To alleviate this loss of power due to data misregistration across subjects at the cortex, some developmental studies have used an approach known as cortical pattern matching (P. M. Thompson et al., 2004). This approach aligns data from different subjects by matching the entire cortical surface across subjects and also performs a higher-order matching of intervening surface areas between the major sulci, using advanced mathematical models based on continuum mechanics. This improves the localization of brain changes, which can be referred to specific gyri, and it also boosts statistical power by removing, as far as possible, the very wide variations in cortical patterns before evaluating gray matter differences. In situations where cortical patterns between brains are topologically different, a one-to-one match may not exist at the gross anatomical level. A well-studied example is that the paracingulate sulcus is less frequently present in schizophrenic patients. Rather than reject the premise of normalizing anatomy altogether, the best conceivable solution is to match accurately what can be matched, and treat what cannot be matched as unmodeled residual variation.
