Scaling is necessary when making comparisons between shapes of event-related potential topographies: a reply to Haig et al.

A. R. Haig, E. Gordon, and S. Hook (1997) disputed G. McCarthy and C. C. Wood's (1985) contention that scaling should be used when assessing the statistical significance of between condition (or group) differences in the shapes of event-related potential (ERP) scalp topographies. Haig et al. based their contention upon the lack of empirical realism in McCarthy and Wood's model of within-group ERP noise, claiming that McCarthy and Wood's results could not be generalized to realistic ERP data. We argue, on both empirical and theoretical grounds, that Haig et al. do not make a compelling case against generalization of McCarthy and Wood's results. Moreover, Haig et al.'s conclusion is based upon a misconception of how scaling should be used. We conclude that when a quantitative measure of differences between topographic shapes is needed, scaling is not an option--it is a requirement.