Chapter 5 - Results of Bayesian statistical analysis in normal and ALS subjects

Abstract

This chapter reviews the need for a broadly applicable motor unit number estimation (MUNE) method to allow research into possible therapies for amyotrophic lateral sclerosis (ALS). An ideal MUNE method needs to be applicable to all stages of ALS, to avoid the problems associated with sampling motor units, to allow for motor unit variability, and to have simple data collection methods so that it can be widely applied in different centers. The chapter explores that the knowledge obtained from the study of the stimulus–response curve, and from existing MUNE methods and their limitations led to the development of a Bayesian statistical approach to MUNE. The biological background and statistical methods for Bayesian MUNE method based on the whole stimulus–response curve have been presented. The results of studies in normal subjects and patients with ALS are also discussed in the chapter.