title: Statistical tests for fMRI based on experimental randomization.
abstract: Statistical parametric mapping (SPM) analysis of fMRI data requires specifying correctly the temporal and spatial noise covariance structure. This is a difficult if not impossible task. When these assumptions are not satisfied, statistical inference can be invalid or inefficient. Permutation tests are free of strong assumptions on the distribution of signal noise. We propose permutation tests of fMRI data based on experimental randomization of the stimulus sequences. Smooth hemodynamic response curves are estimated using quadratic B-splines. We study fMRI data obtained from event-related potential (ERP) oddball paradigm. Tests of two-tone and three-tone stimulus sequences are conducted to illustrate the application of the proposed method. Comparisons of the SPM and proposed method show that a permutation test is more specific and less susceptible to artifacts.
authors.affiliation: Division of Biostatistics, University of Pennsylvania, Philadelphia, PA 19104, USA.
authors.forename: Jonathan
authors.initials: J
authors.lastname: Raz
authors.forename: Hui
authors.initials: H
authors.lastname: Zheng
authors.forename: Hernando
authors.initials: H
authors.lastname: Ombao
authors.forename: Bruce
authors.initials: B
authors.lastname: Turetsky
mesh_terms: D001143:Arousal / Q000502:physiology*; D016477:Artifacts; D001931:Brain Mapping; D002540:Cerebral Cortex / Q000502:physiology*; D018913:Event-Related Potentials, P300 / Q000502:physiology; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000706:statistics & numerical data*; D021621:Imaging, Three-Dimensional / Q000706:statistics & numerical data*; D016014:Linear Models; D008279:Magnetic Resonance Imaging / Q000706:statistics & numerical data*; D008432:Mathematical Computing; D010898:Pitch Perception / Q000502:physiology*; D011597:Psychomotor Performance / Q000502:physiology; D011897:Random Allocation