Greater reinforcement rate during training increases spontaneous recovery
Heavy rewards during teaching can backfire later when you try to fade them out.
01Research in Context
What this study did
The team worked with pigeons and one child.
They taught a simple task using different reward schedules.
Some learners got lots of rewards. Others got only a few.
Then they stopped all rewards to see what happened.
What they found
The birds and child who got more rewards showed bigger bounce-back later.
When rewards stopped, their old behavior returned stronger.
More rewards during training meant more relapse after extinction.
How this fits with other research
LeBlanc et al. (2003) showed that rich schedules make behavior harder to stop.
Thrailkill's work extends this by showing the same rich schedules also cause bigger spontaneous recovery later.
Stancliffe et al. (2007) warned that spontaneous recovery can look like extinction side effects.
This study gives you the lever to control it: dial down the reinforcement rate during training.
Bachá-Méndez et al. (2007) found resurgence of whole behavioral sequences.
Thrailkill shows even single responses can roar back if they were heavily reinforced.
Why it matters
When you build a new skill, don't over-reward at first. Use leaner schedules to prevent later relapse. If the client already has a rich reinforcement history, plan booster extinction sessions or shift to thinner schedules before stopping rewards completely.
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02At a glance
03Original abstract
Spontaneous recovery occurs when a previously reinforced and recently extinguished response reemerges over the course of time, often at the beginning of a new session of extinction. Spontaneous recovery could underlie instances of treatment relapse that threaten otherwise effective behavioral interventions for problem behavior. In two experiments, we arranged multiple schedules with pigeons and a human child to assess the effects of different training reinforcer rates on spontaneous recovery. In both experiments, responding was both more resistant to extinction and more likely to relapse following training with greater reinforcement rates upon returning to extinction after time off from extinction testing. A quantitative model based on behavioral momentum theory accounted well for the data, which suggests reexposure to the extinction context following time off during extinction resulted in (1) the failure of extinction learning to generalize, and (2) greater generalization of original learning during training. The present model attempts to quantify theories attributing spontaneous recovery to changes in temporal context.
Journal of the Experimental Analysis of Behavior, 2018 · doi:10.1002/jeab.307