In light of the increasing importance for measuring myelingratios - the ratio of axon-to-fiber (axon + myelin) diameters in myelin internodes - to understand normal physiology, disease states, repair mechanisms and myelin plasticity, there is urgent need to minimize processing and statistical artifacts in current methodologies. Unfortunately, many contemporary studies fall prey to a variety of artifacts, which reduce study outcome robustness and slow development of novel therapeutics. Underlying causes stem from a lack of understanding of the myelingratio, which has persisted more than a century. An extended exploratory data analysis from first principles (the axon-fiber diameter relation) is presented herein and has major consequences for interpreting publishedgratio studies. Indeed, a model of the myelin internode naturally emerges because of (1) the strong positive correlation between axon and fiber diameters and (2) the demonstration that the relation between these variables is one of direct proportionality. From this model, a robust framework for data analysis, interpretation and understanding allows specific predictions about myelin internode structure under normal physiological conditions. Further, the model establishes that a regression fit togratio plots has zero slope, and it identifies the underlying causes of several data processing artifacts that can be mitigated by plottinggratios against fiber diameter (not axon diameter). Hypothesis testing can then be used for extending the model and evaluating myelin internodal properties under pathophysiological conditions (accompanying article). For without a statistical model as anchor, hypothesis testing is aimless like a rudderless ship on the ocean.
