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Related Concept Videos

How Data are Classified: Numerical Data00:59

How Data are Classified: Numerical Data

Data that are countable or measurable in specific units are called numerical or quantitative data. Quantitative data are always numbers. Quantitative data are the result of counting or measuring the attributes of a population. Amount of money, pulse rate, weight, number of people living in a town, and number of students who opt for statistics are examples of quantitative data.
Quantitative data may be either discrete or continuous. All quantitative data that take on only specific numerical...

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Related Experiment Video

Updated: Jun 3, 2026

Assessment of Social Cognition in Non-human Primates Using a Network of Computerized Automated Learning Device (ALDM) Test Systems
08:42

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Published on: May 5, 2015

Representational format determines numerical competence in monkeys.

Vanessa Schmitt1, Julia Fischer

  • 1Cognitive Ethology Laboratory, German Primate Center, Göttingen, Göttingen 37077, Germany.

Nature Communications
|March 31, 2011
PubMed
Summary
This summary is machine-generated.

Monkeys perform better at numerical tasks when items are inedible or when food rewards are replaced. This suggests internal representation, not item type, drives decision-making accuracy in quantity discrimination.

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Area of Science:

  • Cognitive neuroscience
  • Comparative psychology
  • Animal behavior

Background:

  • Non-human primates possess an ancient numerical system for basic arithmetic and comparisons.
  • Primates often exhibit suboptimal performance in ecologically relevant quantity discrimination tasks with edible items, indicating interference from stimulus salience.

Purpose of the Study:

  • To investigate how stimulus properties and reward systems influence quantity discrimination in non-human primates.
  • To determine if the internal representation of stimuli, rather than their physical characteristics, affects decision-making accuracy.

Main Methods:

  • Monkeys completed quantity discrimination tasks using both edible and inedible items.
  • A reward replacement condition was introduced where food items were used, but rewards consisted of different food items.
  • Performance accuracy was compared across conditions.

Main Results:

  • Quantity discrimination accuracy was significantly higher with inedible items (84%) compared to food items (69%).
  • When tested with food items but rewarded with different food items, accuracy remained high (86%).

Conclusions:

  • The internal representation of stimuli, not their inherent physical quality, is the primary determinant of performance in quantity discrimination tasks.
  • Reward replacement enhances decision-making acuity by facilitating the representation of items as abstract signifiers for rewards.