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Approach-Induced Biases in Human Information Sampling

Hunt, LT; Rutledge, RB; Malalasekera, WM; Kennerley, SW; Dolan, RJ; (2016) Approach-Induced Biases in Human Information Sampling. PLoS Biology , 14 (11) , Article e2000638. 10.1371/journal.pbio.2000638. Green open access

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Abstract

Information sampling is often biased towards seeking evidence that confirms one's prior beliefs. Despite such biases being a pervasive feature of human behavior, their underlying causes remain unclear. Many accounts of these biases appeal to limitations of human hypothesis testing and cognition, de facto evoking notions of bounded rationality, but neglect more basic aspects of behavioral control. Here, we investigated a potential role for Pavlovian approach in biasing which information humans will choose to sample. We collected a large novel dataset from 32,445 human subjects, making over 3 million decisions, who played a gambling task designed to measure the latent causes and extent of information-sampling biases. We identified three novel approach-related biases, formalized by comparing subject behavior to a dynamic programming model of optimal information gathering. These biases reflected the amount of information sampled ("positive evidence approach"), the selection of which information to sample ("sampling the favorite"), and the interaction between information sampling and subsequent choices ("rejecting unsampled options"). The prevalence of all three biases was related to a Pavlovian approach-avoid parameter quantified within an entirely independent economic decision task. Our large dataset also revealed that individual differences in the amount of information gathered are a stable trait across multiple gameplays and can be related to demographic measures, including age and educational attainment. As well as revealing limitations in cognitive processing, our findings suggest information sampling biases reflect the expression of primitive, yet potentially ecologically adaptive, behavioral repertoires. One such behavior is sampling from options that will eventually be chosen, even when other sources of information are more pertinent for guiding future action.

Type: Article
Title: Approach-Induced Biases in Human Information Sampling
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1371/journal.pbio.2000638
Publisher version: http://dx.doi.org/10.1371/journal.pbio.2000638
Language: English
Additional information: Copyright © 2016 Hunt et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. - Please note: a correction to the title of figure 2 has been published in vol. 15(11), e1002618; https://doi.org/10.1371/journal.pbio.1002618.
UCL classification: UCL > Provost and Vice Provost Offices
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 > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Clinical and Movement Neurosciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience
URI: https://discovery.ucl.ac.uk/id/eprint/1529116
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