Springer Discovering Hidden Temporal Patterns in Behavior and Interaction: T-Pattern Detection and Analysis with THEME™: 111 (Neuromethods, 111)

Discovering hidden recurring patterns in observable behavioral processes is an important issue frequently faced by numerous advanced students and researchers across many research areas, including psychology, biology, sports, robotics, media, finance, and medicine. As generally, themany powerful methods included in statistical software packages were not developed for this kind of analysis, discovering such patterns has proven a particularly difficult task, due to a lack of a) adequate formalized models of the kinds of patterns to look for, b) corresponding detection algorithms and c) their implementation in available software. The research described in this book is based on the application of such pattern types, algorithms and software developed from the late seventies to the present in the context of research in collaboration with human and animal behavioral research teams at internationally leading universities in the US and Europe, thus testing the usefulness and validity of the pattern types, algorithms and software in numerous research areas. With the (scale independent statistical hierarchical and fractal-like) T-Pattern at its heart, a set of proposed pattern types, called the T-System, forms the basis for the search algorithms implemented as the software THEME (TM) (vs. 6), which is easily available in free educational and full commercial versions.