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COMPARISON OF VARIANCE AND COVARIANCE PATTERNS IN PARALLEL AND SERIAL THEORIES OF TIMING
Author(s) -
Gibbon John,
Church Russell M.
Publication year - 1992
Publication title -
journal of the experimental analysis of behavior
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.75
H-Index - 61
eISSN - 1938-3711
pISSN - 0022-5002
DOI - 10.1901/jeab.1992.57-393
Subject(s) - autocorrelation , covariance , serial learning , expectancy theory , computer science , contrast (vision) , duration (music) , analysis of covariance , statistics , psychology , mathematics , neuroscience , artificial intelligence , cognition , social psychology , art , literature
Parallel and serial timing processes are analyzed for their account of the dynamics of intertrial responding in the peak procedure. A strictly serial model, such as the behavioral theory of timing (Killeen & Fetterman, 1988), does not fit the dynamic correlation pattern in the location and duration of the middle high‐rate responding portion of peak trials. In contrast, the parallel scalar expectancy theory model, with a sample for memory and threshold, does fit this pattern. A modification of the serial model is presented that also accommodates the within‐trial covariance pattern. The modification, which is formally equivalent to a model for human tapping (Wing & Kristofferson, 1973), entails the addition of concurrent processes operating in parallel with serial timing.