up, via spatial normalization. Such normalization typically involves translation, rotation and scaling and nonlinear warping of the brain surface to match a standard template. Standard brain maps such as the Talairach-Tournoux or templates from the Montréal Neurological Institute (MNI) allow researchers from across the world to compare their results. Images can be smoothed to make the data less noisy (similar to the 'blur' effect used in some image-editing software) by which voxels are averaged with their neighbours, typically using a Gaussian filter or by wavelet transformation. Statistical comparison Parametric statistical models are assumed at each voxel, using the general linear model to describe the data variability in terms of experimental and confounding effects, with residual variability. Hypotheses expressed in terms of the model parameters are assessed at each voxel with univariate statistics. Analyses may examine differences over time (i.e. correlations between a task variable and brain activity in a certain area) using linear convolution models of how the measured signal is caused by underlying changes in neural activity. Because many statistical tests are conducted, adjustments have to be made to control for type I errors (false positives) potentially caused by the comparison of levels of activity over many voxels. A type I error would result in falsely assessing background brain activity as related to the task. Adjustments are made based on the number of resels in the image and the theory of continuous random fields in order to set a new criterion for statistical significance that adjusts for the problem of multiple comparisons. Graphical representations Differences in measured brain activity can be represented in various ways. They can be presented as a table, displaying coordinates that show the most significant differences in activity between tasks. Alternatively, differences in brain activity can be shown as patches of colour on a brain 'slice', with the colours representing the location of voxels with statistically significant differences between conditions. The color gradient is mapped to statistical values, such as t-values or z-scores. This creates an intuitive and visually appealing map of the relative statistical strength of a given area. Differences in activity can be represented as a 'glass brain', a representation of three outline views of the brain as if it were transparent. Only the patches of activation are visible as areas of shading. This is useful as a means of summarizing the total area of significant change in a given statistical comparison. Software