ABA Fundamentals

Leaving patches: An investigation of a laboratory analogue.

Davison et al. (1994) · Journal of the experimental analysis of behavior 1994
★ The Verdict

Learners make small timing errors that change when they leave reinforcement-rich settings.

✓ Read this if BCBAs designing concurrent schedules or token economies.
✗ Skip if Clinicians focused only on discrete trial training.

01Research in Context

01

What this study did

Researchers watched pigeons choose between two feeding spots. One spot gave food often. The other gave food rarely.

The birds had to fly a short distance to switch spots. The team tracked how long each bird stayed before leaving.

They compared two math models. One assumed perfect timing. The other added small timing errors.

02

What they found

The model with timing errors fit the real data far better. Pigeons do not count seconds like a stopwatch.

Small mistakes in judging time changed when birds left each spot. The old perfect-timing model missed these patterns.

03

How this fits with other research

Sherwell et al. (2014) built on this idea. They showed that brief extra cues help animals notice when food odds change. This sharpens the same timing errors Dougherty et al. (1994) modeled.

White (1979) gave a simpler view. Pigeons switched spots based only on current reward rates, ignoring past events. The 1994 study adds memory limits to that baseline.

Allen et al. (1989) found pigeons reproduce time with built-in noise. This supports the 1994 model's use of Weber's law for timing errors.

04

Why it matters

When you set up reinforcement schedules, remember learners cannot track time perfectly. Build in extra cues or signals before changing reward rates. This prevents frustration and keeps responding steady.

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Add a 2-second warning stimulus before thinning reinforcement in any concurrent schedule.

02At a glance

Intervention
not applicable
Design
single case other
Sample size
5
Population
not specified
Finding
not reported

03Original abstract

Five pigeons were trained on a procedure that has been used as a laboratory analogue to natural patch residence. Trials commenced with two responses available. One of these might provide a reinforcer if the patch was a prey patch; the other ended the residence time in the patch and, after a fixed travel time in blackout, produced another patch that might or might not provide a reinforcer. Patch residence also ended, and was followed by the same travel time, after a reinforcer was obtained or after a fixed maximum time was spent in the patch. The dependent variable was patch residence time, from the commencement of the patch to the time at which the subject emitted a response to exit from the patch or until the maximum patch residence time had elapsed. In Parts 1 to 3, the duration of the imposed travel time was varied from 0.25 to 16 s at three different probabilities (.05, .1, and .2) of food per second (lambda) in prey patches. As reported in previous research, both increasing travel time and decreasing probabilities of reinforcers per second increased patch residence time. In Parts 4 to 7, the probability of prey trials (rho) was varied in an irregular order from .1, through .2, .5, and .7, to .9 for different combinations of lambda and travel time. Respectively, these were in Part 4, .05 per second and 0.25 s; in Part 5, .05 per second and 16 s; in Part 6, .2 per second and 0.25 s; and in Part 7, .2 per second and 16 s. A previously offered model, based on optimization assumptions, substantially and consistently underpredicted patch residence time. However, a modification of that model, which assumes that the subjects could not accurately discriminate the residence time that provided the minimum interreinforcer interval, described the data well. The same model also described previously reported residence times in a different species with a uniform distribution of prey-arrival times.

Journal of the experimental analysis of behavior, 1994 · doi:10.1901/jeab.1994.62-89