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Hi: We recently got 'dinged' for using the FEAT clusterizing method to correct for multiple comparisons. Here is the reviewer's complaint: "The methods section is at present too confusing to evaluate scientifically - just as a side remark - it is not state-of-the-art any longer to analyze brain imaging data based on Gaussianized T- or F-fields and use corrected P-values based on the cluster-size statistic. This was general knowledge at the end of the 90's and I doubt Worsley, Evans, Marrett, & Neelin, 1992, even discuss the cluster-size statistic, since if I remember correctly, this test-statistic was introduced by Poline et al. ~ 1994." What is your current thinking about this -- should we use the False Discovery Rate procedure instead or can we argue that the method we are using is both valid and appropriate? Clark