Rat choice in rapidly changing concurrent schedules
Daily schedule changes hurt long-term choice tracking even when moment-by-moment matching looks fine.
01Research in Context
What this study did
The team placed rats in a chamber with two levers.
Each lever paid off on its own VI schedule.
The reinforcer ratio flipped every day.
Researchers watched how choice tracked the new ratios within and across sessions.
What they found
Inside one session the rats matched the new ratio almost perfectly.
Across many sessions that tracking grew weaker.
The animals acted as if yesterday’s ratio still pulled today’s choice.
Standard learning-set ideas can’t explain the slide.
How this fits with other research
Hunter et al. (1985) showed pigeons need about five sessions to lock on to a new ratio.
McLean et al. flipped ratios daily, so the system never settles — that explains the erosion.
Jones et al. (1998) found discriminability fades the longer the rat stays away from the change-over.
Daily flips keep that ‘time-since-changeover’ short, yet sensitivity still drops, so the decay runs deeper than mere time.
Why it matters
If you change token, praise, or activity schedules weekly, don’t assume clients will “catch up” soon.
Build extra review days or booster probes after each switch.
Track data across weeks, not just the first new session, to spot drifting sensitivity.
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Join Free →After any schedule switch, run a mini-probe of the old ratio and graph the dip — then plan re-training.
02At a glance
03Original abstract
In two experiments, experimentally naïve rats were trained in concurrent variable-interval schedules in which the reinforcer ratios changed daily according to a pseudorandom binary sequence. In Experiment 1, relative response rates showed clear sensitivity to current-session reinforcer ratios, but not to previous sessions' reinforcer ratios. Within sessions, sensitivity to the current session's reinforcement rates increased steadily, and by session end, response ratios approached matching to the current-session reinforcer ratios. Across sessions, sensitivity to the current session's reinforcer ratio decreased with continued exposure to the pseudorandom binary sequence, contrary to expectations based on previous studies demonstrating learning sets. Using a second group of naïve rats, Experiment 2 replicated the main results from Experiment 1 and showed that although there were increases over sessions in both changeover rate and response rate during the changeover delay, neither could explain the accompanying reductions in sensitivity. We consider the role of reinforcement history, showing that our results can be simulated using two separate representations, one local and one nonlocal, but a more complex approach will be needed to bring together these results and other history effects such as learning sets and spontaneous recovery.
Journal of the Experimental Analysis of Behavior, 2018 · doi:10.1002/jeab.314