Technical Program

Paper Detail

Paper:	SS-8.3
Session:	Advanced Methods for Mapping Brain Functions from Functional MRI Datasets
Time:	Thursday, May 18, 14:40 - 15:00
Presentation:	Special Session Lecture
Topic:	Special Sessions: Advanced methods for mapping brain functions from functional MRI datasets
Title:	WSPM or How to Obtain Statistical Parametric Maps using Shift-Invariant Wavelet Processing
Authors:	Dimitri Van De Ville, Thierry Blu, Michael Unser, Swiss Federal Institute of Technology Lausanne (EPFL), Switzerland
Abstract:	Recently, we have proposed a new framework for detecting brain activity from fMRI data, which is based on the spatial discrete wavelet transform. The standard wavelet-based approach performs a statistical test in the wavelet domain, and therefore fails to provide a rigorous statistical interpretation in the spatial domain. The new framework provides an ``integrated'' approach: the data is processed in the wavelet domain (by thresholding wavelet coefficients), and a suitable statistical testing procedure is applied afterwards in the spatial domain. This method is based on conservative assumptions only and has a strong type-I error control by construction. At the same time, it has a sensitivity comparable to that of SPM. Here, we discuss the extension of our algorithm to the redundant discrete wavelet transform, which provides a shift-invariant detection scheme. The key features of our technique are illustrated with experimental results. An implementation of our framework is available as a toolbox (WSPM) for the SPM2 software.