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Updated: May 9, 2026

Behavioral Assessment of Manual Dexterity in Non-Human Primates
Published on: November 11, 2011
Quantity matching by an orangutan (Pongo abelii).
1Department of Psychology, Oakland University, 2200 N Squirrel Rd., Rochester, MI, 48309, USA, vonk@oakland.edu.
Orangutans can estimate quantity, performing well on numerical tasks involving animals, shapes, and dots. This indicates a sophisticated numerical cognition in orangutans, extending beyond human subitizing limits.
Area of Science:
- Cognitive ethology
- Comparative psychology
- Primate cognition
Background:
- Understanding numerical cognition in non-human primates provides insights into the evolution of number sense.
- Orangutans (Pongo abelii) are great apes with complex cognitive abilities, but their quantitative reasoning remains less explored compared to other primates.
Purpose of the Study:
- To investigate the numerical abilities of an orangutan using delayed matching-to-sample tasks.
- To determine if orangutans can discriminate quantities based on visual stimuli and generalize this ability to novel numerosities.
Main Methods:
- An adult male orangutan was trained on delayed matching-to-sample (DMTS) tasks involving stimuli with varying numbers of animals, shapes, or dots (1-10).
- Perceptual features like spatial arrangement and background color were varied, and dot size was manipulated.
- Performance was analyzed based on the absolute difference and ratio between comparison stimuli quantities.
Main Results:
- Orangutan performance was independent of perceptual variations but sensitive to numerical differences and ratios.
- Performance did not strictly follow the analog magnitude model's linear predictions.
- The orangutan demonstrated significant transfer to novel numerosities up to ten.
Conclusions:
- Orangutans possess robust quantity estimation abilities, extending to larger numerosities than typically subitized by humans.
- This suggests a more developed numerical cognition in orangutans than previously assumed.
- The findings contribute to understanding the comparative and evolutionary aspects of numerical cognition.
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