title: What is the optimal value of the g-ratio for myelinated fibers in the rat CNS? A theoretical approach.
abstract: BACKGROUND
  The biological process underlying axonal myelination is complex and often prone to injury and disease. The ratio of the inner axonal diameter to the total outer diameter or g-ratio is widely utilized as a functional and structural index of optimal axonal myelination. Based on the speed of fiber conduction, Rushton was the first to derive a theoretical estimate of the optimal g-ratio of 0.6 [1]. This theoretical limit nicely explains the experimental data for myelinated axons obtained for some peripheral fibers but appears significantly lower than that found for CNS fibers. This is, however, hardly surprising given that in the CNS, axonal myelination must achieve multiple goals including reducing conduction delays, promoting conduction fidelity, lowering energy costs, and saving space.
  
  
  RESULTS
  In this study we explore the notion that a balanced set-point can be achieved at a functional level as the micro-structure of individual axons becomes optimized, particularly for the central system where axons tend to be smaller and their myelin sheath thinner. We used an intuitive yet novel theoretical approach based on the fundamental biophysical properties describing axonal structure and function to show that an optimal g-ratio can be defined for the central nervous system (approximately 0.77). Furthermore, by reducing the influence of volume constraints on structural design by about 40%, this approach can also predict the g-ratio observed in some peripheral fibers (approximately 0.6).
  
  
  CONCLUSIONS
  These results support the notion of optimization theory in nervous system design and construction and may also help explain why the central and peripheral systems have evolved different g-ratios as a result of volume constraints.
authors.affiliation: Department of Clinical Neurosciences and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada. tgchomia@ucalgary.ca
authors.forename: Taylor
authors.initials: T
authors.lastname: Chomiak
authors.forename: Bin
authors.initials: B
authors.lastname: Hu
mesh_terms: D000465:Algorithms; D000818:Animals; D001369:Axons / Q000378:metabolism / Q000473:pathology; D002490:Central Nervous System / Q000502:physiology*; D004560:Electricity; D004594:Electrophysiology / Q000379:methods; D046529:Microscopy, Electron, Transmission / Q000379:methods; D008954:Models, Biological; D015233:Models, Statistical; D009186:Myelin Sheath / Q000502:physiology*; D009413:Nerve Fibers, Myelinated / Q000502:physiology; D009431:Neural Conduction; D051381:Rats