Two monkeys solved combinatorial optimization problems for rewards. They deliberated for extended durations, approximated efficient computational algorithms for managing complexity, and even selected algorithms according to the computational complexity of the trial. These findings reveal evidence for algorithm-based reasoning and establish a paradigm for studying the neurophysiological basis of deliberative thought.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$209.00 per year
only $17.42 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
References
Kahneman, D. A perspective on judgment and choice: mapping bounded rationality. Am. Psychol. 58, 697–720 (2003). This summary of Kahneman’s Nobel prize lecture is a nice introduction to system 1 and 2 thinking.
Padoa-Schioppa, C. & Assad, J. A. Neurons in the orbitofrontal cortex encode economic value. Nature 441, 223–226 (2006). This paper used binary choices to show that the orbitofrontal cortex (OFC) codes the values of choice options and the chosen option.
Rich, E. L. & Wallis, J. D. Decoding subjective decisions from orbitofrontal cortex. Nat. Neurosci. 19, 973–980 (2016). This paper used a binary choices paradigm to show that choices could be decoded from OFC.
Schultz, W. Neuronal reward and decision signals: from theories to data. Physiol. Rev. 95, 853–951 (2015). This review article presents a concise summary of single-unit recordings in choice tasks.
Murawski, C. & Bossaerts, P. How humans solve complex problems: the case of the knapsack problem. Sci. Rep. 6, 34851 (2016). This article shows that computational complexity modulates human behaviors in the knapsack problem.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
This is a summary of: Hong, T. & Stauffer, W. R. Computational complexity drives sustained deliberation. Nat. Neurosci. https://doi.org/10.1038/s41593-023-01307-6 (2023).
Rights and permissions
About this article
Cite this article
Computational strategies for deliberative thought. Nat Neurosci 26, 735–736 (2023). https://doi.org/10.1038/s41593-023-01309-4
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41593-023-01309-4
