The Annals of Statistics

Rotation space random fields with an application to fMRI data

K. Shafie, D. Siegmund, B. Sigal, and K.J. Worsley

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Abstract

Siegmund and Worsley considered the problem of testing for a signal with unknown location and scale in a Gaussian random field defined on~$\mathbb{R}^N$. The test statistic was the maximum of a Gaussian random field in an $(N+1)$-dimensional "scale space," N dimensions for location and one dimension for the scale of a smoothing kernel. Siegmund and Worsley used two methods, one involving the expected Euler characteristic of the excursion set and the other involving the volume of tubes, to derive an approximate null distribution. The purpose of this paper is to extend the scale space result to the rotation space random field when N=2, where the maximum is taken over all rotations of the filter as well as scales. We apply this result to the problem of searching for activation in brain images obtained by functional magnetic resonance imaging (fMRI).

Article information

Source
Ann. Statist., Volume 31, Number 6 (2003), 1732-1771.

Dates
First available in Project Euclid: 16 January 2004

Permanent link to this document
https://projecteuclid.org/euclid.aos/1074290326

Digital Object Identifier
doi:10.1214/aos/1074290326

Mathematical Reviews number (MathSciNet)
MR2036389

Zentralblatt MATH identifier
1043.92019

Subjects
Primary: 60G60: Random fields 62M09: Non-Markovian processes: estimation
Secondary: 60D05: Geometric probability and stochastic geometry [See also 52A22, 53C65] 52A22: Random convex sets and integral geometry [See also 53C65, 60D05]

Keywords
Euler characteristic differential topology integral geometry nonstationary random fields image analysis

Citation

Shafie, K.; Sigal, B.; Siegmund, D.; Worsley, K.J. Rotation space random fields with an application to fMRI data. Ann. Statist. 31 (2003), no. 6, 1732--1771. doi:10.1214/aos/1074290326. https://projecteuclid.org/euclid.aos/1074290326


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