Journal
NEUROIMAGE
Volume 28, Issue 3, Pages 544-552Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2005.04.045
Keywords
VBM; cluster inference; random fields analysis; schizophrenia; learning disability
Funding
- Medical Research Council [G0100102] Funding Source: Medline
- MRC [G0100102] Funding Source: UKRI
- Medical Research Council [G0100102] Funding Source: researchfish
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We present an empirical comparison of cluster extent and maximal voxel results in a voxel-based morphometry (VBM) study of brain structure. The cluster extents are adjusted for underlying deviation from uniform smoothness. We implement this comparison on a four-group cohort that has previously shown evidence of a neuro-developmental component in schizophrenia (Moorhead, T.W.J., Job, D.E., Whalley, H.C., Sanderson, T.L., Johnstone, E.C. and Lawrie, S.M. 2004. Voxel-based morphometry of comorbid schizophrenia and learning disability: analyses in normalized and native spaces using parametric and nonparametric statistical methods. NeuroImage 22: 188-202.). We find that adjusted cluster extent results provide information on the nature of deficits that occur in the schizophrenia affected groups, and these important structural differences are not all shown in maximal voxel results. The maximal voxel and cluster extent results are corrected for multiple comparisons using Random Fields (RF) methods. In order to apply the cluster extent measures, we propose a post-hoe method for determining the primary threshold in the analysis. Unadjusted cluster extent results are reported, for these, no allowance is made for non-isotropic smoothness, and comparison with the adjusted extent results shows that the unadjusted results can be either conservative or anti-conservative depending upon the underlying tissue distributions. (c) 2005 Elsevier Inc. All rights reserved.
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