Abstract: The invention is a method to aid analysis of signals, such as electroencephalograms, pursuant to modern mathematical theories of nonlinear dynamical processes, sometimes referred to as chaotic dynamics or chaos theory. It employs graphic display and visual inspection of relatively less filtered, non-averaged raw test data, including raw data heretofore considered random or asynchronous `noise`. The invention enables reversible decomposition of selected elements of graphic portraits of raw signal data to identify subsets of the depicted raw data which correspond to visually-identified, manually-selected patterns from within the graphic portrait. The identified subsets of raw data can be segregated even though a precise mathematical description of the visually identified pattern is unknown.