Literature DB >> 19048450

Generality of the summation effect in human causal learning.

Fabian A Soto1, Edgar H Vogel, Ramón D Castillo, Allan R Wagner.   

Abstract

Considerable research has examined the contrasting predictions of the elemental and configural association theories proposed by Rescorla and Wagner (1972) and Pearce (1987), respectively. One simple method to distinguish between these approaches is the summation test, in which the associative strength attributed to a novel compound of two separately trained cues is examined. Under common assumptions, the configural view predicts that the strength of the compound will approximate to the average strength of its components, whereas the elemental approach predicts that the strength of the compound will be greater than the strength of either component. Different studies have produced mixed outcomes. In studies of human causal learning, Collins and Shanks (2006) suggested that the observation of summation is encouraged by training, in which different stimuli are associated with different submaximal outcomes, and by testing, in which the alternative outcomes can be scaled. The reported experiments further pursued this reasoning. In Experiment 1, summation was more substantial when the participants were trained with outcomes identified as submaximal than when trained with simple categorical (presence/absence) outcomes. Experiments 2 and 3 demonstrated that summation can also be obtained with categorical outcomes during training, if the participants are encouraged by instruction or the character of training to rate the separately trained components with submaximal ratings. The results are interpreted in terms of apparent performance constraints in evaluations of the contrasting theoretical predictions concerning summation.

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Year:  2008        PMID: 19048450     DOI: 10.1080/17470210802373688

Source DB:  PubMed          Journal:  Q J Exp Psychol (Hove)        ISSN: 1747-0218            Impact factor:   2.143


  5 in total

1.  Subsampling of cues in associative learning.

Authors:  Omar D Perez; Edgar H Vogel; Sanjay Narasiwodeyar; Fabian A Soto
Journal:  Learn Mem       Date:  2022-06-16       Impact factor: 2.699

2.  Explaining compound generalization in associative and causal learning through rational principles of dimensional generalization.

Authors:  Fabian A Soto; Samuel J Gershman; Yael Niv
Journal:  Psychol Rev       Date:  2014-07       Impact factor: 8.934

3.  Mechanisms of object recognition: what we have learned from pigeons.

Authors:  Fabian A Soto; Edward A Wasserman
Journal:  Front Neural Circuits       Date:  2014-10-13       Impact factor: 3.492

4.  Two heads are better than one, but how much? Evidence that people's use of causal integration rules does not always conform to normative standards.

Authors:  Miguel A Vadillo; Nerea Ortega-Castro; Itxaso Barberia; A G Baker
Journal:  Exp Psychol       Date:  2014

5.  Three Ways That Non-associative Knowledge May Affect Associative Learning Processes.

Authors:  Anna Thorwart; Evan J Livesey
Journal:  Front Psychol       Date:  2016-12-27
  5 in total

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