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  Internality and the internalisation of failure: Evidence from a novel task

Mancinelli, F., Roiser, J., & Dayan, P. (2021). Internality and the internalisation of failure: Evidence from a novel task. PLoS Computational Biology, 17(7), 1-25. doi:10.1371/journal.pcbi.1009134.

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Mancinelli, F, Author
Roiser, J, Author
Dayan, P1, 2, Author           
Affiliations:
1Department of Computational Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_3017468              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: A critical facet of adjusting one's behaviour after succeeding or failing at a task is assigning responsibility for the ultimate outcome. Humans have trait- and state-like tendencies to implicate aspects of their own behaviour (called 'internal' ascriptions) or facets of the particular task or Lady Luck ('chance'). However, how these tendencies interact with actual performance is unclear. We designed a novel task in which subjects had to learn the likelihood of achieving their goals, and the extent to which this depended on their efforts. High internality (Levenson I-score) was associated with decision making patterns that are less vulnerable to failure. Our computational analyses suggested that this depended heavily on the adjustment in the perceived achievability of riskier goals following failure. We found beliefs about chance not to be explanatory of choice behaviour in our task. Beliefs about powerful others were strong predictors of behaviour, but only when subjects lacked substantial influence over the outcome. Our results provide an evidentiary basis for heuristics and learning differences that underlie the formation and maintenance of control expectations by the self.

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 Dates: 2021-07
 Publication Status: Published online
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 Identifiers: DOI: 10.1371/journal.pcbi.1009134
eDoc: e1009134
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Title: PLoS Computational Biology
Source Genre: Journal
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Publ. Info: San Francisco, CA : Public Library of Science
Pages: - Volume / Issue: 17 (7) Sequence Number: - Start / End Page: 1 - 25 Identifier: ISSN: 1553-734X
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000017180_1