Trading mental effort for confidence in the metacognitive control of value-based decision-making

Abstract
Data availability
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Abstract

Why do we sometimes opt for actions or items that we do not value the most? Under current neurocomputational theories, such preference reversals are typically interpreted in terms of errors that arise from the unreliable signaling of value to brain decision systems. But, an alternative explanation is that people may change their mind because they are reassessing the value of alternative options while pondering the decision. So, why do we carefully ponder some decisions, but not others? In this work, we derive a computational model of the metacognitive control of decisions or MCD. In brief, we assume that fast and automatic processes first provide initial (and largely uncertain) representations of options' values, yielding prior estimates of decision difficulty. These uncertain value representations are then refined by deploying cognitive (e.g., attentional, mnesic) resources, the allocation of which is controlled by an effort-confidence tradeoff. Importantly, the anticipated benefit of allocating resources varies in a decision-by-decision manner according to the prior estimate of decision difficulty. The ensuing MCD model predicts response time, subjective feeling of effort, choice confidence, changes of mind, and choice-induced preference change and certainty gain. We test these predictions in a systematic manner, using a dedicated behavioral paradigm. Our results provide a quantitative link between mental effort, choice confidence, and preference reversals, which could inform interpretations of related neuroimaging findings.

Data availability

Empirical data as well as model fitting code have been uploaded as part of this submission. Also, it is now publicly available at Dryad: https://doi.org/10.5061/dryad.7h44j0zsg

The following data sets were generated

1. Lee D
2. Daunizeau J
(2021) Lee and Daunizeau choice data from: Trading mental effort for confidence in the metacognitive control of value-based decision-making
Dryad Digital Repository, 10.5061/dryad.7h44j0zsg.

https://doi.org/10.5061/dryad.7h44j0zsg

Article and author information

Author details

Douglas G Lee

Sorbonne University, Paris, France

For correspondence
DouglasGLee@gmail.com

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0001-5892-8694
Jean Daunizeau

Institut du Cerveau et de la Moelle épinère (ICM), INSERM, Paris, France

For correspondence
jean.daunizeau@gmail.com

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0001-9142-1270

Funding

Laboratory of Excellence of Biology for Psychiatry

Douglas G Lee

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Human subjects: This study complies with all relevant ethical regulations and received formal approval from the INSERM Ethics Committee (CEEI-IRB00003888, decision no 16-333). In particular, in accordance with the Helsinki declaration, all participants gave written informed consent prior to commencing the experiment, which included consent to disseminate the results of the study via publication.

Copyright

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.