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Probabilistic reasoning by neurons

Author

Listed:
  • Tianming Yang

    (Howard Hughes Medical Institute, National Primate Research Center, University of Washington, Box 357290, Seattle, Washington 98195–7290, USA)

  • Michael N. Shadlen

    (Howard Hughes Medical Institute, National Primate Research Center, University of Washington, Box 357290, Seattle, Washington 98195–7290, USA)

Abstract

Our brains allow us to reason about alternatives and to make choices that are likely to pay off. Often there is no one correct answer, but instead one that is favoured simply because it is more likely to lead to reward. A variety of probabilistic classification tasks probe the covert strategies that humans use to decide among alternatives based on evidence that bears only probabilistically on outcome. Here we show that rhesus monkeys can also achieve such reasoning. We have trained two monkeys to choose between a pair of coloured targets after viewing four shapes, shown sequentially, that governed the probability that one of the targets would furnish reward. Monkeys learned to combine probabilistic information from the shape combinations. Moreover, neurons in the parietal cortex reveal the addition and subtraction of probabilistic quantities that underlie decision-making on this task.

Suggested Citation

  • Tianming Yang & Michael N. Shadlen, 2007. "Probabilistic reasoning by neurons," Nature, Nature, vol. 447(7148), pages 1075-1080, June.
    • Handle: RePEc:nat:nature:v:447:y:2007:i:7148:d:10.1038_nature05852
    DOI: 10.1038/nature05852
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    Cited by:

    1. Floris P de Lange & Simon van Gaal & Victor A F Lamme & Stanislas Dehaene, 2011. "How Awareness Changes the Relative Weights of Evidence During Human Decision-Making," PLOS Biology, Public Library of Science, vol. 9(11), pages 1-10, November.
    2. Scott E. Allen & Ren'e F. Kizilcec & A. David Redish, 2024. "A new model of trust based on neural information processing," Papers 2401.08064, arXiv.org.
    3. Marine Hainguerlot & Thibault Gajdos & Jean-Christophe Vergnaud & Vincent de Gardelle, 2023. "How Overconfidence Bias Influences Suboptimality in Perceptual Decision Making," Post-Print hal-04197403, HAL.
    4. Lars Buesing & Johannes Bill & Bernhard Nessler & Wolfgang Maass, 2011. "Neural Dynamics as Sampling: A Model for Stochastic Computation in Recurrent Networks of Spiking Neurons," PLOS Computational Biology, Public Library of Science, vol. 7(11), pages 1-22, November.
    5. Fredrik Allenmark & Hermann J Müller & Zhuanghua Shi, 2018. "Inter-trial effects in visual pop-out search: Factorial comparison of Bayesian updating models," PLOS Computational Biology, Public Library of Science, vol. 14(7), pages 1-31, July.
    6. Jeromos Vukov & Francisco C Santos & Jorge M Pacheco, 2011. "Incipient Cognition Solves the Spatial Reciprocity Conundrum of Cooperation," PLOS ONE, Public Library of Science, vol. 6(3), pages 1-5, March.
    7. Jill X O'Reilly & Saad Jbabdi & Matthew F S Rushworth & Timothy E J Behrens, 2013. "Brain Systems for Probabilistic and Dynamic Prediction: Computational Specificity and Integration," PLOS Biology, Public Library of Science, vol. 11(9), pages 1-14, September.
    8. Dickhaut, John & Smith, Vernon & Xin, Baohua & Rustichini, Aldo, 2013. "Human economic choice as costly information processing," Journal of Economic Behavior & Organization, Elsevier, vol. 94(C), pages 206-221.
    9. Terence C. Burnham & Jay Phelan, 2022. "Ordinaries 10," Journal of Bioeconomics, Springer, vol. 24(3), pages 181-202, October.
    10. Zhewei Zhang & Chaoqun Yin & Tianming Yang, 2022. "Evidence accumulation occurs locally in the parietal cortex," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    11. Shinichiro Kira & Houman Safaai & Ari S. Morcos & Stefano Panzeri & Christopher D. Harvey, 2023. "A distributed and efficient population code of mixed selectivity neurons for flexible navigation decisions," Nature Communications, Nature, vol. 14(1), pages 1-28, December.
    12. Ulrik W Nash, 2014. "The Curious Anomaly of Skewed Judgment Distributions and Systematic Error in the Wisdom of Crowds," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-17, November.
    13. Moffat, James & Medhurst, John, 2009. "Modelling of human decision-making in simulation models of conflict using experimental gaming," European Journal of Operational Research, Elsevier, vol. 196(3), pages 1147-1157, August.
    14. Sebastian Gluth & Jörg Rieskamp & Christian Büchel, 2013. "Deciding Not to Decide: Computational and Neural Evidence for Hidden Behavior in Sequential Choice," PLOS Computational Biology, Public Library of Science, vol. 9(10), pages 1-15, October.
    15. Robert Legenstein & Wolfgang Maass, 2014. "Ensembles of Spiking Neurons with Noise Support Optimal Probabilistic Inference in a Dynamically Changing Environment," PLOS Computational Biology, Public Library of Science, vol. 10(10), pages 1-27, October.
    16. Floris P de Lange & Simon van Gaal & Victor A. F Lamme & Stanislas Dehaene, 2011. "How Awareness Changes the Relative Weights of Evidence During Human Decision-Making," Working Papers id:4656, eSocialSciences.

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