An Optimum Principle Predicts the Distribution of Axon Diameters in Normal White Matter

PLoS ONE

Volumn 8, Issue 1, 2013, Pages

  Pajevic, Sinisa ^a   Basser, Peter J ^b  

^a NATIONAL INSTITUTES OF HEALTH   (United States)

^b EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH AND HUMAN DEVELOPMENT   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; CELL COUNT; CELL SIZE; CELLULAR DISTRIBUTION; CONTROLLED STUDY; INTERMETHOD COMPARISON; MATHEMATICAL MODEL; NERVE CONDUCTION; NERVE FIBER; NORMAL DISTRIBUTION; PARAMETRIC TEST; WHITE MATTER;

ALGORITHMS; AXONS; DIFFUSION MAGNETIC RESONANCE IMAGING; NERVE FIBERS, MYELINATED; OPTIC NERVE;

EID: 84873820936     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0054095     Document Type: Article

References (36)

1. Assaf Y, Blumenfeld-Katzir T, Yovel Y, Basser P, (2008) Axcaliber: a method for measuring axon diameter distribution from diffusion mri. Magnetic Resonance in Medicine 59: 1347-1354.
2. Tasaki I, (1939) The electro-saltatory transmission of the nerve impulse and the effect of narcosis upon the nerve fiber. American Journal of Physiology-Legacy Content 127: 211-227.
3. Hursh JB, (1939) Conduction velocity and diameter of nerve fibers. American Journal of Physiology 127: 131-139.
4. Tasaki I, Ishii K, Ito H, (1943) On the relation between the conduction-rate, the fiber-diameter and the internodal distance of the medullated nerve fiber. Japanese Journal of Medical Sciences III: Biophysics 9: 189-99.
5. van der Knaap MS, Valk J, Barkhof F, (2005) Magnetic resonance of myelination and myelin disorders. Springer Verlag.
6. Fields R, (2008) White matter in learning, cognition and psychiatric disorders. Trends in Neuro-sciences 31: 361-370.
7. Fields R, Stevens-Graham B, (2002) New insights into neuron-glia communication. Science 298: 556.
8. Blair EA, Erlanger J, (1933) A comparison of the characteristics of axons through their individual electrical responses. American Journal of Physiology 106: 524-564.
9. Pumphrey RJ, Young JZ, (1938) The rates of conduction of nerve fibres of various diameters in cephalopods. Journal of Experimental Biology 15: 453-466.
10. Rushton W, (1951) A theory of the effects of fibre size in medullated nerve. The Journal of Physiology 115: 101.
11. Wang SSH, Shultz JR, Burish MJ, Harrison KH, Hof PR, et al. (2008) Functional trade-offs in white matter axonal scaling. Journal of Neuroscience 28: 4047.
12. Basser PJ, (2004) Scaling laws for myelinated axons derived from an electrotonic core-conductor model. Journal of Integrative Neuroscience 3: 227-244.
13. Zhang K, Sejnowski TJ, (2000) A universal scaling law between gray matter and white matter of cerebral cortex. Proceedings of the National Academy of Sciences 97: 5621.
14. He JH, (2006) An allometric scaling law between gray matter and white matter of cerebral cortex. Chaos, Solitons & Fractals 27: 864-867.
15. Pajevic S, Assaf Y, Tasaki I, Basser PJ (2008) An optimum principle predicts skewed and heavy-tailed distributions of axon diameters in white matter fascicles. In: 2008 Neuro-science Meeting Planner, Society for Neuroscience, Online. Washington, D.C., p. 817.9. Available: www.sfn.org/skins/main/pdf/abstracts/am2008/poster-presentations/wednesday-pm.pdf.
16. Perge JA, Niven JE, Mugnaini E, Balasubramanian V, Sterling P, (2012) Why do axons differ in caliber? The Journal of Neuroscience 32: 626-638.
17. Gov NS, (2009) Physical model for the width distribution of axons. The European Physical Journal E: Soft Matter and Biological Physics 29: 337-344.
18. Tasaki I, (2008) Personal communication.
19. Chklovskii DB, Stepanyants A, (2003) Power-law for axon diameters at branch point. BMC Neu-roscience 4: 18.
20. Chen B, Hall D, Chklovskii D, (2006) Wiring optimization can relate neuronal structure and func-tion. Proceedings of the National Academy of Sciences of the United States of America 103: 4723.
21. Stein R, (1967) The information capacity of nerve cells using a frequency code. Biophysical Journal 7: 797-826.
22. Jacobson H, (1950) The informational capacity of the human ear. Science 112: 143.
23. Jacobson H, (1951) The informational capacity of the human eye. Science 113: 292.
24. Rapoport A, Horvath WJ, (1960) The theoretical channel capacity of a single neuron as determined by various coding systems. Information and Control 3: 335-350.
25. Lass Y, Abeles M, (1975) Transmission of information by the axon: I. Noise and memory in the myelinated nerve fiber of the frog. Biological Cybernetics 19: 61-67.
26. Abeles M, Lass Y, (1975) Transmission of information by the axon: II. The channel capacity. Biological Cybernetics 19: 121-125.
27. MacKay D, McCulloch W, (1952) The limiting information capacity of a neuronal link. Bulletin of Mathematical Biology 14: 127-135.
28. Zador A, (1998) Impact of synaptic unreliability on the information transmitted by spiking neurons. Journal of Neurophysiology 79: 1219.
29. Hildebrand F, (1965) Methods of applied mathematics. Dover Publications.
30. Limpert E, Stahel WA, Abbt M, (2001) Log-normal distributions across the sciences: Keys and clues. BioScience 51: 341-352.
31. Aitchison J, Brown JAC (1963) The lognormal distribution. Cambridge University Press.
32. Heath D, (1967) Normal or log-normal: Appropriate distributions. Nature 213: 1159-1160.
33. Ong HH, Wright AC, Wehrli SL, Souza A, Schwartz ED, et al. (2008) Indirect measurement of regional axon diameter in excised mouse spinal cord with q-space imaging: Simulation and experimental studies. Neuroimage 40: 1619-1632.
34. Aboitiz F, Scheibel AB, Fisher RS, Zaidel E, (1992) Fiber composition of the human corpus callo-sum. Brain research 598: 143-153.
35. Keeling KB, Pavur RJ, (2007) A comparative study of the reliability of nine statistical software packages. Computational Statistics & Data Analysis 51: 3811-3831.
36. Odeh OO, Featherstone AM, Bergtold JS, (2010) Reliability of statistical software. American Journal of Agricultural Economics 92: 1472-1489.