Abstract
This article deals with the definition and detection of particular kinds of temporal patterns in behavior, which are sometimes obvious or well known, but other times difficult to detect, either directly or with standard statistical methods. Characteristics of well-known behavior patterns were abstracted and combined in order to define a scale-independent, hierarchical time pattern type, called aT-pattern. A corresponding detection algorithm was developed and implemented in a computer program, called Theme. The proposed pattern typology and detection algorithm are based on the definition and detection of a particular relationship between pairs of events in a time series, called acritical interval relation. The proposed bottom-up, level-by-level (or breadth-first) search algorithm is based on a binary tree of such relations. The algorithm first detects simpler patterns. Then, more complex and complete patterns evolve through the connection of simpler ones, pattern completeness competition, and pattern selection. Interindividual T-patterns in a quarter-hour interaction between two children are presented, showing that complex hidden T-patterns may be found by Theme in such behavioral streams. Finally, implications for studies of complexity, self-organization, and dynamic patterns are discussed.
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This work was supported by Icelandic Research Council Grants 95140, 96058, and 97163. Special thanks for invaluable support go to J. Beaudichon, University of Paris V-Sorbonne; S. Duncan, University of Chicago; R. Ghiglione, University of Paris XIII; A. Langaney, M.N.H.N., Paris; H. Montagner, INSERM, France; and M. Lyon, S. K. Moeller, and S. Ross, University of Copenhagen. A free executable version (not source code) of the Theme program is available on line (www.hi.is/~msm), but at the time of this writing, it is hoped that a more powerful commercial version will soon be available from a company (PatternScope) that is now being created by the author and Icelandic Venture Funds (see www.hi.is/~msm for up-to-date information).
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Magnusson, M.S. Discovering hidden time patterns in behavior: T-patterns and their detection. Behavior Research Methods, Instruments, & Computers 32, 93–110 (2000). https://doi.org/10.3758/BF03200792
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DOI: https://doi.org/10.3758/BF03200792