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Automatic and Fast Encoding of Representational Uncertainty Underlies the Distortion of Relative Frequency

Humans do not have an accurate representation of probability information in the environment but distort it in a surprisingly stereotyped way (“probability distortion”), as shown in a wide range of judgment and decision-making tasks. Many theories hypothesize that humans automatically compensate for...

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Autores principales: Ren, Xiangjuan, Luo, Huan, Zhang, Hang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society for Neuroscience 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8055084/
https://www.ncbi.nlm.nih.gov/pubmed/33674418
http://dx.doi.org/10.1523/JNEUROSCI.2006-20.2021
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author Ren, Xiangjuan
Luo, Huan
Zhang, Hang
author_facet Ren, Xiangjuan
Luo, Huan
Zhang, Hang
author_sort Ren, Xiangjuan
collection PubMed
description Humans do not have an accurate representation of probability information in the environment but distort it in a surprisingly stereotyped way (“probability distortion”), as shown in a wide range of judgment and decision-making tasks. Many theories hypothesize that humans automatically compensate for the uncertainty inherent in probability information (“representational uncertainty”) and probability distortion is a consequence of uncertainty compensation. Here we examined whether and how the representational uncertainty of probability is quantified in the human brain and its relevance to probability distortion behavior. Human subjects (13 female and 9 male) kept tracking the relative frequency of one color of dot in a sequence of dot arrays while their brain activity was recorded by MEG. We found converging evidence from both neural entrainment and time-resolved decoding analysis that a mathematically derived measure of representational uncertainty is automatically computed in the brain, despite it is not explicitly required by the task. In particular, the encodings of relative frequency and its representational uncertainty, respectively, occur at latencies of ∼300 and 400 ms. The relative strength of the brain responses to these two quantities correlates with the probability distortion behavior. The automatic and fast encoding of the representational uncertainty provides neural basis for the uncertainty compensation hypothesis of probability distortion. More generally, since representational uncertainty is closely related to confidence estimation, our findings exemplify how confidence might emerge before perceptual judgment. SIGNIFICANCE STATEMENT Human perception of probabilities and relative frequencies can be markedly distorted, which is a potential source of disastrous decisions. But the brain is not just ignorant of probability; probability distortions are highly patterned and similar across different tasks. Recent theoretical work suggests that probability distortions arise from the brain's compensation of its own uncertainty in representing probability. Is such representational uncertainty really computed in the brain? To answer this question, we asked human subjects to track an ongoing stimulus sequence of relative frequencies and recorded their brain responses using MEG. Indeed, we found that the neural encoding of representational uncertainty accompanies that of relative frequency, although the former is not explicitly required by the task.
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spelling pubmed-80550842021-04-21 Automatic and Fast Encoding of Representational Uncertainty Underlies the Distortion of Relative Frequency Ren, Xiangjuan Luo, Huan Zhang, Hang J Neurosci Research Articles Humans do not have an accurate representation of probability information in the environment but distort it in a surprisingly stereotyped way (“probability distortion”), as shown in a wide range of judgment and decision-making tasks. Many theories hypothesize that humans automatically compensate for the uncertainty inherent in probability information (“representational uncertainty”) and probability distortion is a consequence of uncertainty compensation. Here we examined whether and how the representational uncertainty of probability is quantified in the human brain and its relevance to probability distortion behavior. Human subjects (13 female and 9 male) kept tracking the relative frequency of one color of dot in a sequence of dot arrays while their brain activity was recorded by MEG. We found converging evidence from both neural entrainment and time-resolved decoding analysis that a mathematically derived measure of representational uncertainty is automatically computed in the brain, despite it is not explicitly required by the task. In particular, the encodings of relative frequency and its representational uncertainty, respectively, occur at latencies of ∼300 and 400 ms. The relative strength of the brain responses to these two quantities correlates with the probability distortion behavior. The automatic and fast encoding of the representational uncertainty provides neural basis for the uncertainty compensation hypothesis of probability distortion. More generally, since representational uncertainty is closely related to confidence estimation, our findings exemplify how confidence might emerge before perceptual judgment. SIGNIFICANCE STATEMENT Human perception of probabilities and relative frequencies can be markedly distorted, which is a potential source of disastrous decisions. But the brain is not just ignorant of probability; probability distortions are highly patterned and similar across different tasks. Recent theoretical work suggests that probability distortions arise from the brain's compensation of its own uncertainty in representing probability. Is such representational uncertainty really computed in the brain? To answer this question, we asked human subjects to track an ongoing stimulus sequence of relative frequencies and recorded their brain responses using MEG. Indeed, we found that the neural encoding of representational uncertainty accompanies that of relative frequency, although the former is not explicitly required by the task. Society for Neuroscience 2021-04-21 /pmc/articles/PMC8055084/ /pubmed/33674418 http://dx.doi.org/10.1523/JNEUROSCI.2006-20.2021 Text en Copyright © 2021 Ren et al. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.
spellingShingle Research Articles
Ren, Xiangjuan
Luo, Huan
Zhang, Hang
Automatic and Fast Encoding of Representational Uncertainty Underlies the Distortion of Relative Frequency
title Automatic and Fast Encoding of Representational Uncertainty Underlies the Distortion of Relative Frequency
title_full Automatic and Fast Encoding of Representational Uncertainty Underlies the Distortion of Relative Frequency
title_fullStr Automatic and Fast Encoding of Representational Uncertainty Underlies the Distortion of Relative Frequency
title_full_unstemmed Automatic and Fast Encoding of Representational Uncertainty Underlies the Distortion of Relative Frequency
title_short Automatic and Fast Encoding of Representational Uncertainty Underlies the Distortion of Relative Frequency
title_sort automatic and fast encoding of representational uncertainty underlies the distortion of relative frequency
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8055084/
https://www.ncbi.nlm.nih.gov/pubmed/33674418
http://dx.doi.org/10.1523/JNEUROSCI.2006-20.2021
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