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The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.

A computational study of the impact of inhomogeneous internodal lengths on conduction velocity in myelinated neurons

Scurfield, Abby, Latimer, David C.·2018·PLOS ONE
DOI 10.1371/journal.pone.0191106PMC PMC5766232
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Fig 1 Conduction velocity along progressively remyelinated axons. The black squares represent the average CV (and standard deviation) for 500 model neurons with a given fraction of remyelinated segments. The blue solid curve is the benchmark velocity v¯(p). The red circles represent the CV for an axon with uniform internode length given by the average internode length of the remyelinated model neurons.
Fig 1 Conduction velocity along progressively remyelinated axons. The black squares represent the average CV (and standard deviation) for 500 model neurons with a given fraction of remyelinated segments. The blue solid curve is the benchmark velocity v¯(p). The red circles represent the CV for an axon with uniform internode length given by the average internode length of the remyelinated model neurons.CC BY · PubMed Central
Fig 2 Conduction velocity along progressively remyelinated axons for the Gow and Devaux TJ model. The black circles represent the average CV (and standard deviation) for 500 model neurons with a given fraction of remyelinated segments with a g-ratio of 0.69; the blue solid curve is the benchmark velocity v¯(p) for this case. The purple diamonds represent the average CV (and standard deviation) for 500 model neurons with a given fraction of remyelinated segments whose g-ratio is 0.86; the red solid curve is the benchmark velocity v¯(p) for this case.
Fig 2 Conduction velocity along progressively remyelinated axons for the Gow and Devaux TJ model. The black circles represent the average CV (and standard deviation) for 500 model neurons with a given fraction of remyelinated segments with a g-ratio of 0.69; the blue solid curve is the benchmark velocity v¯(p) for this case. The purple diamonds represent the average CV (and standard deviation) for 500 model neurons with a given fraction of remyelinated segments whose g-ratio is 0.86; the red solid curve is the benchmark velocity v¯(p) for this case.CC BY · PubMed Central

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Research works printed but not linked: 39

