Can Monkeys Choose Optimally When Faced With Noisy Stimuli And Unequal Rewards?

Main Category: Veterinary
Also Included In: Biology / Biochemistry
Article Date: 13 Feb 2009 - 6:00 PDT

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Even when faced with distractions, monkeys are able to consistently choose the path of greatest reward, according to a study conducted by researchers from Princeton and Stanford Universities. The study, published February 13th in the open-access journal PLoS Computational Biology, adds to the growing evidence that animal foraging behavior can approach optimality, and could provide a basis for understanding the computations involved in this and related tasks.

In the article, Feng and colleagues address ongoing experiments relating to monkeys' abilities to distinguish among moving stimuli. Monkeys were trained to identify the direction of motion of a field of randomly-moving dots, a fraction of which move coherently in one of two possible directions. But unlike most previous studies in which all correct choices were equally rewarded, different sized rewards were now associated with different stimuli, and the researchers developed a mathematical model to predict how the animals should balance sensory information and prior expectations regarding rewards, in order to maximize their net returns. The study is unique in that it assesses not only the accuracy of decisions, but also the overall harvesting efficiency.

Remarkably, the monkeys devised a near-optimal strategy. Across the course of several hundred choices in each daily session, with randomly interspersed coherence and reward conditions, their typical harvesting efficiency fell within 1-2% of the theoretical maximum. These findings reveal impressive decision-making ability, and raise important questions about the neural mechanisms that underlie it.

CITATION
"Can Monkeys Choose Optimally When Faced with Noisy Stimuli and Unequal Rewards?"
Feng S, Holmes P, Rorie A, Newsome WT (2009)
PLoS Comput Biol 5(2): e1000284. doi:10.1371/journal.pcbi.1000284
Click here to view article online

About PLoS Computational Biology

PLoS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales through the application of computational methods. All works published in PLoS Computational Biology are open access. Everything is immediately available subject only to the condition that the original authorship and source are properly attributed. Copyright is retained by the authors. The Public Library of Science uses the Creative Commons Attribution License.

PLoS Computational Biology

About the Public Library of Science

The Public Library of Science (PLoS) is a non-profit organization of scientists and physicians committed to making the world's scientific and medical literature a freely available public resource.

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Article adapted by Medical News Today from original press release.
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