In resurgence, an operant behavior that has undergone extinction can return (“resurge”) when a second operant that has replaced it itself undergoes extinction. The phenomenon may provide insight into relapse that may occur after incentive or contingency management therapies in humans. Three experiments with rats examined the impact of several variables on the strength of the resurgence effect. In each, pressing one lever (L1) was first reinforced and then extinguished while pressing a second, alternative, lever (L2) was now reinforced. When L2 responding was then itself extinguished, L1 responses resurged. Experiment 1 found that resurgence was especially strong after an extensive amount of L1 training (12 as opposed to 4 training sessions) and after L1 was reinforced on a random ratio schedule as opposed to a variable interval schedule that was matched on reinforcement rate. Experiment 2 found that after 12 initial sessions of L1 training, 4, 12, or 36 sessions of Phase 2 each allowed substantial (and apparently equivalent) resurgence. Experiment 3 found no effect of changing the identity of the reinforcer (from grain pellet to sucrose pellet or sucrose to grain) on the amount of resurgence. The results suggest that resurgence can be robust; in the natural world, an operant behavior with an extensive reinforcement history may still resurge after extensive incentive-based therapy. The results are discussed in terms of current explanations of the resurgence effect.
In two predictive-learning experiments, we investigated the role of the informational value of contexts for the formation of context-dependent behavior. During Phase 1 of each experiment, participants received either a conditional discrimination in which contexts were relevant (Group Relevant) or a simple discrimination in which contexts were irrelevant (Group Irrelevant). Each experiment also included an ABA renewal procedure. Participants received Z+ in context A during Phase 1, extinction of Z in context B during Phase 2, and were tested with Z in context A during a test phase. In each experiment, extinction of Z proceeded faster and was followed by stronger response recovery in Group Relevant than in Group Irrelevant. In Experiment 2, which included recording of eye-gaze behavior, dwell times on contexts were longer in Group Relevant than in Group Irrelevant. Our results support the idea that relevant contexts receive more attention, leading to stronger context specificity of learning.
In two predictive-learning experiments, we investigated the role of the informational value of contexts for the formation of context-specific extinction learning. The contexts were each composed of two elements from two dimensions, A and B. In Phase 1 of each experiment, participants received acquisition training with a target cue Z in context A1B1 (the numbers assign particular values on the context dimensions). In Phase 2, participants were trained with conditional discriminations between two other cues, X and Y, for which only one of the two context dimensions was relevant. In a third phase, participants received extinction trials with cue Z in context A2B2. During a final test phase, we observed that a partial change of the extinction context disrupted extinction performance when the extinction context was changed on the dimension that had been trained as being relevant for the conditional discrimination. However, when the extinction context was changed on the irrelevant context dimension, extinction performance was not affected. Our results are consistent with the idea that relevant contexts receive more attention than do irrelevant contexts, leading to stronger context-specific processing of information learned in the former than in the latter type of contexts.
According to the attentional theory of context processing (ATCP), learning becomes context specific when acquired under conditions that promote attention toward contextual stimuli regardless of whether attention deployment is guided by learning experience or by other factors unrelated to learning. In one experiment with humans, we investigated whether performance in a predictive learning task can be brought under contextual control by means of a secondary task that was unrelated to predictive learning, but supposed to modulate participants' attention toward contexts. Initially, participants acquired cue-outcome relationships presented in contexts that were each composed of two elements from two dimensions. Acquisition training in the predictive learning task was combined with a one-back task that required participants to match across consecutive trials context elements belonging to one of the two dimensions. During a subsequent test, we observed that acquisition behavior in the predictive learning task was disrupted by changing the acquisition context along the dimension that was relevant for the one-back task, while there was no evidence for context specificity of predictive learning when the acquisition context was changed along the dimension that was irrelevant for the one-back task. Our results support the generality of the principles advocated by ATCP.
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