Human noise blindness drives suboptimal cognitive inference

Humans typically make near-optimal sensorimotor judgements but show systematic biases when making more cognitive judgements. Here we test the hypothesis that, while humans are sensitive to the noise present during early sensory encoding, the "optimality gap" arises because they are blind t...

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Main Authors: Herce Castañón, S, Moran, R, Ding, J, Egner, T, Bang, D, Summerfield, C
Format: Journal article
Language:English
Published: Springer Nature 2019
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author Herce Castañón, S
Moran, R
Ding, J
Egner, T
Bang, D
Summerfield, C
author_facet Herce Castañón, S
Moran, R
Ding, J
Egner, T
Bang, D
Summerfield, C
author_sort Herce Castañón, S
collection OXFORD
description Humans typically make near-optimal sensorimotor judgements but show systematic biases when making more cognitive judgements. Here we test the hypothesis that, while humans are sensitive to the noise present during early sensory encoding, the "optimality gap" arises because they are blind to noise introduced by later cognitive integration of variable or discordant pieces of information. In six psychophysical experiments, human observers judged the average orientation of an array of contrast gratings. We varied the stimulus contrast (encoding noise) and orientation variability (integration noise) of the array. Participants adapted near-optimally to changes in encoding noise, but, under increased integration noise, displayed a range of suboptimal behaviours: they ignored stimulus base rates, reported excessive confidence in their choices, and refrained from opting out of objectively difficult trials. These overconfident behaviours were captured by a Bayesian model blind to integration noise. Our study provides a computationally grounded explanation of human suboptimal cognitive inference.
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spelling oxford-uuid:4b548e32-69e6-49d0-bd00-8fffae9602b12022-03-26T15:42:58ZHuman noise blindness drives suboptimal cognitive inferenceJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:4b548e32-69e6-49d0-bd00-8fffae9602b1EnglishSymplectic Elements at OxfordSpringer Nature2019Herce Castañón, SMoran, RDing, JEgner, TBang, DSummerfield, CHumans typically make near-optimal sensorimotor judgements but show systematic biases when making more cognitive judgements. Here we test the hypothesis that, while humans are sensitive to the noise present during early sensory encoding, the "optimality gap" arises because they are blind to noise introduced by later cognitive integration of variable or discordant pieces of information. In six psychophysical experiments, human observers judged the average orientation of an array of contrast gratings. We varied the stimulus contrast (encoding noise) and orientation variability (integration noise) of the array. Participants adapted near-optimally to changes in encoding noise, but, under increased integration noise, displayed a range of suboptimal behaviours: they ignored stimulus base rates, reported excessive confidence in their choices, and refrained from opting out of objectively difficult trials. These overconfident behaviours were captured by a Bayesian model blind to integration noise. Our study provides a computationally grounded explanation of human suboptimal cognitive inference.
spellingShingle Herce Castañón, S
Moran, R
Ding, J
Egner, T
Bang, D
Summerfield, C
Human noise blindness drives suboptimal cognitive inference
title Human noise blindness drives suboptimal cognitive inference
title_full Human noise blindness drives suboptimal cognitive inference
title_fullStr Human noise blindness drives suboptimal cognitive inference
title_full_unstemmed Human noise blindness drives suboptimal cognitive inference
title_short Human noise blindness drives suboptimal cognitive inference
title_sort human noise blindness drives suboptimal cognitive inference
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