Motor unit number estimation using reversible jump Markov chain Monte Carlo methods

Journal of the Royal Statistical Society. Series C: Applied Statistics

Volumn 56, Issue 3, 2007, Pages 235-269

  Ridall, P G ^a   Pettitt, A N ^a   Friel, N ^b   McCombe, P A ^c   Henderson, R D ^c  

^a QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

^b UNIVERSITY OF GLASGOW   (United Kingdom)

^c UNIVERSITY OF QUEENSLAND   (Australia)

Author keywords

Alternation; Amyotrophic lateral sclerosis; Markov chain Monte Carlo methods; Motor neurone disease; Motor unit number estimation; Reversible jump

Indexed keywords

EID: 34249044465     PISSN: 00359254     EISSN: 14679876     Source Type: Journal    
DOI: 10.1111/j.1467-9876.2007.00576.x     Document Type: Article

References (41)

1. Benarroch, E. E., Westmoreland, B. F., Daube, J. R., Regan, T. J. Sandok, B. A. (1999) Medical Neurosciences: an Approach to Anatomy, Pathology by Systems and Levels, 4th edn. London : Lippincott Williams and Wilkins.
2. Bergmans, J. (1970) The Physiology of Single Human Nerve Fibres. Louvain : Vander.
3. Bjornskov, E. K., Norris, F. H. J. Mower-Kuby, J. (1984) Quantitative axon terminal and end-plate morphology in amyotrophic lateral sclerosis. Arch. Neurol., 41, 527 530.
4. Blok, J., Visser, G., de Graaf, S., Zwarts, M. Stegeman, D. (2005) Statistical motor unit number estimation assuming a binomial distribution. Muscle Nerve, 31, 182 191.
5. Bostock, H., Cikurel, K. Burke, D. (1998) Threshold tracking techniques in the study of human peripheral nerve. Muscle Nerve, 21, 137 158.
6. Bromberg, M. B. (1993) Motor unit estimation: reproducibility of the spike-triggered averaging technique in normal and ALS subjects. Muscle Nerve, 16, 466 471.
7. Bromberg, M. B. (2003) Consensus. In Motor Unit Number Estimation: Proc. 1st Int. Symp. Motor Unit Number Estimation (ed. M. B. Bromberg pp. 335 338. London : Elsevier.
8. Brooks, S. P. Giudici, P. (1998) Convergence assessment for reversible jump MCMC simulations. In Bayesian Statistics 6 (eds J. M. Bernardo, J. Berger, A. P. Dawid A. F. M. Smith pp. 733 742. Oxford : Oxford University Press.
9. Brooks, S. P., Giudici, P. Roberts, G. O. (2003) Efficient construction of reversible jump Markov chain Monte Carlo proposal distributions (with discussion). J. R. Statist. Soc. B, 65, 3 55.
10. Bruce, I. C., White, M. W., Irlicht, L. S., O'Leary, S. J., Dynes, S., Javel, E. Clark, G. M. (1999) A stochastic model of the electrically stimulated auditory nerve: single-pulse response. IEEE Trans. Biomed. Engng, 46, 617 629.
11. Daube, J. R. (1995) Estimating the number of motor units in a muscle. J. Clin. Neurphysiol., 16, 585 594.
12. Day, S. J. Hulliger, M. (2001) Experimental simulation of cat electromyogram: evidence for algebraic summation of motor-unit action-potential trains. J. Neurophys., 86, 2144 2158.
13. Doherty, T. J. Brown, W. F. (1993) The estimated numbers and relative sizes of thenar motor units as selected by multiple point stimulation in young and old adults. Muscle Nerve, 16, 355 366.
14. Feinstein, B., Lindegard, B., Nyman, E. Wohlfart, G. (1955) Morphologic studies of motor units in normal human muscles. Acta. Anat., 23, 127 142.
15. Green, P. J. (1995) Reversible jump Markov chain Monte Carlo computation and Bayesian model determination. Biometrika, 82, 711 732.
16. Hales, J. P., Liu, S.-Y. C. Bostock, H. (2004) Variations in excitability of single human motor axons, related to stochastic properties of nodal sodium channels. J. Physiol., 559, 953 964.
17. Henderson, R. D., Ridall, P. G., McCombe, P. A., Pettitt, A. N. Daube, J. R. (2006) The stimulus-response curve and motor unit variability in normal and ALS subjects. Muscle Nerve, 34, 34 43.
