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 a critical 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. lnterindividual 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. Hidden or nonobvious temporal patterns in behavior are oflong-standing interest in various areas ofbehavioral research: "Behavior consists ofpatterns in time. Investigations of behavior deal with sequences that, in contrast to bodily characteristics, are not always visible" (EiblEibesfeldt, 1970, p. I, emphasis added). Integrated studies of the structure ofverbal and nonverbal behavior have been repeatedly proposed (Pike, 1960; Skinner, 1957): "The activity of man constitutes a structural whole, in such a way that it cannot be subdivided into neat "parts" or "levels" or "compartments" insulated in character, content, and organization from other behavior. Verbal and nonverbal activity is a unified whole, and theory and methodology should be organized or created to treat it as such" (Pike, 1960, p. 2). Such an approach requires sufficient knowledge about recurrent patterns in observable behavior. However, these patterns may be hidden and difficult to detect without adequate tools. This paper concerns some ofthese methodological difficulties and proposes some solutions. hi.is/-msm).butatthetimeofthiswriting.itis hoped that a more powerful commercial version will soon be available from a company (PaUernScope) that is now being created by the author and Icelandic Venture Funds (see www.hi.is/r-rnsrn for up-to-date information).
Another approach for the detection of patterns in behavior are T-Patterns REF .
Discovering hidden time patterns in behavior: T-patterns and their detection
Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc
Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc
Computer Science Medicine