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The relation between persistence, as measured by resistance to change, and resurgence has been examined with nonhuman animals but not systematically with humans. The present study examined persistence and resurgence with undergraduate students engaging in a computer task for points exchangeable for money. In Phase 1, a target response was maintained on a multiple variable-interval (VI) 15-s (Rich) VI 60-s (Lean) schedule of reinforcement. In Phase 2, the target response was extinguished while an alternative response was reinforced at equal rates in both schedule components. In Phase 3, the target and the alternative responses were extinguished. In an additional test of persistence (Phase 4), target responding was reestablished as in Phase 1 and then disrupted by access to videos in both schedule components. In Phases 2 and 4, target responding was more persistent in the Rich than in the Lean component. Also, resurgence generally was greater in the Rich than in the Lean component in Phase 3. The present findings with humans extend the generality of those obtained with nonhuman animals showing that higher reinforcement rates produce both greater persistence and resurgence, and suggest that common processes underlie response persistence and relapse. [ABSTRACT FROM AUTHOR]

Resurgence occurs when a previously reinforced and then extinguished target response increases due to a worsening of reinforcement conditions for an alternative response. We conducted four crowdsourcing experiments to evaluate effects of alternative-reinforcer rate and magnitude on resurgence with humans. Contingent on an alternative response, we manipulated across groups either the rate of point delivery (Experiment 1) or number of points delivered per reinforcer (Experiments 2–3). Experiment 4 arranged combinations of high- or low-rate and high- or low-magnitude alternative reinforcement across four groups. When extinguishing alternative responding across experiments, we observed resurgence of target responding with relatively high rates of alternative reinforcement but differences in reinforcer magnitude did not influence resurgence. A quantitative model based on the concatenated matching law, Resurgence as Choice in Context (RaC2), provided a poor fit to the data, generally underpredicted target responding, and could not account for data from control groups experiencing extinction of target responding in the absence of alternative reinforcement. We then fit a modified version of RaC2 borrowing an assumption from theories of choice that suggest some proportion of reinforcers are misallocated between responses – this modified version of RaC2 provided a better account of these findings. • Examined effects of reinforcer rate and magnitude on resurgence through crowdsourcing. • In four experiments, greater reinforcer rates but not magnitudes increased resurgence. • We fit a quantitative model based on matching, Resurgence as Choice in Context (RaC2). • RaC2 fits improved when assuming reinforcers are misallocated between responses. • Misallocation also allowed RaC2 to be fit for the first time to simple extinction data. [ABSTRACT FROM AUTHOR]