Renewal effects in interference between outcomes as measured by a cued response reaction time task: Further evidence for associative retrieval models.

Cobos, Pedro L.; González-Martín, Estrella; Varona-Moya, Sergio; López, Francisco J.

doi:10.1037/a0033528

Cited by 7 publications

(9 citation statements)

References 23 publications

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“…It has been documented in rats using conditioned suppression (e.g., Bouton & Bolles, 1979), operant conditioning (e.g., Bouton, Todd, Vurbic, & Winterbauer, 2011), taste aversion (e.g., Rosas & Bouton, 1998), magazine training (e.g., Peck, 1989), andchaining (e.g., Thairkill &Bouton, 2017). Renewal has been reported with spatial learning in mice (e.g., Lattal, Mullen, & Abel, 2003), pigeon autoshaping (e.g., Rescorla, 2008), and with a variety of different tasks and procedures in human beings -i.e., predictive learning (e.g., Üngör & Lachnit, 2008;Rosas, García-Gutiérrez, & Callejas-Aguilera, 2006), conditioned suppression (e.g., Nelson, Sanjuan, Vadillo-Ruiz, Perez, & León, 2011;Neumann, 2006), fear conditioning (e.g., Effting & Kindt, 2007), causal learning (e.g., , eye-blink conditioning (e.g., Grillon, Alvarez, Johnson & Chavis, 2008), skin conductance conditioning (e.g., Vervliet, Vansteenwegen, Baeyens, Hermans, & Eelen, 2005) and associative learning evaluated by reaction time (e.g., Cobos, González-Martín, Varona-Moya, & López, 2013).…”

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confidence: 99%

Context dependency as a Function of Prediction Error-Based Attention

Rosas

Nelson

2019

Psicológica Journal

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Context dependence of information has been shown to be based, at least in part, on the attention contexts received at the time of training. Recent research suggests that attention to irrelevant contexts may be a byproduct of the activation of a general exploratory attentional mechanism prompted by high prediction errors associated with situations of uncertainty. Alternatively, low prediction errors may engage an attentional mechanism of exploitation in situations in which contexts play a relevant role. A selective review discusses the potential of this approach to explain context switch effects from an attentional perspective.

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confidence: 99%

Context dependency as a Function of Prediction Error-Based Attention

Rosas

Nelson

2019

Psicológica Journal

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“…For instance, strong responding can reappear if the CS is presented in a new context. This "renewal" of conditioned responding has been extensively replicated over species and experimental paradigms (e.g., Bouton and Bolles 1979;Bouton and King 1983) and has been the object of substantial research in human learning (e.g., Rosas et al 2001;Vadillo et al 2004;Nelson et al 2011b;Cobos et al 2013).…”

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confidence: 99%

Ambiguity produces attention shifts in category learning

et al. 2016

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It has been suggested that people and nonhuman animals protect their knowledge from interference by shifting attention toward the context when presented with information that contradicts their previous beliefs. Despite that suggestion, no studies have directly measured changes in attention while participants are exposed to an interference treatment. In the present experiments, we adapted a dot-probe task to track participants' attention to cues and contexts while they were completing a simple category learning task. The results support the hypothesis that interference produces a change in the allocation of attention to cues and contexts.

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“…It is unlikely that these findings could be attributed to their use of stricter time-pressure conditions than those used in our procedure. In particular, it should be noted that the time pressure used in our task—a SOA of 250 ms.—is similar to that used in those studies showing evidence in favor of a dual-process account (ranging from 200 to 350 ms.; [8, 14, 31, 32]). In other words, a SOA that was able to preclude a fast retrieval of propositional knowledge to control performance in these experiments, revealed dissociative results.…”

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confidence: 99%

Rapid Top-Down Control of Behavior Due to Propositional Knowledge in Human Associative Learning

2016

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Propositional and associative processes have been proposed to explain human associative learning. Our main objective in this study was to evaluate whether propositional knowledge may gain control over behavior even under high time-pressure conditions, as suggested by propositional single-process models. In the experiment reported, different groups of participants had to learn a series of cue-outcome relationships on a trial-by-trial basis under different time pressure conditions. Later, a simple verbal instruction indicated that one of the cues had reversed its contingency (informed condition). The other cue had also changed its contingency, though in an unanticipated way (uninformed condition) whilst other contingencies did not change (no-change condition). The results showed that, in the absence of instructions, interference (i.e., uninformed vs. no-change effect) was greater in the high time than in the low time-pressure group. This result indicates that those responses which were previously relevant are more difficult to inhibit when there is little time to respond. However, time pressure had no detectable effect on the use of the verbal instruction, since an equivalent instruction advantage (i.e., uninformed vs. informed effect) was obtained in both time pressure groups. These results reveal that propositional knowledge can override those cue-outcome relationships that were learnt trial-by-trial even under conditions of high cognitive demand. This pattern of results is consistent with a propositional single-process model of associative learning.

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Renewal effects in interference between outcomes as measured by a cued response reaction time task: Further evidence for associative retrieval models.

Cited by 7 publications

References 23 publications

Context dependency as a Function of Prediction Error-Based Attention

Context dependency as a Function of Prediction Error-Based Attention

Ambiguity produces attention shifts in category learning

Rapid Top-Down Control of Behavior Due to Propositional Knowledge in Human Associative Learning

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