Academic Journal
Human brains construct individualized global rankings from identical few-shot learning input.
| Τίτλος: | Human brains construct individualized global rankings from identical few-shot learning input. |
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| Συγγραφείς: | Liu, Dongning, Wang, Muzhi, Luo, Huan |
| Πηγή: | PLoS Biology; 4/13/2026, Vol. 24 Issue 4, p1-26, 26p |
| Θεματικοί όροι: | Magnetoencephalography, Individual differences, Linear orderings, Cognitive neuroscience, Induction (Logic), Central nervous system |
| Περίληψη: | Ranking—a ubiquitous relational structure—enables humans to organize complex information and overcome cognitive load, yet in real-world settings it is often inferred from sparse, few-shot learning of local pairwise relationships. How the human brain performs relational inference under such limited evidence remains unknown. We hypothesized that under few-shot learning, relational inference is shaped by inductive biases, such that individuals actively impose structured global relationships—often idiosyncratic—to constrain and unify limited local information. In a preregistered behavioral study combined with magnetoencephalography (MEG) recordings, we show that even after identical few-shot local pair learning, individuals construct stable and self-consistent, yet idiosyncratic, global rankings that diverge from the ground-truth order—a phenomenon not readily explained by classical computational models of transitive inference. MEG recordings further reveal that frontoparietal neural representations are reorganized to reflect each individual's subjective ranking rather than those of others. Together, these findings highlight the constructive and generative nature of human cognition: under sparse samples and limited computational resources, the human brain actively infers and imposes relational structure. Do humans establish common knowledge from identical inputs? This study uses behavior and MEG to show that even based on identical local evidence, human brains construct stable, self-consistent, yet highly individual global rankings, highlighting the constructive nature of human cognition. [ABSTRACT FROM AUTHOR] |
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| Βάση Δεδομένων: | Complementary Index |
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| Items | – Name: Title Label: Title Group: Ti Data: Human brains construct individualized global rankings from identical few-shot learning input. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Liu%2C+Dongning%22">Liu, Dongning</searchLink><br /><searchLink fieldCode="AR" term="%22Wang%2C+Muzhi%22">Wang, Muzhi</searchLink><br /><searchLink fieldCode="AR" term="%22Luo%2C+Huan%22">Luo, Huan</searchLink> – Name: TitleSource Label: Source Group: Src Data: PLoS Biology; 4/13/2026, Vol. 24 Issue 4, p1-26, 26p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Magnetoencephalography%22">Magnetoencephalography</searchLink><br /><searchLink fieldCode="DE" term="%22Individual+differences%22">Individual differences</searchLink><br /><searchLink fieldCode="DE" term="%22Linear+orderings%22">Linear orderings</searchLink><br /><searchLink fieldCode="DE" term="%22Cognitive+neuroscience%22">Cognitive neuroscience</searchLink><br /><searchLink fieldCode="DE" term="%22Induction+%28Logic%29%22">Induction (Logic)</searchLink><br /><searchLink fieldCode="DE" term="%22Central+nervous+system%22">Central nervous system</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Ranking—a ubiquitous relational structure—enables humans to organize complex information and overcome cognitive load, yet in real-world settings it is often inferred from sparse, few-shot learning of local pairwise relationships. How the human brain performs relational inference under such limited evidence remains unknown. We hypothesized that under few-shot learning, relational inference is shaped by inductive biases, such that individuals actively impose structured global relationships—often idiosyncratic—to constrain and unify limited local information. In a preregistered behavioral study combined with magnetoencephalography (MEG) recordings, we show that even after identical few-shot local pair learning, individuals construct stable and self-consistent, yet idiosyncratic, global rankings that diverge from the ground-truth order—a phenomenon not readily explained by classical computational models of transitive inference. MEG recordings further reveal that frontoparietal neural representations are reorganized to reflect each individual's subjective ranking rather than those of others. Together, these findings highlight the constructive and generative nature of human cognition: under sparse samples and limited computational resources, the human brain actively infers and imposes relational structure. Do humans establish common knowledge from identical inputs? This study uses behavior and MEG to show that even based on identical local evidence, human brains construct stable, self-consistent, yet highly individual global rankings, highlighting the constructive nature of human cognition. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of PLoS Biology is the property of Public Library of Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1371/journal.pbio.3003756 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 26 StartPage: 1 Subjects: – SubjectFull: Magnetoencephalography Type: general – SubjectFull: Individual differences Type: general – SubjectFull: Linear orderings Type: general – SubjectFull: Cognitive neuroscience Type: general – SubjectFull: Induction (Logic) Type: general – SubjectFull: Central nervous system Type: general Titles: – TitleFull: Human brains construct individualized global rankings from identical few-shot learning input. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Liu, Dongning – PersonEntity: Name: NameFull: Wang, Muzhi – PersonEntity: Name: NameFull: Luo, Huan IsPartOfRelationships: – BibEntity: Dates: – D: 13 M: 04 Text: 4/13/2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 15449173 Numbering: – Type: volume Value: 24 – Type: issue Value: 4 Titles: – TitleFull: PLoS Biology Type: main |
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