ABA Fundamentals

Combined effects of food deprivation and food frequency on the amount and temporal distribution of schedule-induced drinking.

Castilla et al. (2013) · Journal of the experimental analysis of behavior 2013
★ The Verdict

Hungrier clients drink more between reinforcers and spread the drinks across the whole interval, not just after delivery.

✓ Read this if BCBAs running fixed-interval or fixed-time reinforcement with animals or humans who have free access to water or other adjunctive outlets.
✗ Skip if Clinicians working exclusively with rich VR schedules or token systems where adjunctive behavior is blocked.

01Research in Context

01

What this study did

Luis and team worked with lab rats on a fixed-interval food schedule. They asked two questions: Does food deprivation change how much the rats drink between pellets? Does the time between pellets matter too?

They tested four hunger levels (0, 8, 16, 24 h without food) and three pellet-to-pellet times (30 s, 120 s, 240 s). A lick sensor recorded every tongue touch to a water spout.

02

What they found

Hungrier rats licked more. The biggest jump came between 16 h and 24 h of deprivation. Shorter pellet gaps (30 s) also produced the most licks.

Timing changed with hunger. Well-fed rats drank right after a pellet. Starved rats spread the same drinks across the whole interval, almost like they were pacing themselves.

03

How this fits with other research

Anger et al. (1976) showed drinking peaks when pellets arrive every 120 s. Castilla et al. (2013) found the same sweet spot, but only in mildly hungry rats. At 24 h of deprivation, even the 30-s schedule drove high drinking, so hunger widens the effective range.

Johnson et al. (1994) saw less drinking when water was offered close to the next pellet. Luis saw the opposite: starved rats kept drinking late in the interval. The difference is procedure—R offered one timed sip; Luis let rats drink freely, showing adjunctive patterns can override probe timing.

Together, these studies draw the same curve: drinking rises, peaks, then falls as the interval grows. Hunger lifts the whole curve and flattens it, so the peak is less sharp.

04

Why it matters

If you run FI schedules in a classroom or animal lab, know that hunger and interval length team up. A kid on a lean schedule who skipped lunch may show more water-cooler trips or other adjunctive habits. Track these side behaviors; they can mask or mimic the main target. Try offering a small snack before sessions or lengthening the interval if adjunctive behavior interferes.

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→ Action — try this Monday

Record water or bathroom trips during FI sessions; if they rise, check meal schedule and consider a pre-session snack.

02At a glance

Intervention
not applicable
Design
single case other
Population
not specified
Finding
positive

03Original abstract

Under intermittent food schedules animals develop temporally organized behaviors throughout interfood intervals, with behaviors early in the intervals (interim) normally occurring in excess. Schedule-induced drinking (a prototype of interim, adjunctive behavior) is related to food deprivation and food frequency. This study investigated the interactions that resulted from combining different food-deprivation levels (70%, 80% or 90% free-feeding weights) with different food-occurrence frequencies (15-, 30- or 60-s interfood intervals) in a within-subjects design. Increases in food deprivation and food frequency generally led to increased licking, with greater differences due to food deprivation as interfood intervals became shorter. Distributions of licking were modestly shifted to later in the interfood interval as interfood intervals lengthened, a result that was most marked under 90% food deprivation, which also resulted in flatter distributions. It would therefore appear that food deprivation modulates the licking rate and the distribution of licking in different ways. Effects of food deprivation and food frequency are adequately explained by a theory of adjunctive behavior based on delayed food reinforcement, in contrast to alternative hypotheses.

Journal of the experimental analysis of behavior, 2013 · doi:10.1002/jeab.53