The hide-and-seek of retrospective revaluation: Recovery from blocking is context dependent in human causal learning.

2011 ◽  
Vol 37 (2) ◽  
pp. 230-240 ◽  
Author(s):  
Yannick Boddez ◽  
Frank Baeyens ◽  
Dirk Hermans ◽  
Tom Beckers
Keyword(s):  
Causal Learning ◽  
Retrospective Revaluation ◽  
Human Causal Learning ◽  
Context Dependent

The Comparator Theory Fails to Account for the Selective Role of Within-Compound Associations in Cue-Selection Effects

2006 ◽  
Vol 53 (4) ◽  
pp. 316-320 ◽  
Author(s):  
Klaus G. Melchers ◽  
Harald Lachnit ◽  
David R. Shanks
Keyword(s):  
Selection Effect ◽  
Causal Learning ◽  
Selection Effects ◽  
Retrospective Revaluation ◽  
Associative Theory ◽  
Human Causal Learning ◽  
Equal Importance ◽  
Cue Selection ◽  
Learning Trials

In a human causal learning experiment, we investigated cue selection effects to test the comparator theory ( Denniston, Savastano, & Miller, 2001 ; Miller & Matzel, 1988 ). The theory predicts that the occurrence of cue selection is independent of whether the relevant learning trials are presented in a standard forward manner or in a backward manner and that within-compound associations are of equal importance in both cases. We found that the strength of the cue-selection effect was positively correlated with knowledge of within-compound associations in the backward condition but not in the forward condition. Furthermore, cue-selection effects were less pronounced in the former than in the latter condition. These results are at variance with the comparator hypothesis but are in agreement with a modified associative theory and with the suggestion that retrospective revaluation might be due to rehearsal processes.

Higher-Order Retrospective Revaluation in Human Causal Learning

2002 ◽  
Vol 55 (2b) ◽  
pp. 137-151 ◽  
Author(s):  
Jan De Houwer ◽  
Tom Beckers
Keyword(s):  
Higher Order ◽  
Second Order ◽  
Causal Learning ◽  
Retrospective Revaluation ◽  
Wagner Model ◽  
Third Order ◽  
Contrast Model ◽  
Human Causal Learning ◽  
Causal Status ◽  
Comparator Model

Previous studies demonstrated that participants will retrospectively adjust their ratings about the relation between a target cue and an outcome on the basis of information about the causal status of a competing cue that was previously paired with the target cue. We demonstrate that such retrospective revaluation effects occur not only for target cues with which the competing cue was associated directly, but also for target cues that were associated indirectly with the competing cue. These second-order and third-order retrospective revaluation effects are compatible with certain implementations of the probabilistic contrast model and with a modified, extended comparator model, but cannot be explained on the basis of a revised Rescorla—Wagner model or a revised SOP model.

Second-Order Backward Blocking and Unovershadowing in Human Causal Learning

2002 ◽  
Vol 49 (1) ◽  
pp. 27-33 ◽  
Author(s):  
Jan De Houwer ◽  
Tom Beckers
Keyword(s):  
Higher Order ◽  
Second Order ◽  
Causal Learning ◽  
First Order ◽  
Human Causal Learning ◽  
Before And After ◽  
Causal Status

Abstract. De Houwer and Beckers (in press , Experiment 1) recently demonstrated that ratings about the relation between a target cue T2 and an outcome are higher when training involves CT1+ and T1T2+ followed by C+ trials than when training involves CT1+ and T1T2+ followed by C- trials. We replicated this study but now explicitly asked participants to rate the causal status of the cues both before and after the C+ or C- trials. Results showed that causal ratings for T2 were significantly higher after C+ trials than before C+ trials and that T2 received significantly lower ratings after C- trials than before C- trials. The results thus provide the first evidence for higher-order unovershadowing and higher-order backward blocking. In addition, the ratings for T1 revealed that first-order backward blocking (i.e., decrease in ratings for T1 as the result of C+ trials) was stronger than first-order unovershadowing (i.e., increase in ratings for T1 as the result of C- trials).

Comparing elemental and configural associative theories in human causal learning: A case for attention.

2008 ◽  
Vol 34 (2) ◽  
pp. 303-313 ◽  
Author(s):  
Harald Lachnit ◽  
Holger Schultheis ◽  
Stephan König ◽  
Metin Üngör ◽  
Klaus Melchers
Keyword(s):  
Causal Learning ◽  
Human Causal Learning

Changes in cue associability across training in human causal learning.

2008 ◽  
Vol 34 (4) ◽  
pp. 423-436
Author(s):  
Chris J. Mitchell ◽  
Justin A. Harris ◽  
R. Frederick Westbrook ◽  
Oren Griffiths
Keyword(s):  
Causal Learning ◽  
Human Causal Learning

scholarly journals Prior beliefs influence symmetrical or asymmetrical generalizations in human causal learning

2017 ◽  
Vol 45 (3) ◽  
pp. 300-312
Author(s):  
Ryoji Nishiyama ◽  
Takatoshi Nagaishi ◽  
Takahisa Masaki
Keyword(s):  
Causal Learning ◽  
Prior Beliefs ◽  
Human Causal Learning
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