Rotation and scale space random fields and the gaussian kinematic formula

Robert J. Adler, Eliran Subag, Jonathan E. Taylor

Research output: Contribution to journalArticlepeer-review

Abstract

We provide a new approach, along with extensions, to results in two important papers of Worsley, Siegmund and coworkers closely tied to the statistical analysis of fMRI (functional magnetic resonance imaging) brain data. These papers studied approximations for the exceedence probabilities of scale and rotation space random fields, the latter playing an important role in the statistical analysis of fMRI data. The techniques used there came either from the Euler characteristic heuristic or via tube formulae, and to a large extent were carefully attuned to the specific examples of the paper. This paper treats the same problem, but via calculations based on the so-called Gaussian kinematic formula. This allows for extensions of the Worsley-Siegmund results to a wide class of non-Gaussian cases. In addition, it allows one to obtain results for rotation space random fields in any dimension via reasonably straightforward Riemannian geometric calculations. Previously only the two-dimensional case could be covered, and then only via computer algebra. By adopting this more structured approach to this particular problem, a solution path for other, related problems becomes clearer.

Original languageEnglish
Pages (from-to)2910-2942
Number of pages33
JournalAnnals of Statistics
Volume40
Issue number6
DOIs
StatePublished - Dec 2012

Keywords

  • Euler characteristic
  • FMRI
  • Gaussian kinematic formula
  • Lipschitz-Killing curvatures
  • Random fields
  • Rotation space
  • Scale space
  • Thresholding

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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