Jones, Kelvin E. and Parveen Bawa. Computer simulation of the responses of human motoneurons to composite 1A EPSPS: effects of background firing rate. J. Neurophysiol. 77: 405–420, 1997. Two compartmental models of spinal alpha motoneurons were constructed to explore the relationship between background firing rate and response to an excitatory input. The results of these simulations were compared with previous results obtained from human motoneurons and discussed in relation to the current model for repetitively firing human motoneurons. The morphologies and cable parameters of the models were based on two type-identified cat motoneurons previously reported in the literature. Each model included five voltage-dependent channels that were modeled using Hodgkin-Huxley formalism. These included fast Na+ and K+ channels in the initial segment and fast Na+ and K+ channels as well as a slow K+ channel in the soma compartment. The density and rate factors for the slow K+ channel were varied until the models could reproduce single spike AHP parameters for type-identified motoneurons in the cat. Excitatory synaptic conductances were distributed along the equivalent dendrites with the same density described for la synapses from muscle spindles to type-identified cat motoneurons. Simultaneous activation of all synapses on the dendrite resulted in a large compound excitatory postsynaptic potential (EPSP). Brief depolarizing pulses injected into a compartment of the equivalent dendrite resulted in pulse potentials (PPs), which resembled the compound EPSPs. The effects of compound EPSPs and PPs on firing probability of the two motoneuron models were examined during rhythmic firing. Peristimulus time histograms, constructed between the stimulus and the spikes of the model motoneuron, showed excitatory peaks whose integrated time course approximated the time course of the underlying EPSP or PP as has been shown in cat motoneurons. The excitatory peaks were quantified in terms of response probability, and the relationship between background firing rate and response probability was explored. As in real human motoneurons, the models exhibited an inverse relationship between response probability and background firing rate. The biophysical properties responsible for the relationship between response probability and firing rate included the shapes of the membrane voltage trajectories between spikes and nonlinear changes in PP amplitude during the interspike interval at different firing rates. The results from these simulations suggest that the relationship between response probability and background firing rate is an intrinsic feature of motoneurons. The similarity of the results from the models, which were based on the properties of cat motoneurons, and those from human motoneurons suggests that the biophysical properties governing rhythmic firing in human motoneurons are similar to those of the cat.
A deep convolutional visual encoding model of neuronal responses in the LGN
