Wavelet-Based fMRI Statistical Analysis and Spatial Interpretation: A Unifying Approach

Wavelet-based statistical analysis methods for fMRI are able to detect brain activity without smoothing the data. Typically, the statistical inference is performed in the wavelet domain by testing the t-values of each wavelet coefficient; subsequently, an activity map is reconstructed from the significant coefficients. The limitation of this approach is that there is no direct statistical interpretation of the reconstructed map. In this paper, we propose a new methodology that takes advantage of wavelet processing but keeps the statistical meaning in the spatial domain. We derive a spatial threshold with a proper non-stationary component and determine optimal threshold values by minimizing an approximation error. The sensitivity of our method is comparable to SPM's (Statistical Parametric Mapping).

• Type: Conference
• Year: 2004
• Where: ISBI
• Authors: Dimitri Van De Ville, Thierry Blu, Michael Unser
• Keywords: Direct Statistical Interpretation, ISBI 2004, Medical Imaging, Statistical Parametric Mapping, Wavelet-based Statistical Analysis