Derivation of cable parameters for a reduced model that retains asymmetric voltage attenuation of reconstructed spinal motor neuron dendrites.

Spinal motor neurons have voltage gated ion channels localized in their dendrites that generate plateau potentials. The physical separation of ion channels for spiking from plateau generating channels can result in nonlinear bistable firing patterns. The physical separation and geometry of the dendrites results in asymmetric coupling between dendrites and soma that has not been addressed in reduced models of nonlinear phenomena in motor neurons. We measured voltage attenuation properties of six anatomically reconstructed and type-identified cat spinal motor neurons to characterize asymmetric coupling between the dendrites and soma. We showed that the voltage attenuation at any distance from the soma was direction-dependent and could be described as a function of the input resistance at the soma. An analytical solution for the lumped cable parameters in a two-compartment model was derived based on this finding. This is the first two-compartment modeling approach that directly derived lumped cable parameters from the geometrical and passive electrical properties of anatomically reconstructed neurons.

Change in excitability of motor axons modifies statistical MUNE results.

Motor unit number estimation (MUNE) techniques--whether they reflect a true motor unit count or some related index--should not be confounded by changes in the neuromuscular system other than a decline in the number of functional motor units. In neurodegenerative conditions such as amyotrophic lateral sclerosis (ALS), there is evidence of changes in the excitability of motor axons. If changes in axon excitability confound a particular MUNE technique, this would influence the use of that technique in ALS patients. We hypothesized on the basis of computational models that changes in axon membrane excitability would change the outcome of a statistical MUNE test, even though the true number of motor units remained unchanged. To test the validity of the model predictions we induced changes in axon excitability of healthy control subjects by applying a polarizing current while simultaneously carrying out a statistical MUNE test. In a group of 7 subjects we found a significant difference in MUNE as a result of the change in axon excitability produced by the polarizing current (paired t-test, P < 0.05). We conclude that the statistical MUNE method is confounded by changes in axon excitability. Since increasing evidence shows that axon excitability is altered as part of the pathophysiological process underlying ALS, clinical researchers should be cautious when using statistical MUNE with this patient population.

Simulations of motor unit number estimation techniques.

Motor unit number estimation (MUNE) is an electrodiagnostic procedure used to evaluate the number of motor axons connected to a muscle. All MUNE techniques rely on assumptions that must be fulfilled to produce a valid estimate. As there is no gold standard to compare the MUNE techniques against, we have developed a model of the relevant neuromuscular physiology and have used this model to simulate various MUNE techniques. The model allows for a quantitative analysis of candidate MUNE techniques that will hopefully contribute to consensus regarding a standard procedure for performing MUNE.

Method for counting motor units in mice and validation using a mathematical model.

Weakness and atrophy are clinical signs that accompany muscle denervation resulting from motor neuron disease, peripheral neuropathies, and injury. Advances in our understanding of the genetics and molecular biology of these disorders have led to the development of therapeutic alternatives designed to slow denervation and promote reinnervation. Preclinical in vitro research gave rise to the need of a method for measuring the effects in animal models. Our goal was to develop an efficient method to determine the number of motor neurons making functional connections to muscle in a transgenic mouse model of amyotrophic lateral sclerosis (ALS). We developed a novel protocol for motor unit number estimation (MUNE) using incremental stimulation. The method involves analysis of twitch waveforms using a new software program, ITS-MUNE, designed for interactive calculation of motor unit number. The method was validated by testing simulated twitch data from a mathematical model of the neuromuscular system. Computer simulations followed the same stimulus-response protocol and produced waveform data that were indistinguishable from experiments. We show that our MUNE protocol is valid, with high precision and small bias across a wide range of motor unit numbers. The method is especially useful for large muscle groups where MUNE could not be done using manual methods. The results are reproducible across naïve and expert analysts, making it suitable for easy implementation. The ITS-MUNE analysis method has the potential to quantitatively measure the progression of motor neuron diseases and therefore the efficacy of treatments designed to alleviate pathologic processes of muscle denervation.