A computer analysis of serial interactions in spaced responding.

Scientists watched monkeys press a lever for food on a DRL 20-second schedule.

They fed every pause that lasted 20 s or more.

A computer recorded each press and ran math checks called autocorrelation and power spectra to hunt for tiny timing patterns the eye cannot see.

Even after long training the monkeys still showed hidden rhythms in their pauses.

Short pauses tended to follow short pauses and long pauses followed long ones across several trials.

These slow waves prove that "steady" DRL performance still carries fine-grained structure.

FARMEMOORHEARSKELLEHER et al. (1964) first mapped DRL pauses in rats but only drew simple histograms.

Cruse et al. (1966) now supersedes that work by showing the same schedule hides serial dependencies that crude graphs miss.

Dews (1978) later used similar computer tools on FI schedules and found the classic scallop inside each interval, proving the method works across schedule types.

Wanchisen et al. (1989) showed that a brief VR history can warp later FI patterns; the monkey data hint that past reinforcement leaves the same kind of temporal footprints under DRL.

If you run DRL to reduce rapid calling out or mouthing, do not assume the client is truly "stable" when the overall rate drops.

Check a few sessions of inter-response times with a simple lag-1 plot or Excel correlation.

A hidden drift toward short-short or long-long runs can signal emerging extinction or reinforcement loss, giving you an early cue to tweak the schedule before the behavior breaks down.