Open AccessPermutation testing of orthogonal factorial effects in a language‐processing experiment using fMRI
Author(s) -
Suckling John,
Davis Matthew H.,
Ooi Cinly,
Wink Alle Meije,
Fadili Jalal,
Salvador Raymond,
Welchew David,
Şendur Levent,
Maxim Vochita,
Bullmore Edward T.
Publication year - 2006
Publication title -
human brain mapping
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.005
H-Index - 191
eISSN - 1097-0193
pISSN - 1065-9471
DOI - 10.1002/hbm.20252
Subject(s) - sentence , permutation (music) , type i and type ii errors , inferior frontal gyrus , artificial intelligence , set (abstract data type) , speech recognition , psychology , pattern recognition (psychology) , computer science , statistics , mathematics , functional magnetic resonance imaging , neuroscience , physics , acoustics , programming language
Abstract The block‐paradigm of the Functional Image Analysis Contest (FIAC) dataset was analysed with the Brain Activation and Morphological Mapping software. Permutation methods in the wavelet domain were used for inference on cluster‐based test statistics of orthogonal contrasts relevant to the factorial design of the study, namely: the average response across all active blocks, the main effect of speaker, the main effect of sentence, and the interaction between sentence and speaker. Extensive activation was seen with all these contrasts. In particular, different vs. same‐speaker blocks produced elevated activation in bilateral regions of the superior temporal lobe and repetition suppression for linguistic materials (same vs. different‐sentence blocks) in left inferior frontal regions. These are regions previously reported in the literature. Additional regions were detected in this study, perhaps due to the enhanced sensitivity of the methodology. Within‐block sentence suppression was tested post‐hoc by regression of an exponential decay model onto the extracted time series from the left inferior frontal gyrus, but no strong evidence of such an effect was found. The significance levels set for the activation maps are P ‐values at which we expect <1 false‐positive cluster per image. Nominal type I error control was verified by empirical testing of a test statistic corresponding to a randomly ordered design matrix. The small size of the BOLD effect necessitates sensitive methods of detection of brain activation. Permutation methods permit the necessary flexibility to develop novel test statistics to meet this challenge. Hum Brain Mapp27:425–433, 2006. © 2006 Wiley‐Liss, Inc.