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Contribution Details

Type Journal Article
Scope Discipline-based scholarship
Title Rethinking model-based and model-free influences on mental effort and striatal prediction errors
Organization Unit
Authors
  • Carolina Feher da Silva
  • Gaia Lombardi
  • Micah Goldsmith Edelson
  • Todd Anthony Hare
Item Subtype Original Work
Refereed Yes
Status Published in final form
Language
  • English
Journal Title Nature Human Behaviour
Publisher Nature Publishing Group
Geographical Reach international
ISSN 2397-3374
Volume 7
Number 6
Page Range 956 - 969
Date 2023
Abstract Text A standard assumption in neuroscience is that low-effort model-free learning is automatic and continuously used, whereas more complex model-based strategies are only used when the rewards they generate are worth the additional effort. We present evidence refuting this assumption. First, we demonstrate flaws in previous reports of combined model-free and model-based reward prediction errors in the ventral striatum that probably led to spurious results. More appropriate analyses yield no evidence of model-free prediction errors in this region. Second, we find that task instructions generating more correct model-based behaviour reduce rather than increase mental effort. This is inconsistent with cost–benefit arbitration between model-based and model-free strategies. Together, our data indicate that model-free learning may not be automatic. Instead, humans can reduce mental effort by using a model-based strategy alone rather than arbitrating between multiple strategies. Our results call for re-evaluation of the assumptions in influential theories of learning and decision-making.
Digital Object Identifier 10.1038/s41562-023-01573-1
Other Identification Number merlin-id:23671
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Keywords Behavioral neuroscience, experimental and cognitive psychology, social psychology