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Contribution Details

Type Journal Article
Scope Discipline-based scholarship
Title Efficient coding of subjective value
Organization Unit
Authors
  • Rafael Polania
  • Michael Woodford
  • Christian Ruff
Item Subtype Original Work
Refereed Yes
Status Published in final form
Language
  • English
Journal Title Nature Neuroscience
Publisher Nature Publishing Group
Geographical Reach international
ISSN 1097-6256
Volume 22
Number 1
Page Range 134 - 142
Date 2019
Abstract Text Preference-based decisions are essential for survival, for instance, when deciding what we should (not) eat. Despite their importance, preference-based decisions are surprisingly variable and can appear irrational in ways that have defied mechanistic explanations. Here we propose that subjective valuation results from an inference process that accounts for the structure of values in the environment and that maximizes information in value representations in line with demands imposed by limited coding resources. A model of this inference process explains the variability in both subjective value reports and preference-based choices, and predicts a new preference illusion that we validate with empirical data. Interestingly, the same model explains the level of confidence associated with these reports. Our results imply that preference-based decisions reflect information- maximizing transmission and statistically optimal decoding of subjective values by a limited-capacity system. These findings provide a unified account of how humans perceive and valuate the environment to optimally guide behavior.
Official URL https://www.nature.com/articles/s41593-018-0292-0
Digital Object Identifier 10.1038/s41593-018-0292-0
Other Identification Number merlin-id:17184
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Keywords General Neuroscience