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Neural structure mapping in human probabilistic reward learning

View ORCID ProfileFabrice Luyckx, Hamed Nili, View ORCID ProfileBernhard Spitzer, Christopher Summerfield
doi: https://doi.org/10.1101/366757
Fabrice Luyckx
University of Oxford;
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  • For correspondence: fabrice.luyckx@psy.ox.ac.uk
Hamed Nili
Wellcome Centre for Integrative Neuroimaging;
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Bernhard Spitzer
Max Planck Institute for Human Development
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Christopher Summerfield
University of Oxford;
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Abstract

Humans can learn abstract concepts that describe invariances over relational patterns in data. One such concept, known as magnitude, allows stimuli to be compactly represented by a single dimension (i.e. on a mental line), for example according to their cardinality, size or value. Here, we measured representations of magnitude in humans by recording neural signals whilst they viewed symbolic numbers. During a subsequent reward-guided learning task, the neural patterns elicited by novel complex visual images reflected their pay-out probability in a way that suggested they were encoded onto the same mental number line. Our findings suggest that in humans, learning about values is accompanied by structural alignment of value representations with neural codes for the concept of magnitude.

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The copyright holder for this preprint is the author/funder. It is made available under a CC-BY-NC-ND 4.0 International license.
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  • Posted July 10, 2018.

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Neural structure mapping in human probabilistic reward learning
Fabrice Luyckx, Hamed Nili, Bernhard Spitzer, Christopher Summerfield
bioRxiv 366757; doi: https://doi.org/10.1101/366757
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Neural structure mapping in human probabilistic reward learning
Fabrice Luyckx, Hamed Nili, Bernhard Spitzer, Christopher Summerfield
bioRxiv 366757; doi: https://doi.org/10.1101/366757

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