-clamp responses of low- and medium-threshold spinal motoneurons studied in decerebrate cats and then driven with different patterns of excitatory and inhibitory inputs. The responses of the models to excitatory inputs reproduced a number of features of human motor unit discharge. However, the pattern of rate modulation was strongly influenced by the temporal and spatial pattern of concurrent inhibitory inputs. Thus, even though PIC activation is likely to exert a strong influence on firing rate modulation, PIC activation in combination with different patterns of excitatory and inhibitory synaptic inputs can produce a wide variety of motor unit discharge patterns."
Reference:
1 . Powers RK, Elbasiouny SM, Rymer WZ, Heckman CJ (2012) Contribution of Intrinsic Properties and Synaptic Inputs to Motoneuron Discharge Patterns: A Simulation Study. J Neurophysiol 107(3):808-23 [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 cell;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Activity Patterns; Bursting; Action Potentials;
Implementer(s): Powers, Randy [rkpowers at u.washington.edu];
Search NeuronDB for information about:  Spinal cord lumbar motor neuron alpha cell;
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PowersEtAl2012
code
Gfluctdv.mod *
ghchan.mod *
kca2.mod *
kdrRL.mod *
L_Ca.mod *
mAHP.mod *
na3rp.mod *
naps.mod *
synss.mod
ana_FI.hoc
ana_G.hoc
ana_passive.hoc
ana_vc.hoc
ana_vc_synss.hoc
AP_AHP.ses
FIgraph.hoc
FRcablepas.hoc
FRmnrampcc.ses
FRmnrampvc_synss.ses
FRMotoneuronNaHH.hoc
gramp.ses
GUI_FR_analysis.hoc
inhibdist
makebiramp.hoc *
passive.ses
RecActive.hoc
re-init.hoc
SetConductances.hoc
test.hoc
twobirampsdel.hoc *
vramp
vrampdel
vrampdel.hoc
                            
/* makebiramp.hoc

   sets up a triangular waveform for use as a command potential

   assumes the following are known:

   dt		time step

*/



// Easy mnemonics so I can set these in the interpreter

// and then invoke simple() (just in case I forget the calling

// syntax for mkramp(), or maybe only want to change one param).

// My convention for constants is upper case

V0 = -80	// default for stdrun.hoc is -65 mV

SLOPE = 0.2	// mv/ms

TR = 10000	// ms





objref mycmd,mycmd1,mycmd2

mycmd = new Vector()	// must create object outside proc
mycmd1 = new Vector()	// must create object outside proc
mycmd2 = new Vector()	// must create object outside proc





/* Creates a "ramp" vector

      _____ v1

     /

    / slope

v0 /

    tr



 arguments:

   $1	v0	command at start of ramp	(mV)

   $2	slope	dv/dt during ramp			(mV/ms)

   $3	tr	duration of ramp			(ms)

		note 1: v1 = v0 + slope*tr

		note 2: at end of t0 + tr, vector.play will leave 

			command at v1, but if this is played into 

			dur2 of a SEClamp object, what really happens 

			will depend on whether t enters dur3

 */

// I double the initial letter so these local variables won't 

// collide with global names that I may want to use later

proc mkbiramp() { local ii, vv0, sslope, ttr, vv1

	vv0 = $1

	sslope = $2

	ttr = $3

	vv1 = vv0 + sslope*ttr/2

	mycmd1.indgen(vv0, vv1, dt*sslope)
	mycmd2.indgen(vv0,vv1,dt*sslope)
 mycmd2.reverse()
 mycmd.resize(0)
 mycmd.append(mycmd1,mycmd2)

}





// I can invoke mkbiramp() with all 3 arguments,

// or I can change a single "constant" (V0, SLOPE, or TR)

// and then invoke simple() with no arguments.

proc simple() {

	mkbiramp(V0, SLOPE, TR)

}

proc vsimple() {

	mkbiramp(vV0, vSLOPE, vTR)

}


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