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Easy Rider: Monkeys Learn to Drive a Wheelchair to Navigate through a Complex Maze

Overview of attention for article published in PLOS ONE, May 2014
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Title
Easy Rider: Monkeys Learn to Drive a Wheelchair to Navigate through a Complex Maze
Published in
PLOS ONE, May 2014
DOI 10.1371/journal.pone.0096275
Pubmed ID
Authors

Stephanie Etienne, Martin Guthrie, Michel Goillandeau, Tho Hai Nguyen, Hugues Orignac, Christian Gross, Thomas Boraud

Abstract

The neurological bases of spatial navigation are mainly investigated in rodents and seldom in primates. The few studies led on spatial navigation in both human and non-human primates are performed in virtual, not in real environments. This is mostly because of methodological difficulties inherent in conducting research on freely-moving monkeys in real world environments. There is some incertitude, however, regarding the extrapolation of rodent spatial navigation strategies to primates. Here we present an entirely new platform for investigating real spatial navigation in rhesus monkeys. We showed that monkeys can learn a pathway by using different strategies. In these experiments three monkeys learned to drive the wheelchair and to follow a specified route through a real maze. After learning the route, probe tests revealed that animals successively use three distinct navigation strategies based on i) the place of the reward, ii) the direction taken to obtain reward or iii) a cue indicating reward location. The strategy used depended of the options proposed and the duration of learning. This study reveals that monkeys, like rodents and humans, switch between different spatial navigation strategies with extended practice, implying well-conserved brain learning systems across different species. This new task with freely driving monkeys provides a good support for the electrophysiological and pharmacological investigation of spatial navigation in the real world by making possible electrophysiological and pharmacological investigations.

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Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 26%
Student > Ph. D. Student 5 22%
Student > Master 4 17%
Student > Doctoral Student 2 9%
Professor 2 9%
Other 2 9%
Unknown 2 9%
Readers by discipline Count As %
Neuroscience 5 22%
Computer Science 4 17%
Psychology 2 9%
Medicine and Dentistry 2 9%
Agricultural and Biological Sciences 1 4%
Other 4 17%
Unknown 5 22%