Parametric probability distribution functions for axon diameters of corpus callosum

Sepehrband, Farshid, Alexander, Daniel C., Clark, Kristi A., Kurniawan, Nyoman D., Yang, Zhengyi and Reutens, David C. (2016) Parametric probability distribution functions for axon diameters of corpus callosum. Frontiers in Neuroanatomy, 10 . doi:10.3389/fnana.2016.00059

Author Sepehrband, Farshid
Alexander, Daniel C.
Clark, Kristi A.
Kurniawan, Nyoman D.
Yang, Zhengyi
Reutens, David C.
Title Parametric probability distribution functions for axon diameters of corpus callosum
Journal name Frontiers in Neuroanatomy   Check publisher's open access policy
ISSN 1662-5129
Publication date 2016-05-26
Year available 2016
Sub-type Article (original research)
DOI 10.3389/fnana.2016.00059
Open Access Status DOI
Volume 10
Total pages 9
Place of publication Lausanne, Switzerland
Publisher Frontiers Research Foundation
Collection year 2017
Language eng
Formatted abstract
Axon diameter is an important neuroanatomical characteristic of the nervous system that alters in the course of neurological disorders such as multiple sclerosis. Axon diameters vary, even within a fiber bundle, and are not normally distributed. An accurate distribution function is therefore beneficial, either to describe axon diameters that are obtained from a direct measurement technique (e.g., microscopy), or to infer them indirectly (e.g., using diffusion-weighted MRI). The gamma distribution is a common choice for this purpose (particularly for the inferential approach) because it resembles the distribution profile of measured axon diameters which has been consistently shown to be non-negative and right-skewed. In this study we compared a wide range of parametric probability distribution functions against empirical data obtained from electron microscopy images.We observed that the gamma distribution fails to accurately describe the main characteristics of the axon diameter distribution, such as location and scale of the mode and the profile of distribution tails. We also found that the generalized extreme value distribution consistently fitted the measured distribution better than other distribution functions. This suggests that there may be distinct subpopulations of axons in the corpus callosum, each with their own distribution profiles. In addition, we observed that several other distributions outperformed the gamma distribution, yet had the same number of unknown parameters; these were the inverse Gaussian, log normal, log logistic and Birnbaum-Saunders distributions.
Keyword Axon diameter distribution
Corpus callosum
Electron microscopy
Gamma distribution
Generalized extreme value distribution
Probability distribution function
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
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Centre for Advanced Imaging Publications
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