Motoneuron pool input-output function (Powers & Heckman 2017)

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Accession:239582
"Although motoneurons have often been considered to be fairly linear transducers of synaptic input, recent evidence suggests that strong persistent inward currents (PICs) in motoneurons allow neuromodulatory and inhibitory synaptic inputs to induce large nonlinearities in the relation between the level of excitatory input and motor output. To try to estimate the possible extent of this nonlinearity, we developed a pool of model motoneurons designed to replicate the characteristics of motoneuron input-output properties measured in medial gastrocnemius motoneurons in the decerebrate cat with voltage- clamp and current-clamp techniques. We drove the model pool with a range of synaptic inputs consisting of various mixtures of excitation, inhibition, and neuromodulation. We then looked at the relation between excitatory drive and total pool output. Our results revealed that the PICs not only enhance gain but also induce a strong nonlinearity in the relation between the average firing rate of the motoneuron pool and the level of excitatory input. The relation between the total simulated force output and input was somewhat more linear because of higher force outputs in later-recruited units. ..."
Reference:
1 . Powers RK, Heckman CJ (2017) Synaptic control of the shape of the motoneuron pool input-output function. J Neurophysiol 117:1171-1184 [PubMed]
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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): Spinal cord lumbar motor neuron alpha ACh cell;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s):
Implementer(s): Powers, Randy [rkpowers at u.washington.edu];
Search NeuronDB for information about:  Spinal cord lumbar motor neuron alpha ACh cell;
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RPCH_JNP17
FivecompthTA
FivecompthTA_15
FivecompthTA_15.hoc
                            
//modified from cMG to be more like human MN with longer AHP lower thresh PIC
//PIC inactivation also reduced and less skew in distribution of properties
soma.diam = 26.986149584487535
soma.L = 3396.3905817174514
soma.g_pas = 0.00026531576177285326
soma.e_pas = -71.62326869806094
soma.gbar_na3rp = 0.0174792243767313
soma.gbar_naps = 2.226038781163435e-05
soma.sh_na3rp = 1.0
soma.sh_naps = 5.0
soma.ar_na3rp = 1.0
soma.ar_naps = 1.0
soma.gMax_kdrRL = 0.01811634349030471
soma.gcamax_mAHP = 7.992701866928584e-06
soma.gkcamax_mAHP = 0.0005434903047091413
soma.taur_mAHP = 52.60387811634349
soma.ek = -80.0
soma.Ra = 0.001
soma.cm = 1.6814731578947368
soma.ghbar_gh = 0.00015465373961218837
soma.half_gh = -77.0
forsec dend{
L = 2063.868227146814
diam = 10.709457229916898
g_pas = 0.0001390196731301939
e_pas = -71.62326869806094
gcabar_L_Ca_inact = 0.0001143213296398892
Ra = 44.62892797783933
cm = 0.8756503905817175
ghbar_gh = 0.00015465373961218837
half_gh = -77.0
}
d1.gcabar_L_Ca_inact = 0.00010556786703601108
d2.gcabar_L_Ca_inact = 0.00011556786703601108
d3.gcabar_L_Ca_inact = 0.0001236842105263158
d4.gcabar_L_Ca_inact = 0.0001386842105263158
qinf_na3rp = 8.0
thinf_na3rp = -50.0
vslope_naps = 5.0
asvh_naps = -90.0
bsvh_naps = -22.0
mvhalfca_mAHP = -20.0
mtauca_mAHP = 2.0
celsius = 37.0
theta_m_L_Ca_inact = -40.13019390581717
tau_m_L_Ca_inact = 40.0
theta_h_L_Ca_inact = -2.4653739612188375
tau_h_L_Ca_inact = 2500.0
kappa_h_L_Ca_inact = 5.0
htau_gh = 30.0
mVh_kdrRL = -21.0
tmin_kdrRL = 0.8
taumax_kdrRL = 20.0
V0 = 0.5817174515235468