day, it was shown that the activity had caused a resting-state change in hippocampal activity. Dynamic causal modeling revealed that the hippocampus also exhibited a new level of effective connectivity with the striatum, though there was no learning-related change in any visual area. Combining fMRI with DCM on subjects performing a learning task allows one to delineate which brain systems are involved in various sorts of learning, whether implicit or explicit, and document for long these tasks lead to changes in resting-state brain activation. IQ estimation Voxel-based morphometric measurements of grey matter localization in the brain can be used to predict components of IQ. A set of 35 teenagers were tested for IQ and were fMRI scanned over the course of 3.5 years, and had their IQ predicted by the level of grey matter localization. This study was well-conducted, but studies of this sort frequently suffer from "double-dipping," where a single dataset is used both to identify the brain regions of interest and to develop a predictive model, which leads to overtraining of the model and an absence of real predictive power. The study authors avoided double-dipping by using a "leave-one-out" methodology, that involves building a predictive model for each of the n members of a sample based on data from the other n-1 members. This ensures that the model is independent of the subject whose IQ is being predicted, and resulted in a model capable of explaining 53% of the change in verbal IQ as a function of grey matter density in the left motor cortex. The study also observed the previously reported phenomenon that a ranking of young subjects by IQ does not stay constant as the subjects age, which confounds any measurement of the efficacy of educational programs. These studies can be cross-validated by attempting to locate and assess patients with lesions or other damage in the identified brain region, and examining whether they exhibit functional deficits relative to the population. This methodology would be hindered by the lack of a "before" baseline measurement, however. Phonological loop The phonological loop is a component of working memory that stores a small set of words that can be maintained indefinitely if not distracted. The concept was proposed by the psychologists Alan Baddeley and Graham Hitch to explain how phrases or sentences can be internalized and used to direct action. By using statistical parametric mapping to assess differences in cerebral