This chapter talks about the validity of general recognition theory (GRT) and discusses how GRT analyses can be extended to neuroscience data and especially to data from neuroimaging experiments. GRT has all the advantages of univariate signal detection theory, but it also offers the best existing method for examining interactions among perceptual dimensions. GRT and signal detection theory both assume that decision processes act on a percept that may depend on the nature of the task, but does not depend on the actual response that is made. The encoding approach is similar to typical applications of GRT, except neuroimaging data are used to test the models as well as behavioral data. Unlike traditional behavioral applications, however, multiple GRT analyses could be possible with neuroimaging data. For example, functional magnetic resonance imaging (fMRI) provides enough data that different GRT models could be fit to data from each separate neural region-of-interest (ROI).
