Biomedical subjects

M Slawnych

Publications and source records attributed to M Slawnych.

2 recordsLinked to original sources

PubMed1997

Motor unit number estimation: sample size considerations.

A computer model of the motor unit number estimation procedure was developed to evaluate the sampling error associated with estimates of the number of motor units in muscles. Two different distributions were used to model the motor unit amplitude distribution and were chosen in such a manner that they qualitatively matched the distributions observed under both normal and neurogenic conditions. As expected, the results indicated that estimation error decreases as a function of sample size. However, the relationship between these two variables was nonlinear in the sense that successive increases in sample size lead to progressively smaller decreases in estimation error. The results also indicated that the shape of the motor unit amplitude distribution plays an important role. Specifically, estimates obtained using the distribution modeling normal muscle were generally higher than the actual number of motor units in the muscle, which was not the case for the distribution modeling neurogenic muscle. In addition, the neurogenic distribution was associated with much smaller estimation error, suggesting that motor unit number estimation is well suited to the analysis of neurogenic disease processes.

Cell Count↗

PubMed1996

Motor unit estimates obtained using the new "MUESA" method.

Motor unit number estimates were obtained from the extensor digitorum brevis and thenar muscles using a new method called MUESA. MUESA is distinguished from other estimation methods in the manner in which it deals with probabilistic motor unit activation, which is more commonly referred to as "alternation." Because of "alternation," incremental increases in the observed muscle potentials often cannot be interpreted in terms of the successive activation of single motor units. In the MUESA method, the nerve is subjected to a number of constant-intensity stimulus trains, and the resultant muscle response sequences are decomposed into their constituent motor unit action potentials. In general, if a stimulus train results in the probabilistic activation of n motor units, we can expect to see up to 2n different potentials, with each potential representing a unique combination of active and/or inactive motor units. If all 2n potentials are indeed observed, the decomposition of the observed potential sequence into its constituent motor unit action potentials is very straightforward. For the majority of the cases in which the number of observed potentials is not an integer power of 2, we have developed a novel decomposition method based on the analysis of the relative firing rates of the motor units.

Adolescent↗