Because of the dearth of experimental animal models of psychiatric disorders, the study of the effect of the disease state is only possible in tissue derived from patients vs. controls, especially in the target tissue of disease-related changes in the brain. The human postmortem brain offers the most appropriate experimental paradigm towards understanding the etiology of psychiatric disorders. The availability of post-mortem human samples from psychiatric patients and comparison groups in recent years has contributed prominently to the accumulating body of information leading to a better understanding of these disorders. This is the first book to summarize this research approach and the meaningful data which has recently been acquired.

Many computionally challenging problems omnipresent in science and engineering exhibit multiscale phenomena so that the task of computing or even representing all scales of action is computationally very expensive unless the multiscale nature of these problems is exploited in a fundamental way. Some diverse examples of practical interest include the computation of fluid turbulence, structural analysis of composite materials, terabyte data mining, image processing, and a multitude of others. This book consists of both invited and contributed articles which address many facets of efficient multiscale representation and scientific computation from varied viewpoints such as hierarchical data representations, multilevel algorithms, algebraic homogeni- zation, and others. This book should be of particular interest to readers interested in recent and emerging trends in multiscale and multiresolution computation with application to a wide range of practical problems.