Abstract #301298

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JSM 2003 Abstract #301298
Activity Number: 251
Type: Contributed
Date/Time: Tuesday, August 5, 2003 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #301298
Title: Making the T-test Relevant to fMRI Data
Author(s): Martina Pavlicova*+ and Noel A. C. Cressie and Thomas J. Santner
Companies: The Ohio State University and Ohio State University and The Ohio State University
Address: 1958 Neil Ave., Columbus, OH, 43210-1247,
Keywords: ROC curve ; non-Gaussian distribution ; power-threshold plot
Abstract:

The most traditional method of processing functional magnetic resonance imaging (fMRI) data is based on a voxel-wise general linear model (GLM). For simple designs, such as the box-car 0-1 design, a haemodynamic response function (HRF) is convolved with the design function and the result is fit to the time series data obtained for each voxel. However, GLM fitting assumes correct specification of the HRF. We avoid direct specification of the HRF; rather, we assume only knowledge of haemodynamic delay, which is used to omit scans acquired in transition periods between activation and rest.To test voxel differences between activation data and rest data, we propose use of a modified version of the two-sample t-test that accounts for departures from Gaussian and independence assumptions. The modified and classical t-tests are compared by applying both to artificial data and comparing their performances using ROC curves and power-threshold plots.

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