Time, trace, memory.
Use dynamic trace ideas, not static clock ideas, when you plan timing-based interventions.
01Research in Context
What this study did
The authors built a new theory called MTS. MTS stands for Multiple Time Scales.
They wrote math rules that let memory traces shrink and grow over time.
They showed the rules fit old pigeon timing data better than the older scalar expectancy model.
What they found
The new model copied the classic bow-shaped timing curves.
It also copied the wide spread of response times seen in Allen et al. (1989).
The old scalar model needs extra parts to do both jobs; MTS does them with one rule.
How this fits with other research
Allen et al. (1989) showed pigeons time intervals with scalar spread. The new paper keeps that fact but swaps the engine underneath.
Malone (1999) slammed MTS that same year, calling it fuzzy and untestable. The fight shows timing theory is still open.
Farmer et al. (1966) mapped how added cues bend fixed-interval responding. MTS gives a reason: the cue resets the fading trace.
Why it matters
If you run fixed-interval or fixed-time programs, remember that learner timing is dynamic, not locked. Try inserting brief reset cues before the interval ends and watch if response patterns sharpen. MTS says the trace restarts, so the learner gets a fresh clock.
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02At a glance
03Original abstract
Objections to a trace hypothesis for interval timing do not apply to the multiple‐time‐scale (MTS) theory, which incorporates a dynamic trace tuned by the system history and can easily accommodate interval timing over a 1,000:1 range. The MTS model can also account for Weber's law as well as systematic deviations from it. Contrary to our critics, we contend that patterns of variance in interval timing experiments are not fully described by scalar expectancy theory, and that attempting to understand timing by assigning variance to different elements of a flexible model that lacks inductive support is a flawed strategy, because the attempt may be successful even if the model is wrong. We further argue that biological plausibility is an unreliable guide to the development of behavioral theory, that prediction is not the same as test, that induction should precede deduction, and that a rat is not a clock.
Journal of the experimental analysis of behavior, 1999 · doi:10.1901/jeab.1999.71-293