18. Hodgkin, A. L. Huxley, A. F. (1952) A quantitative description of membrane current and its application to conduction and excitation in nerves. J. Physiol., 1, 500 544.
19. Liu, J. S. (2001) Monte Carlo Strategies in Scientific Computing. London : Springer.
20. McComas, A. J., Fawcett, P., Cambell, M. Sica, R. (1971) Electrophysiological estimation of the number of motor units within a human muscle. J. Neurol. Neursurg. Psychiatr., 34, 121 131.
21. Richardson, S. Green, P. J. (1997) On Bayesian analysis of mixtures with an unknown number of components (with discussion). J. R. Statist. Soc. B, 59, 731 792
22. McCombe, P. (2006) Motor unit number estimation: a Bayesian approach. Biometrics, 62, 1235 1250.
23. Shefner, J. M. (2001) Motor unit number estimation in human neurological diseases and animal models. J. Clin. Neurphysiol., 112, 955 964.
24. Shefner, J. M., Cudkowicz, M. E., Zhang, H., Schoenfeld, D. Jillapalli, D. (2004) The use of statistical MUNE in a multicenter clinical trial. Muscle Nerve, 30, 463 469.
25. Slawnych, M., Laszlo, C. Herschler, C. (1996) Motor unit estimates obtained using the new ''MUESA'' method. Muscle Nerve, 19, 626 636.
26. Stein, R. B. Yang, J. F. (1990) Methods for estimating the number of motor units in human muscles. Ann. Neurol., 28, 487 495.
27. Verveen, A. A. (1960) On the fluctuation of the threshold of the nerve fibre. In Structure and Function of the Cerebral Cortex (eds D. B. Tower J. P. Schade). Amsterdam : Elsevier.
28. Aitkin, M., Boys, R. J. Chadwick, T. (2005) Bayesian point null hypothesis testing via the posterior likelihood ratio. Statist. Comput., 15, 217 230.
29. Al-Awadhi, F., Hurn, M. A. Jennison, C. (2004) Improving the acceptance rate of reversible jump MCMC proposals. Statist. Probab. Lett., 69, 189 198.
30. Andrieu, C. Karagiannis, G. (2007) Annealed importance sampling for improved reversible jump algorithms. Technical Report. Statistics Group, University of Bristol, Bristol.
31. Andrieu, C. Roberts, G. O. (2006) The pseudo-marginal approach for efficient computation. Technical Report. Statistics Group, University of Bristol, Bristol.
32. Blok, J. H., van Dijk, J. P., Drost, G., Zwarts, M. J. Stegeman, D. F. (2002) A high-density multichannel surface electromyography system for the characterization of single motor units. Rev. Scient. Instrum., 73, 1887 1897.
33. Blok, J. H., van Dijk, J. P., Zwarts, M. J. Stegeman, D. F. (2005) Motor unit action potential topography and its use in motor unit number estimation. Muscle Nerve, 32, 280 291.
34. Bromberg, M. B. (2003) Consensus. In Motor Unit Number Estimaton (ed. M. B. Bromberg pp. 335 338. Amsterdam : Elsevier.
35. Doherty, T. J., Stashuk, D. W. Brown, W. F. (1993) Determinants of mean motor unit size: impact on estimates of motor unit number. Muscle Nerve, 16, 1326 1331.
36. Green, P. J. Mira, A. (2001) Delayed rejection in reversible jump Metropolis-Hastings. Biometrika, 88, 1035 1053.
37. Papaspiliopoulos, O., Roberts, G. O. Sköld, M. (2007) A general framework for parametrisation of hierarchical models. Statist. Sci., to be published.
38. Richardson, S. Green, P. J. (1997) On Bayesian analysis of mixtures with an unknown number of components (with discussion). J. R. Statist. Soc. B, 59, 731 792 correction, 60 (1998), 661.
39. Ridall, P. G., Pettitt, A. N., Henderson, R. McCombe, P. (2006) Motor unit number estimation: a Bayesian approach. Biometrics, 62, 1235 1250.
40. Roberts, G. O., Papaspiliopoulus, O. Dellaportas, P. (2004) Bayesian inference for non-Gaussian Ornstein-Uhlenbeck stochastic volatility processes. J. R. Statist. Soc. B, 66, 369 393.
41. Shefner, J. M. (2001) Motor unit number estimation in human neurological disease and animal models. Clin. Neurphysiol., 112, 955 964.