Wavelet-Based Statistical Parametric Mapping (WSPM)

WSPM release 1.40

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Introduction

The WSPM toolbox is implemented and maintained by Dimitri Van De Ville. The underlying theoretical framework was developed together with Michael Unser and Thierry Blu, initially at the Biomedical Imaging Group (EPFL). The main contribution of WSPM is to combine wavelet thresholding/denoising with voxel-wise statistical hypothesis testing.

These pages introduce the WSPM toolbox (wavelet-based SPM). After checking the pre-requisites, you can go on to download and install the toolbox. To understand how to use the toolbox, feel free to follow the example.

News and history

  • December, 2009: release version 1.40
    • SPM 8 compatibility
  • October 15, 2008: release version 1.32
    • Minor bugfix
  • September 2, 2008: release version 1.31
    • Minor bugfixes
    • FDR procedure working for identity transform
  • April 29, 2008: release version 1.30
    • Due to popular demand – SPM5 compatibility
  • March 17, 2008: release version 1.23
    • False discovery rate support
  • February 27, 2007: release version 1.22
    • Multi-volume support
    • Minor bugfixes
    • Complete batch support (thanks to Tom Nichols)
    • Examples can be found in WSPM.m
  • February 16, 2007: release version 1.21
    • Batch-mode to generate contrasts (results)
    • 3D DWT: different number of iterations in XY and Z supported
    • Significance volume (wspmT*.*) in the spatial domain is masked (outside mask = NaN)
    • Support for custom mask (ROI-based and corrected or uncorrected hypothesis testing)
    • Contrast volume (con*.*) in the spatial domain such that they can be used for a second-level WSPM analysis
  • October 7, 2005: release version 1.10
    • Multi-sessions compatible
    • Automatic change-dir to the working directory SPM.swd
    • Contrast volume is written without thresholding in wavelet domain to better accommodate for group analyses in near future
    • Wavelet coefficients for contrast and variance are written also to volumes now; again, these could be exploited later on for group analyses in the wavelet domain
    • Added “multiple” redundancy option for quincunx subsampling scheme
    • Added additional type of error control: False Discovery Rate
    • Bug fix for MATLAB 7.x
    • Adaptive SPM.Wavelet.wCon structure for flexible adding/removing of wavelet-related parameters of a contrast
    • Works without mask volume if it is not available
    • Detect whether DWT volumes of same transform have been computed before; asks to replace or recompute
  • April 22, 2005: release version 1.00

References

  1. D. Van De Ville, T. Blu, M. Unser “Integrated Wavelet Processing and Spatial Statistical Testing of fMRI Data,” NeuroImage, vol. 23, no. 4, pp. 1472-1485, December 2004.
  2. D. Van De Ville, T. Blu, M. Unser “Surfing the Brain: An Overview of Wavelet-Based Techniques for fMRI Data Analysis,” IEEE Engineering in Medicine and Biology Magazine, vol. 25, no. 2, pp. 65-78, March-April 2006.
  3. D. Van De Ville, M.L. Seghier, F. Lazeyras, T. Blu, M. Unser “WSPM: Wavelet-Based Statistical Parametric Mapping,” Neuroimage, vol. 37, no. 4, pp. 1205-1217, October 2007.
  4. D. Van De Ville, M. Unser “False Discovery Rate for Wavelet-Based Statistical Parametric Mapping,” IEEE Journal of Selected Topics in Signal Processing, vol. 2, no. 6, pp. 897-906, 2008.