Human brains construct individualized global rankings from identical few-shot learning input.

Overview

1. School of Psychological and Cognitive Sciences, Peking University, Beijing, China
2. PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
3. Beijing Key Laboratory of Behavior and Mental Health, Peking University, Beijing, China
4. Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, China
5. Applied Computational Psychiatry Lab, Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Queen Square Institute of Neurology and Mental Health Neuroscience Department, Division of Psychiatry, UCL, London, United Kingdom

Abstract

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.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Data

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• osf:gya95, at OSF; found in “Data Availability”

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All data files are available at https://osf.io/gya95/.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Version 1, 29 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 3 authors, 9 MeSH terms, 3 funders, 48 references.

Cite

This paper

Liu, D., Wang, M., & Luo, H. (2026). Human brains construct individualized global rankings from identical few-shot learning input. PLoS biology, 24(4), e3003756. https://doi.org/10.1371/journal.pbio.3003756

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