### Figure 1

This
schematic depicts the transformations that start with an imaging data sequence
and end with a statistical parametric map (SPM). SPMs that can be thought of as 'X-rays' of
the significance of an effect.
Voxel-based analyses require the data to be in the same anatomical
space: This is effected by realigning the data (and removing movement-related
signal components that persist after realignment). After realignment the images are subject to
non-linear warping so that they match a template that already conforms to a
standard anatomical space. After
smoothing, the general linear model is employed to (i) estimate the parameters
of the model and (ii) derive the appropriate univariate test statistic at every
voxel (see Figure 4.htm). The test statistics that ensue (usually T or
F statistics) constitute the SPM. The
final stage is to make statistical inferences on the basis of the SPM and
Random Field theory (see Figure 7.htm) and characterize
the responses observed using the fitted responses or parameter estimates.