DOCUMENTS

  TITLE AUTHOR INSTITUTION DATE ABSTRACT DOWNLOAD
Kick-off Beckers 1 Tom Beckers KUL 2013 02  
Kick-off Beckers 2 Tom Beckers KUL 2013 02  
COOL2 WP2 Update Tom Beckers KUL 2013 11  
Selectivity in associative learning: A cognitive stage framework for blocking and cue competition phenomena Tom Beckers KUL 2014 10

Blocking is the most important phenomenon in the history of associative learning theory: For over 40 years, blocking has inspired a whole generation of learning models. Blocking is part of a family of effects that are typically termed “cue competition” effects. Common amongst all cue competition effects is that a cue-outcome relation is poorly learned or poorly expressed because the cue is trained in the presence of an alternative predictor or cause of the outcome. We provide an overview of the cognitive processes involved in cue competition effects in humans and propose a stage framework that brings these processes together. The framework contends that the behavioral display of cue competition is cognitively construed following three stages that include (1) an encoding stage, (2) a retention stage, and (3) a performance stage. We argue that the stage framework supports a comprehensive understanding of cue competition effects.

Program 3rd COOL meeting Tom Beckers KUL 2014 11  
738kb
Luyten L., Boddez Y., Hermans D. (2015). Positive appraisal style: the mental immune system?. Behavioral and Brain Sciences, 38, art.nr. e112. Yannick Boddez KUL 2015 02  
536kb
Van Lier J., Vervliet B., Boddez Y., Raes F. (2014). “Why is everyone always angry with me?!”: When thinking ‘why’ leads to generalization. Journal of Behavior Therapy and Experimental Psychiatry, 47, 34-41. Yannick Boddez KUL 2015 02  
Feature- versus rule-based generalization in rats, pigeons and humans. Tom Beckers KUL 2015 07
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Maes, E., De Filippo, G., Inkster, A., Lea, S. E. G., De Houwer, J., D'Hooge, R., Beckers, T., & Wills, A. J. (in press). Feature- versus rule-based generalization in rats, pigeons and humans. Animal Cognition.

Abstract:
Humans can spontaneously create rules that allow them to efficiently generalize what they have learned to novel situations. An enduring question is whether rule-based generalization is uniquely human or whether other animals can also abstract rules and apply them to novel situations. In recent years, there have been a number of high-profile claims that animals such as rats can learn rules. Most of those claims are quite weak because it is possible to demonstrate that simple associative systems (which do not learn rules) can account for the behavior in those tasks. Using a procedure that allows us to clearly distinguish feature-based from rule-based generalization (the Shanks-Darby procedure), we demonstrate that adult humans show rule-based generalization in this task, while generalization in rats and pigeons was based on featural overlap between stimuli. In brief, when learning that a stimulus made of two components (“AB”) predicts a different outcome than its elements (“A” and “B”), people spontaneously abstract an opposites rule and apply it to new stimuli (e.g. knowing that “C” and “D” predict one outcome, they will predict that “CD” predicts the opposite outcome). Rats and pigeons show the reverse behavior – they generalize what they have learned, but on the basis of similarity (e.g. “CD” is similar to “C” and “D”, so the same outcome is predicted for the compound stimulus as for the components). Genuinely rule-based behavior is observed in humans, but not in rats and pigeons, in the current procedure.

Vanbrabant K., Boddez Y., Verduyn P., Mestdagh M., Hermans D., Raes F. (2015). A new approach for modeling generalization gradients: A case for hierarchical models. Frontiers in Psychology, 6, art.nr. 652, 1-10. Yannick Boddez KUL 2015 12  
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Bennett M., Vervoort E., Boddez Y., Hermans D., Baeyens F. (2015). Perceptual and conceptual similarities facilitate the generalisation of instructed fear. Journal of Behavior Therapy and Experimental Psychiatry, 48, 149-155. Yannick Boddez KUL 2015 12  
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Boddez Y., De Houwer J., Beckers T. (2017). The inferential reasoning theory of causal learning: Towards a multi-process propositional account. In: Waldmann M. (Eds.), The Oxford Handbook of Causal Reasoning, Chapt. 4, (pp. 1-22). Oxford: Oxford University Press. Yannick Boddez KUL 2015 12  
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Takano K., Boddez Y., Raes F. (2016). I sleep with my Mind’s eye open: Cognitive arousal and overgeneralization underpin the misperception of sleep. Journal of Behavior Therapy and Experimental Psychiatry, 52, 157-165. Yannick Boddez KUL 2018 04  
Scheveneels S., Boddez Y., Vervliet B., Hermans D. (2016). The validity of laboratory-based treatment research: Bridging the gap between fear extinction and exposure treatment. Behaviour Research and Therapy, 86, 87-94. Yannick Boddez KUL 2018 04  
Moors A., Boddez Y. (2017). Author reply: Emotional episodes are action episodes. Emotion Review, 9 (4), 353-354. Yannick Boddez KUL 2018 04  
Boddez Y., Bennett M., van Esch S., Beckers T. (2017). Bending rules: The shape of the perceptual generalization gradient is sensitive to inference rules. Cognition & Emotion, 31, 1444-1452. Yannick Boddez KUL 2018 04  

COOL

Mechanisms of conscious and unconscious learning

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