Effects of orientation and differential reinforcement II: transitivity and transfer across five-member sets

Amd, Micah; Oliveira, Marlon Alexandre de; Passarelli, Denise Aparecida; Balog, Livia C.; Rose, Júlio C. de

doi:10.1016/j.beproc.2018.02.012

Cited by 13 publications

(20 citation statements)

References 52 publications

(78 reference statements)

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“…Meaningless symbols can become emotionally salient following correlations with emotion-eliciting events (US) under controlled conditions (Staats and Staats, 1957; Mowrer, 1960; Osgood, 1980). For example, correlating nonsense words with pictures of happy faces (US) can transform the former into a positively valenced Conditioned Stimulus, or CS (Amd et al., 2018). CS valence transformations are not limited to CS that directly appeared with US only; in natural language, it is more often the case that words acquire valence following contextually mediated relations with other, valenced CS (Staats, 1961; Dymond and Rehfeldt, 2000; Tonneau, 2004; Amd et al., 2018).…”

Section: Introductionmentioning

confidence: 99%

“…For example, correlating nonsense words with pictures of happy faces (US) can transform the former into a positively valenced Conditioned Stimulus, or CS (Amd et al., 2018). CS valence transformations are not limited to CS that directly appeared with US only; in natural language, it is more often the case that words acquire valence following contextually mediated relations with other, valenced CS (Staats, 1961; Dymond and Rehfeldt, 2000; Tonneau, 2004; Amd et al., 2018). To see how, imagine the CS from the above example (call it CS0) was linked with a second term (call it CS1) in a context that promotes functionally equivalent stimulus relations/links (Tonneau, 2001).…”

Section: Introductionmentioning

confidence: 99%

“…Next, suppose our CS is paired with another nonsense word; call this CS0-CS1. To describe how “far” each CS is from its linked US, we say that CS0 and CS1 are 0 and 1 nodes from the US, respectively (e.g., Amd et al., 2018). Observing valence transformations for CS1 is an instance of indirect, 1-node transformation.…”

Section: Introductionmentioning

confidence: 99%

“…We know that when CS and US categories consist of nonsense words and emotional faces respectively, valence transformations appear limited by nodal distance. Specifically, valences for CS that are two or more nodes away from their face US may not significantly transform (Bortoloti and de Rose, 2009; Amd et al., 2018; Silveira et al., 2018). A recent study by Amd et al.…”

Section: Introductionmentioning

confidence: 99%

“…Briefly, “extinction” describes how repeated presentations of a CS alone in a context where it had previously been associated with a US may cause the CS valences to trend toward their pre-conditioning state. We replicated Amd et al. (2018) procedure for establishing three 5-member stimulus sets that varied along valence (positive/happy, neutral, negative/sad).…”

Section: Introductionmentioning

confidence: 99%

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Effects of Nodal Distance on Conditioned Stimulus Valences Across Time

et al. 2019

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A meaningless symbol that repeatedly co-occurs with emotionally salient faces (US) can transform into a valenced symbol (CS). US-to-CS valence transformations have been observed for CS that have been directly ( US → CS0 ) and indirectly ( US →CS0→ CS1 → CS2 ) linked with face US. The structure of a US→CS0→CS1→CS2 series may be conceptualized in terms of “nodal distance,” where CS0, CS1, and CS2 are 0, 1, and 2 nodes from the US respectively. Increasing nodal distance between an evaluated CS and its linked US can reduce magnitude of observed CS valence transformations. We explored currently whether nodal distance can influence CS valence extinction , which describes reductions in CS valence following repeated exposures to CS without any accompanying US. In our study, faces with happy/neutral/sad expressions (US) were directly linked with nonsense words (US→CS0). The directly linked CS0 was concurrently linked with other words (CS0→CS1, CS1→CS2). Subjects evaluated all stimuli before and after conditioning, then continued to provide CS evaluations twice a week for 6 weeks. Bayesian factors provided credible evidence for the transformation and extinction of CS valences that were 0 and 1 nodes from US (all BF 10 ’s > 100). The variability across post-conditioning CS evaluations provides indirect evidence for context-sensitive/propositional and structural/associative operations during CS evaluations.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Effects of Nodal Distance on Conditioned Stimulus Valences Across Time

et al. 2019

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Mediated Generalization and Stimulus Equivalence

Eilifsen

Arntzen

2021

Perspect Behav Sci

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From the 1930s to the 1970s a large number of experimental studies on mediated generalization were published, and this research tradition provided an important context for early research on stimulus equivalence. Mediated generalization and stimulus equivalence have several characteristics in common, notably that both traditions seek to experimentally investigate derived responding among arbitrarily related stimuli in human participants. Although studies of stimulus equivalence are currently being regularly published, few studies investigate mediated generalization in humans today, and the research tradition is mainly of historical interest. The current article will give an account of the origin, the development, and the demise of research on mediated generalization, including a presentation of publication trends, experimental methodology, and the conceptual context research on mediated generalization took place within. Finally, some thoughts on the demise of mediated generalization and its relevance for modern research on stimulus equivalence and other types of derived responding are presented, including reflections on the observability of explanatory variables and the use of inferential statistics.

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