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Adaptable history biases in human perceptual decisions

Abrahamyan, A; Silva, LL; Dakin, SC; Carandini, M; Gardner, JL; (2016) Adaptable history biases in human perceptual decisions. Proceedings of the National Academy of Sciences of the United States of America , 113 (25) E3548-E3557. 10.1073/pnas.1518786113. Green open access

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Abstract

When making choices under conditions of perceptual uncertainty, past experience can play a vital role. However, it can also lead to biases that worsen decisions. Consistent with previous observations, we found that human choices are influenced by the success or failure of past choices even in a standard two-alternative detection task, where choice history is irrelevant. The typical bias was one that made the subject switch choices after a failure. These choice history biases led to poorer performance and were similar for observers in different countries. They were well captured by a simple logistic regression model that had been previously applied to describe psychophysical performance in mice. Such irrational biases seem at odds with the principles of reinforcement learning, which would predict exquisite adaptability to choice history. We therefore asked whether subjects could adapt their irrational biases following changes in trial order statistics. Adaptability was strong in the direction that confirmed a subject's default biases, but weaker in the opposite direction, so that existing biases could not be eradicated. We conclude that humans can adapt choice history biases, but cannot easily overcome existing biases even if irrational in the current context: adaptation is more sensitive to confirmatory than contradictory statistics.

Type: Article
Title: Adaptable history biases in human perceptual decisions
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1073/pnas.1518786113
Publisher version: http://dx.doi.org/10.1073/pnas.1518786113
Language: English
Additional information: Copyright © 2016 National Academy of Sciences. This is the accepted manuscript version of this article; the final published version can be found on the PNAS website at http://www.pnas.org/content/113/25/E3548
Keywords: bias adaptation, choice bias, choice history, computational modeling, decision making
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Institute of Ophthalmology
URI: https://discovery.ucl.ac.uk/id/eprint/1495870
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