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Human value learning and representation reflect rational adaptation to task demands

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Abstract

Humans and other animals routinely make choices between goods of different values. Choices are often made within identifiable contexts, such that an efficient learner may represent values relative to their local context. However, if goods occur across multiple contexts, a relative value code can lead to irrational choices. In this case, an absolute context-independent value is preferable to a relative code. Here we test the hypothesis that value representation is not fixed but rationally adapted to context expectations. In two experiments, we manipulated participants’ expectations about whether item values learned within local contexts would need to be subsequently compared across contexts. Despite identical learning experiences, the group whose expectations included choices across local contexts went on to learn more absolute-like representation than the group whose expectations covered only fixed local contexts. Human value representation is thus neither relative nor absolute but efficiently and rationally tuned to task demands.

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Fig. 1: Experiment 1 design and tasks.
Fig. 2: All-Pairs choice accuracy in Experiment 1.
Fig. 3: Value RDMs from Experiment 1.
Fig. 4: RDM correlations from Experiment 1.
Fig. 5: Experiment 2 design and All-Pairs choice accuracy.
Fig. 6: Value RDMs from Experiment 2.
Fig. 7: Model RDM correlations from Experiment 2.

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Data availability

The data are available online on the Open Science Framework (https://osf.io/h32u6/).

Code availability

The analysis code is available on the Open Science Framework (https://osf.io/h32u6/).

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Acknowledgements

A.J. was supported by a British Academy Postdoctoral Fellowship in developing this research (D-MAD, PF150005). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. We thank P. Barr for programming Experiment 2. We thank the Palminteri lab for helpful suggestions on these data.

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Authors

Contributions

K.J. and A.J. designed the research. T.A. and R.H. conducted the research. A.J. analysed the data. K.J. and A.J. contributed materials and analysis tools and wrote the paper.

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Correspondence to Andreas Jarvstad.

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Nature Human Behaviour thanks Charley Wu, Sebastian Gluth and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Supplementary Information

Supplementary Methods I–III and Results I–IX.

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Juechems, K., Altun, T., Hira, R. et al. Human value learning and representation reflect rational adaptation to task demands. Nat Hum Behav 6, 1268–1279 (2022). https://doi.org/10.1038/s41562-022-01360-4

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