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Dear SPM users, the seemingly simple question is if a normalization of functional images (EPI) will be more accurate using the following steps: 1) the structural image (usually T1) is co-registered to the mean EPI 2) normalization parameters are determined for the T1 (via unified segmentation) and 3) normalization parameters are applied to EPI time series The alternative would be to apply the unified segmentation procedure directly to the mean EPI which provides normalization parameters for the time series. Some people (usually neuroscientists) argue that the first procedure is more accurate since the T1 provides much more spatial details (good contrast between GM, WM and CSF) which improve the normalization. Other people (usually MR physicists) argue that the distortions of the two modalities (T1 weighted images vs. T2* weighted images) are quite different. Therefore, good normalization parameters for the structural image are not necessarily helpful in order to transform EPI images into standard MNI space in the best possible way. Is this debate still a "matter of taste" or is there any study that already addressed this issue (which I am not able to find...)? I am aware of the study by Crinion and colleagues (Neuroimage 2007) which addressed a related but still different question. Are there any estimates of displacement using the procedures described above? Thanks a lot for your comments, Thilo -- Thilo Kellermann RWTH Aachen University Department of Psychiatry, Psychotherapy and Psychosomatics JARA Translational Brain Medicine Pauwelsstr. 30 52074 Aachen Germany Tel.: +49 (0)241 / 8089977 Fax.: +49 (0)241 / 8082401 E-Mail: [log in to unmask]