ABA Fundamentals

Single-sample discrimination of different schedules' reinforced interresponse times.

Tanno et al. (2009) · Journal of the experimental analysis of behavior 2009
★ The Verdict

The time between a learner’s own responses can act as a built-in cue to tell schedules apart.

✓ Read this if BCBAs who thin reinforcement schedules or teach schedule discrimination.
✗ Skip if Practitioners who work only with fixed-ratio or fixed-interval programs.

01Research in Context

01

What this study did

Tanno et al. (2009) asked if rats can tell schedules apart by the timing of their own presses. They set up two schedules that paid off only after the rat waited a set time between presses. The gap between reinforced times was either small or large.

Each rat got one long session. The computer switched schedules many times without any lights or sounds. The only cue was the pattern of reinforced wait times.

02

What they found

When the reinforced wait times were far apart, the rats acted differently right away. They pressed faster during the random-ratio part and slower during the random-interval part.

With small time gaps, the rats could not tell the schedules apart. Bigger temporal gaps gave the rats a clear signal they could use.

03

How this fits with other research

Shimp (1967) first showed that paying for short waits makes pigeons press faster. Takayuki extends that idea: the wait time itself becomes a cue the animal notices.

Haring (1985) found that waits longer than one second are more sensitive to outside stimuli. Takayuki agrees: longer gaps between reinforced waits made the schedule easier to discriminate.

Dodd (1984) proved pigeons can tell DRL from DRO schedules. Takayuki shows rats can also tell random-ratio from random-interval schedules using only the timing of their own responses.

04

Why it matters

If you use schedule thinning, think about the time between responses. A wide gap in reinforced wait times can help the learner notice the new rule. A narrow gap may blur the rule and slow learning. Try adding a brief pause requirement when you shift from rich to lean schedules; the pause itself can signal the change.

Free CEUs

Want CEUs on This Topic?

The ABA Clubhouse has 60+ free CEUs — live every Wednesday. Ethics, supervision & clinical topics.

Join Free →
→ Action — try this Monday

Insert a short wait requirement when you move to a leaner schedule and watch if the learner adjusts pace.

02At a glance

Intervention
other
Design
single case other
Population
other
Finding
positive

03Original abstract

Food-deprived rats in Experiment 1 responded to one of two tandem schedules that were, with equal probability, associated with a sample lever. The tandem schedules' initial links were different random-interval schedules. Their values were adjusted to approximate equality in time to completing each tandem schedule's response requirements. The tandem schedules differed in their terminal links: One reinforced short interresponse times; the other reinforced long ones. Tandem-schedule completion presented two comparison levers, one of which was associated with each tandem schedule. Pressing the lever associated with the sample-lever tandem schedule produced a food pellet. Pressing the other produced a blackout. The difference between terminal-link reinforced interresponse times varied across 10-trial blocks within a session. Conditional-discrimination accuracy increased with the size of the temporal difference between terminal-link reinforced interresponse times. In Experiment 2, one tandem schedule was replaced by a random ratio, while the comparison schedule was either a tandem schedule that only reinforced long interresponse times or a random-interval schedule. Again, conditional-discrimination accuracy increased with the temporal difference between the two schedules' reinforced interresponse times. Most rats mastered the discrimination between random ratio and random interval, showing that the interresponse times reinforced by these schedules can serve to discriminate between these schedules.

Journal of the experimental analysis of behavior, 2009 · doi:10.1901/jeab.2009.91-157