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Runs included 24?s http://en.wikipedia.org/wiki/NK_cells blocks corresponding to the five conditions, which were repeated twice for a total duration of 360?s. The order of conditions within runs was counterbalanced within and across subjects. At the end of each scan session a 3D high resolution T1-weighted anatomical image (TR/TE?=?9.68/4.6?ms, TI?=?1100?ms, field of view?=?250?mm, matrix?=?256?��?256, slice thickness?=?1.2?mm, 182 slices, SENSE factor?=?2) was acquired. Human data were analyzed with the Statistical Parameter Mapping package, SPM2 and SPM 8 (Wellcome Department of Cognitive Neurology, London, UK), implemented in Matlab (The Mathworks Inc.). Results were very similar for the two versions of SPM. For each subject, motion correction was performed by realignment of all http://www.selleckchem.com/products/Gefitinib.html the functional EPI volumes to the first volume of the first time series and a mean image of the realigned volumes was created. This mean image was co-registered to the anatomical T1-weighted image. Both the anatomical and the mean EPI image were warped to a standard reference system (Talairach and Tournoux, 1988), by normalizing both to their respective template images (Montreal Neurological Institute, MNI). Subsequently, the derived normalization parameters from the mean EPI image, were applied to all EPI volumes, which were subsampled to a voxel size of 2?��?2?��?2?mm and smoothed with a Gaussian kernel of 5?mm FWHM. Statistical analysis was performed using the General Linear Model (Friston et al., 1995a?and?Friston et al., 1995b) by modeling each condition using a delayed boxcar function and by convolving this with the http://www.selleckchem.com/products/DAPT-GSI-IX.html hemodynamic response function. Global signal intensity was normalized and an appropriate high-pass temporal filter (2 times the total duration of all different conditions in a run) was applied to remove low frequency drifts independent of stimuli-induced signal changes. The first level contrasts for the different action types (hand action and actor action) compared to their three respective controls were calculated for each individual subject. These contrast images were subjected to a second level, random-effects ANOVA analysis. The interactions were investigated at this second level by subtracting hand action minus its averaged controls from actor action minus its averaged controls. These interactions were masked inclusively with the single effect of actor action compared to its controls (at p?