Biophysical Properties of Saltating Potentials in Myelinated Axons

Abstract

The driving objective of this dissertation is to describe the essential biophysical structure, and consequent computational properties, of myelinated axons. In other words, if one were to engineer a brain, what elements should constitute the myelinated axon? Though important parts of the axo-glial biophysical structure are known, many ultrastructural aspects are often overlooked. One such aspect has the potential to fundamentally change the biophysical model for the operation of myelinated axons, including signal processing and energy consumption: conduction in the submyelin spaces. Myelin envelopes nearly all larger-diameter axons, where axons comprise the tracts by which neurons communicate with each other as well as a myriad of other cell types, both from within the central and peripheral nervous systems to those of other organs and muscles throughout the animal body.

The current biophysical model for myelination describes an axo-myelin structure devoid of intermediary conducting pathways (Chapter 1). Empirically, however, multiple spaces with the potential for ionic conduction exist between the axon and its myelin sheath, notably the periaxonal space, which runs along most of the length of myelinated regions. Is this submyelin space materially conductive? A series of experiments and computational modelling demonstrate the conductivity of not only the periaxonal, but also paranodal submyelin spaces (Chapter 2). In addition, these submyelin pathways are connected axially to the extracellular space, creating a double cable biophysical architecture for myelinated axons. A number of biophysical consequences are inferred from the resolved biophysical structure, such as the distinct effect of periaxonal or paranodal space sizes on conduction velocity and signal processing in general (Chapter 2). This approach is generalized and automated to resolve the biophysical properties of the entire neuron – particularly if myelinated – on a rapid and large scale (Chapter 3). Further, digital demyelination of optimized neuron models reveals a mechanism for the experimentally-observed intrinsic hyperexcitability of demyelinated axons (Chapter 3). Finally, the consequences of the double cable architecture of myelinated axons in health and disease are discussed (Chapter 4), describing the axonal plasticity, neuro-glial communication, homeostatic, and energy equilibrium roles submyelin spaces could play, and how this understanding may be harnessed to address disregulated conduction in myelinated axons, such as in degenerative myelin diseases.