  1. AL Hodgkin, 1952, A quantitative description of membrane current and its application to conduction and excitation in nerve, J Physiol, 117, 500, 10.1113/jphysiol.1952.sp004764 · DOI · Paper page
  2. MA Matthews, 1968, An electron microscopic study of the relationship between axon diameter and the initiation of myelin production in the peripheral nervous system, Anat Rec, 161, 337, 10.1002/ar.1091610306 · DOI
  3. C Hildebrand, 1993, Myelinated nerve fibres in the CNS, Prog Neurobiol, 40, 319, 10.1016/0301-0082(93)90015-K · DOI
  4. N Baumann, 2001, Biology of oligodendrocyte and myelin in the mammalian central nervous system, Physiol Rev, 81, 871, 10.1152/physrev.2001.81.2.871 · DOI · Paper page
  5. WA Rushton, 1951, A theory of the effects of fibre size in medullated nerve, J Physiol (Lond), 115, 101, 10.1113/jphysiol.1951.sp004655 · DOI
  6. JB Hursh, 1939, Conduction velocity and diameter of nerve fibers, Am J Physiol, 127, 131, 10.1152/ajplegacy.1939.127.1.131 · DOI · Paper page
  7. I Tasaki, 1943, On the relation between the conduction rate, the fibre diameter, and the internodal distance of the medullated nerve fibre, Jpn J Med Sci III Biophys, 9, 189
  8. IA Boyd, 1979, Scaling factor relating conduction velocity and diameter for myelinated afferent nerve fibres in the cat hind limb, J Physiol, 289, 277, 10.1113/jphysiol.1979.sp012737 · DOI
  9. L Goldman, 1968, Computation of impulse conduction in myelinated fibers; theoretical basis of the velocity-diameter relation, Biophys J, 8, 596, 10.1016/S0006-3495(68)86510-5 · DOI
  10. JW Moore, 1978, Simulations of conduction in uniform myelinated fibers. Relative sensitivity to changes in nodal and internodal parameters, Biophys J, 21, 147, 10.1016/S0006-3495(78)85515-5 · DOI
  11. G Aston-Jones, 1985, Age-impaired impulse flow from nucleus basalis to cortex, Nature, 318, 462, 10.1038/318462a0 · DOI
  12. FR Morales, 1987, Basic electrophysiological properties of spinal cord motoneurons during old age in the cat, J Neurophysiol, 58, 180, 10.1152/jn.1987.58.1.180 · DOI
  13. MC Xi, 1999, Changes in the axonal conduction velocity of pyramidal tract neurons in the aged cat, Neuroscience, 92, 219, 10.1016/S0306-4522(98)00754-4 · DOI
  14. A Peters, 2009, The effects of normal aging on myelinated nerve fibers in monkey central nervous system, Frontiers in Neuroanatomy, 3, 11, 10.3389/neuro.05.011.2009 · DOI · Paper page
  15. A Peters, 2003, Is there remyelination during aging of the primate central nervous system?, J Comp Neurol, 460, 238, 10.1002/cne.10639 · DOI
  16. DP Schafer, 2006, Early events in node of Ranvier formation during myelination and remyelination in the PNS, Neuron Glia Biol, 2, 69, 10.1017/S1740925X06000093 · DOI
  17. J McLeod, 1973, Pathological Conduction in Nerve Fibers, Electromyography of Sphincter Muscles, Automatic Analysis of Electromyogram with Computers, vol. 2, 248
  18. BE Powers, 2012, Axonal Thinning and Extensive Remyelination without Chronic Demyelination in Spinal Injured Rats, J Neurosci, 32, 5120, 10.1523/JNEUROSCI.0002-12.2012 · DOI
  19. M Ikeda, 2012, The relationship between nerve conduction velocity and fiber morphology during peripheral nerve regeneration, Brain and Behavior, 2, 382, 10.1002/brb3.61 · DOI
  20. J Lasiene, 2009, Age-related myelin dynamics revealed by increased oligodendrogenesis and short internodes, Aging Cell, 8, 201, 10.1111/j.1474-9726.2009.00462.x · DOI · Paper page
  21. RF Gledhill, 1977, Morphological characteristics of central demyelination and remyelination: A single-fiber study, Ann Neurol, 1, 552, 10.1002/ana.410010607 · DOI
  22. W Brück, 2003, Remyelination in multiple sclerosis, J Neurol Sci, 206, 181, 10.1016/S0022-510X(02)00191-0 · DOI
  23. KJ Smith, 1980, Nerve conduction during peripheral demyelination and remyelination, J Neurol Sci, 48, 201, 10.1016/0022-510X(80)90201-4 · DOI
  24. ID Duncan, 2009, Extensive remyelination of the CNS leads to functional recovery, PNAS, 106, 6832, 10.1073/pnas.0812500106 · DOI · Paper page
  25. H Zhang, 2011, Central nervous system remyelination in culture: A tool for multiple sclerosis research, Exp Neurol, 230, 138, 10.1016/j.expneurol.2011.04.009 · DOI
  26. RG Lascelles, 1966, Changes due to age in internodal length in the sural nerve in man, J Neurol Neurosurg Pyschiat, 29, 40, 10.1136/jnnp.29.1.40 · DOI
  27. AD Vizoso, 1950, The relationship between internodal length and growth in human nerves, J Anat, 84, 342
  28. Y Wang, 2005, Degradation of Signal Timing in Cortical Areas V1 and V2 of Senescent Monkeys, Cerebral Cortex, 15, 403, 10.1093/cercor/bhh143 · DOI
  29. CC McIntyre, 2002, Modeling the excitability of mammalian nerve fibers: Influence of afterpotentials on the recovery cycle, J Neurophysiol, 87, 995, 10.1152/jn.00353.2001 · DOI
  30. ML Hines, 1997, The NEURON simulation environment, Neural Comput, 9, 1179, 10.1162/neco.1997.9.6.1179 · DOI
  31. DMT Dekker, 2014, The impact of internodal segmentation in biophysical nerve fiber models, J Comput Neurosci, 37, 307, 10.1007/s10827-014-0503-y · DOI
  32. AR Blight, 1985, Computer simulation of action potentials and afterpotentials in mammalian myelinated axons: The case for a lower resistance myelin sheath, Neuroscience, 15, 13, 10.1016/0306-4522(85)90119-8 · DOI
  33. J Devaux, 2008, Tight junctions potentiate the insulative properties of small CNS myelinated axons, J Cell Biol, 183, 909, 10.1083/jcb.200808034 · DOI
  34. A Gow, 2008, A model of tight junction function in central nervous system myelinated axons, Neuron Glia Biol, 4, 307, 10.1017/S1740925X09990391 · DOI
  35. MH Brill, 1977, Conduction velocity and spike configuration in myelinated fibres: computed dependence on internode distance, J Neurol Neurosurg Psychiatry, 40, 769, 10.1136/jnnp.40.8.769 · DOI
  36. JM Ritchie, 1981, Sodium and potassium channels in demyelinated and remyelinated mammalian nerve, Nature, 294, 257, 10.1038/294257a0 · DOI
  37. SD Novakovic, 1996, Clusters of axonal Na+ channels adjacent to remyelinating Schwann cells, J Neurocytol, 25, 403, 10.1007/BF02284811 · DOI
  38. M Sasaki, 2006, Molecular reconstruction of nodes of Ranvier after remyelination by transplanted olfactory ensheathing cells in the demyelinated spinal cord, J Neurosci, 26, 1803, 10.1523/JNEUROSCI.3611-05.2006 · DOI
  39. S Dugandzija-Novakovic, 1995, Clustering of Na+ channels and node of Ranvier formation in remyelinating axons, J Neurosci, 15, 492, 10.1523/JNEUROSCI.15-01-00492.1995 · DOI

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Metadata

Authors
Scurfield, A., & Latimer, D. C.
ORCID
Latimer, David C.
Venue
PLOS ONE
Publisher
Public Library of Science (PLoS)
Published
2018-01-12
Volume
13
Issue
1
Pages
e0191106
ISSN
1932-6203
DOI
10.1371/journal.pone.0191106
PMC
PMC5766232
Cited by
38
References
8
Language
en
Licence
creativecommons.org/licenses/by/4.0/ (vor)

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