This chapter presents the advantages of the use of functional regions of interest along with its specific concerns, and provides a reference to Karl J. Friston related to the subject. Functionally defined ROI help to test hypotheses about the cognitive functions of particular regions of the brain. fROI are useful for specifying brain locations and investigating separable components of the mind. The chapter provides an overview of the common and uncommon misconceptions about fROI related to assumptions of homogeneity, factorial designs (...) versus independent localizers, a summary measure, and the naming of fROI. (shrink)

Published research findings are sometimes refuted by subsequent evidence, says Ioannidis, with ensuing confusion and disappointment.

Sample correlations converge to the population value with increasing sample size, but the estimates are often inaccurate in small samples. In this report we use Monte-Carlo simulations to determine the critical sample size from which on the magnitude of a correlation can be expected to be stable. The necessary sample size to achieve stable estimates for correlations depends on the effect size, the width of the corridor of stability, and the requested confidence that the trajectory does not leave this corridor (...) any more. Results indicate that in typical scenarios the sample size should approach 250 for stable estimates. (shrink)