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Semiparametric Bayesian local functional models for diffusion tensor tract statistics.

Publication ,  Journal Article
Hua, Z; Dunson, DB; Gilmore, JH; Styner, MA; Zhu, H
Published in: NeuroImage
October 2012

We propose a semiparametric Bayesian local functional model (BFM) for the analysis of multiple diffusion properties (e.g., fractional anisotropy) along white matter fiber bundles with a set of covariates of interest, such as age and gender. BFM accounts for heterogeneity in the shape of the fiber bundle diffusion properties among subjects, while allowing the impact of the covariates to vary across subjects. A nonparametric Bayesian LPP2 prior facilitates global and local borrowings of information among subjects, while an infinite factor model flexibly represents low-dimensional structure. Local hypothesis testing and credible bands are developed to identify fiber segments, along which multiple diffusion properties are significantly associated with covariates of interest, while controlling for multiple comparisons. Moreover, BFM naturally group subjects into more homogeneous clusters. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. A simulation study is performed to evaluate the finite sample performance of BFM. We apply BFM to investigate the development of white matter diffusivities along the splenium of the corpus callosum tract and the right internal capsule tract in a clinical study of neurodevelopment in new born infants.

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Published In

NeuroImage

DOI

EISSN

1095-9572

ISSN

1053-8119

Publication Date

October 2012

Volume

63

Issue

1

Start / End Page

460 / 474

Related Subject Headings

  • Pattern Recognition, Automated
  • Neurology & Neurosurgery
  • Nerve Fibers, Myelinated
  • Male
  • Infant, Newborn
  • Infant
  • Image Interpretation, Computer-Assisted
  • Image Enhancement
  • Humans
  • Female
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Hua, Z., Dunson, D. B., Gilmore, J. H., Styner, M. A., & Zhu, H. (2012). Semiparametric Bayesian local functional models for diffusion tensor tract statistics. NeuroImage, 63(1), 460–474. https://doi.org/10.1016/j.neuroimage.2012.06.027
Hua, Zhaowei, David B. Dunson, John H. Gilmore, Martin A. Styner, and Hongtu Zhu. “Semiparametric Bayesian local functional models for diffusion tensor tract statistics.NeuroImage 63, no. 1 (October 2012): 460–74. https://doi.org/10.1016/j.neuroimage.2012.06.027.
Hua Z, Dunson DB, Gilmore JH, Styner MA, Zhu H. Semiparametric Bayesian local functional models for diffusion tensor tract statistics. NeuroImage. 2012 Oct;63(1):460–74.
Hua, Zhaowei, et al. “Semiparametric Bayesian local functional models for diffusion tensor tract statistics.NeuroImage, vol. 63, no. 1, Oct. 2012, pp. 460–74. Epmc, doi:10.1016/j.neuroimage.2012.06.027.
Hua Z, Dunson DB, Gilmore JH, Styner MA, Zhu H. Semiparametric Bayesian local functional models for diffusion tensor tract statistics. NeuroImage. 2012 Oct;63(1):460–474.
Journal cover image

Published In

NeuroImage

DOI

EISSN

1095-9572

ISSN

1053-8119

Publication Date

October 2012

Volume

63

Issue

1

Start / End Page

460 / 474

Related Subject Headings

  • Pattern Recognition, Automated
  • Neurology & Neurosurgery
  • Nerve Fibers, Myelinated
  • Male
  • Infant, Newborn
  • Infant
  • Image Interpretation, Computer-Assisted
  • Image Enhancement
  • Humans
  • Female