Rules warp feature encoding in decision-making circuits
R Becket Ebitz,
Jiaxin Cindy Tu and
Benjamin Y Hayden
PLOS Biology, 2020, vol. 18, issue 11, 1-38
Abstract:
We have the capacity to follow arbitrary stimulus–response rules, meaning simple policies that guide our behavior. Rule identity is broadly encoded across decision-making circuits, but there are less data on how rules shape the computations that lead to choices. One idea is that rules could simplify these computations. When we follow a rule, there is no need to encode or compute information that is irrelevant to the current rule, which could reduce the metabolic or energetic demands of decision-making. However, it is not clear if the brain can actually take advantage of this computational simplicity. To test this idea, we recorded from neurons in 3 regions linked to decision-making, the orbitofrontal cortex (OFC), ventral striatum (VS), and dorsal striatum (DS), while macaques performed a rule-based decision-making task. Rule-based decisions were identified via modeling rules as the latent causes of decisions. This left us with a set of physically identical choices that maximized reward and information, but could not be explained by simple stimulus–response rules. Contrasting rule-based choices with these residual choices revealed that following rules (1) decreased the energetic cost of decision-making; and (2) expanded rule-relevant coding dimensions and compressed rule-irrelevant ones. Together, these results suggest that we use rules, in part, because they reduce the costs of decision-making through a distributed representational warping in decision-making circuits.Following a simple rule feels easier than weighing and integrating every piece of evidence into a decision; this study asks why this is the case through examining how following a rule changes the way that decisions are made in the brain.
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.3000951 (text/html)
https://journals.plos.org/plosbiology/article/file ... 00951&type=printable (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:plo:pbio00:3000951
DOI: 10.1371/journal.pbio.3000951
Access Statistics for this article
More articles in PLOS Biology from Public Library of Science
Bibliographic data for series maintained by plosbiology ().