Scalar expectancy

The Scalar timing or scalar expectancy theory (SET) is a model that posits an internal clock, and particular memory and decision processes.[1] SET is the predominate model of animal timing behavior.[2]

History

John Gibbon originally proposed the scalar expectancy model, an extension of Weber's Law, as a quantitative model used to explain the temporally controlled behavior on non-human subjects.[1] SET in its early version was primarily used to explain the break-run pattern, a common response pattern on fixed-interval reinforcement schedules.[3] In a break-run pattern, an animal does not start responding to the stimulus upon representation. However, as the target duration approaches, the subject switches to a high rate of responding; this switch occurs at approximately two-thirds of the target duration.[1]

Animal mechanism

The clock and memory are driven by a discrete pacemaker-accumulator mechanism that yields a linear scale for encoded time. The scalar expectancy theory posits that animals make choices based on a single sample. The animals are posited to make estimates of the time to reinforcement delivery using a scalar-timing process. This scalar-timing process rescales estimates for different values of the interval being timed. Scalar-timing implies a constant coefficient of variation. Expectations or reinforcement are based on these estimates are formed from these sample. The animal discriminates between response alternatives by taking the ratio of their expectancies. A number of alternatives have been developed over the years. These include Killeen’s Behavioral Theory of timing (BeT) model[4] and Machado’s learning-to-time (LeT) model.[5]

Human mechanism

In 1993, Wearden claimed that human behavior exhibits appropriate scalar properties, as was indicated by in experiments of on internal production with concurrent chronometric counting.[6] However, human timing behavior in undoubtedly more varied that animal timing behavior. A major factor responsible for this variability is attentional allocation.[6]

References

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