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September 2019 Modelling multilevel spatial behaviour in binary-mark muscle fibre configurations
Tilman M. Davies, Matthew R. Schofield, Jon Cornwall, Philip W. Sheard
Ann. Appl. Stat. 13(3): 1329-1347 (September 2019). DOI: 10.1214/18-AOAS1214

Abstract

The functional properties of skeletal muscles depend on the spatial arrangements of fast and slow muscle fibre types. Qualitative assessment of muscle configurations suggest that muscle disease and normal ageing are associated with visible changes in the spatial pattern, though a lack of statistical modelling hinders our ability to formally assess such trends. We design a nested Gaussian conditional autoregressive (CAR) model to quantify spatial features of dichotomously marked muscle fibre networks and implement it within a Bayesian framework. Our model is applied to data from a human skeletal muscle and results reveal spatial variation at multiple levels across the muscle. The model provides the foundation for future research in describing the extent of change to normal muscle fibre type parameters under experimental or pathological conditions.

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Tilman M. Davies. Matthew R. Schofield. Jon Cornwall. Philip W. Sheard. "Modelling multilevel spatial behaviour in binary-mark muscle fibre configurations." Ann. Appl. Stat. 13 (3) 1329 - 1347, September 2019. https://doi.org/10.1214/18-AOAS1214

Information

Received: 1 March 2018; Revised: 1 September 2018; Published: September 2019
First available in Project Euclid: 17 October 2019

zbMATH: 07145959
MathSciNet: MR4019141
Digital Object Identifier: 10.1214/18-AOAS1214

Keywords: Bayesian inference , Gaussian process , hierarchical model , physiology

Rights: Copyright © 2019 Institute of Mathematical Statistics

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Vol.13 • No. 3 • September 2019
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