Forming beliefs: Why valence matters
Abstract
One of the most salient attributes of information is valence: whether a piece of news is good or bad. Contrary to classic learning theories, which implicitly assume beliefs are adjusted similarly regardless of valence, we review evidence suggesting that different rules and mechanisms underlie learning from desirable and undesirable information. For self-relevant beliefs this asymmetry generates a positive bias, with significant implications for individuals and society. We discuss the boundaries of this asymmetry, characterize the neural system supporting it, and describe how changes in this circuit are related to individual differences in behavior.
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Psychotic symptoms may provide a form of personal identity, and personal level data may be assumed more reliable than those from others.
“That is, psychotic symptoms may provide a form of personal identity, and personal level data may be assumed more reliable than those from others.”
From The Predictive Coding Account of Psychosis (2018) · cites this paper as [112]
There may be a motivated quality to psychotic inferences.
“There may also be a motivated quality to psychotic inferences (112).”
From The Predictive Coding Account of Psychosis (2018) · cites this paper as [112]
Psychotic symptoms are susceptible to the same biases and asymmetries in updating observed with non-delusional beliefs.
“This renders them susceptible to the same biases and asymmetries in updating observed with non-delusional beliefs (112).”
From The Predictive Coding Account of Psychosis (2018) · cites this paper as [112]
Optimistic updating relies on a learning process involving asymmetric information integration.
“but relied on a learning process involving asymmetric information integration (20, 41).”
From Distinct oxytocin effects on belief updating in response to desirable and undesirable feedback (2016) · cites this paper as [41]
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References 106 · Cited by 345
- Authors
- Sharot, T., & Garrett, N.
- Affiliations
- University College London (GB)
- Corresponding author
- Sharot, Tali
- Venue
- Trends in Cognitive Sciences
- Publisher
- Elsevier BV
- Published
- 2016-01
- Volume
- 20
- Issue
- 1
- Pages
- 25-33
- ISSN
- 1364-6613 (ISSN-L)
- OpenAlex
- W2202219582
- Cited by
- 345
- References
- 106
- Citations by year
- 2026: 32 · 2025: 49 · 2024: 32 · 2023: 42 · 2022: 46 · 2021: 36 · 2020: 30 · 2019: 11 · 2018: 35 · 2017: 21 · 2016: 11
- FWCI
- 3.13
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Trends in Cognitive Sciences (publishedVersion)
- PubMed (publishedVersion)
- UEA Digital Repository (University of East Anglia) (submittedVersion)
- Funders
- Wellcome Trust
- Topics
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Cognitive Science and Education Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Keywords
- belief formation, valence, positive bias, individual differences
- MeSH terms
- Culture, Humans, Learning, Nerve Net, Social Values
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