Studying the neural representations of uncertainty.
Journal
Nature neuroscience
ISSN: 1546-1726
Titre abrégé: Nat Neurosci
Pays: United States
ID NLM: 9809671
Informations de publication
Date de publication:
Nov 2023
Nov 2023
Historique:
received:
08
02
2022
accepted:
30
08
2023
medline:
3
11
2023
pubmed:
10
10
2023
entrez:
9
10
2023
Statut:
ppublish
Résumé
The study of the brain's representations of uncertainty is a central topic in neuroscience. Unlike most quantities of which the neural representation is studied, uncertainty is a property of an observer's beliefs about the world, which poses specific methodological challenges. We analyze how the literature on the neural representations of uncertainty addresses those challenges and distinguish between 'code-driven' and 'correlational' approaches. Code-driven approaches make assumptions about the neural code for representing world states and the associated uncertainty. By contrast, correlational approaches search for relationships between uncertainty and neural activity without constraints on the neural representation of the world state that this uncertainty accompanies. To compare these two approaches, we apply several criteria for neural representations: sensitivity, specificity, invariance and functionality. Our analysis reveals that the two approaches lead to different but complementary findings, shaping new research questions and guiding future experiments.
Identifiants
pubmed: 37814025
doi: 10.1038/s41593-023-01444-y
pii: 10.1038/s41593-023-01444-y
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
1857-1867Subventions
Organisme : EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council)
ID : StG-947105
Organisme : Agence Nationale de la Recherche (French National Research Agency)
ID : 18-CE37-0010-01
Informations de copyright
© 2023. Springer Nature America, Inc.
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