In recent years a number of multivariate approaches have been introduced to map neural systems in health and disease. In this review, we focus on spatial covariance methods applied to functional imaging data to identify patterns of regional activity associated with behavior. In the rest state, this form of network analysis can be used to detect abnormal topographies reflecting regional changes in distributed neural systems. In activation experiments, this approach can be used to quantify network-performance relationships in normal and disease cohorts. Functional changes in the relevant neural systems are likely to underlie the behavioral abnormalities observed in a variety of disease and treatment conditions.