Optimism as a prior belief about the probability of future reward. Stankevicius, A., Huys, Q. J M., Kalra, A., & Seriès, P. PLoS Comput Biol, 10(5):e1003605, 2014. Publisher: Institute for Adaptive and Neural Computation, University of Edinburgh, Edinburgh, United Kingdom.![Optimism as a prior belief about the probability of future reward. [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Optimists hold positive a priori beliefs about the future. In Bayesian statistical theory, a priori beliefs can be overcome by experience. However, optimistic beliefs can at times appear surprisingly resistant to evidence, suggesting that optimism might also influence how new information is selected and learned. Here, we use a novel Pavlovian conditioning task, embedded in a normative framework, to directly assess how trait optimism, as classically measured using self-report questionnaires, influences choices between visual targets, by learning about their association with reward progresses. We find that trait optimism relates to an a priori belief about the likelihood of rewards, but not losses, in our task. Critically, this positive belief behaves like a probabilistic prior, i.e. its influence reduces with increasing experience. Contrary to findings in the literature related to unrealistic optimism and self-beliefs, it does not appear to influence the iterative learning process directly.
@article{stankevicius_optimism_2014,
title = {Optimism as a prior belief about the probability of future reward.},
volume = {10},
url = {http://dx.doi.org/10.1371/journal.pcbi.1003605},
doi = {10.1371/journal.pcbi.1003605},
abstract = {Optimists hold positive a priori beliefs about the future. In Bayesian statistical theory, a priori beliefs can be overcome by experience. However, optimistic beliefs can at times appear surprisingly resistant to evidence, suggesting that optimism might also influence how new information is selected and learned. Here, we use a novel Pavlovian conditioning task, embedded in a normative framework, to directly assess how trait optimism, as classically measured using self-report questionnaires, influences choices between visual targets, by learning about their association with reward progresses. We find that trait optimism relates to an a priori belief about the likelihood of rewards, but not losses, in our task. Critically, this positive belief behaves like a probabilistic prior, i.e. its influence reduces with increasing experience. Contrary to findings in the literature related to unrealistic optimism and self-beliefs, it does not appear to influence the iterative learning process directly.},
language = {eng},
number = {5},
journal = {PLoS Comput Biol},
author = {Stankevicius, Aistis and Huys, Quentin J M. and Kalra, Aditi and Seriès, Peggy},
year = {2014},
pmid = {24853098},
note = {Publisher: Institute for Adaptive and Neural Computation, University of Edinburgh, Edinburgh, United Kingdom.},
pages = {e1003605},
}
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