Article

Nature 447, 1075-1080 (28 June 2007) | doi:10.1038/nature05852; Received 30 November 2006; Accepted 18 April 2007; Published online 3 June 2007

Probabilistic reasoning by neurons

Tianming Yang1 & Michael N. Shadlen1

  1. Howard Hughes Medical Institute, Department of Physiology and Biophysics, National Primate Research Center, University of Washington, Box 357290, Seattle, Washington 98195–7290, USA

Correspondence to: Tianming Yang1Michael N. Shadlen1 Correspondence and requests for materials should be addressed to T.Y. (Email: tianming@u.washington.edu) or M.N.S. (Email: shadlen@u.washington.edu).

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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.

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