Related Experiment Video
Updated: Jun 23, 2026

07:59
Using a Comparative Species Approach to Investigate the Neurobiology of Paternal Responses
Published on: September 19, 2011
13.0K
Continuous or discrete magnitudes? A comparative study between cats, dogs and humans
Mireia Solé Pi1, Luz A Espino1, Péter Szenczi2,3
1Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Mexico City, Mexico.
Plos One
|October 1, 2025
Summary
Quantity discrimination varies across species. Cats and humans show preferences based on quantity or shape, while dogs do not consistently differentiate stimuli, suggesting ecological context influences decision-making.
Area of Science:
- Cognitive Science
- Comparative Psychology
- Animal Behavior
Background:
- Quantity discrimination is a fundamental cognitive ability.
- Species differ in whether they rely on numerical or continuous magnitude cues for decisions.
- Understanding these differences sheds light on the evolution of cognition.
Purpose of the Study:
- To investigate whether numerosity or total surface area influences choice in cats, dogs, and humans.
- To compare decision-making processes across these species using a spontaneous choice paradigm.
- To explore the role of shape preference in quantity discrimination.
Main Methods:
- A two-way spontaneous choice paradigm was employed.
- Food stimuli were used for cats and dogs; image stimuli for humans.
- Ratios of stimuli (0.5 and 0.67) and shape variations were systematically manipulated.
Main Results:
- Cats preferred larger food quantities at a 0.5 ratio but not 0.67.
- Dogs did not differentiate food quantities regardless of ratio.
- Humans discriminated quantities almost perfectly; dogs and humans showed shape preferences (e.g., circles).
- Human reaction times varied with stimulus properties, unlike cats and dogs.
Conclusions:
- Quantity estimation is not universally processed; it is influenced by a species' ecological context.
- Decision-making strategies for quantity vary significantly across cats, dogs, and humans.
- Future research should explore quantity estimation in diverse contexts and motivational states.
Related Concept Videos
How Data are Classified: Categorical Data
A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
Multiple Comparison Tests
Multiple comparison test, abbreviated as MCT, is a post hoc analysis generally performed after comparing multiple samples with one or more tests. An MCT will help identify a significantly different sample among multiple samples or a factor among multiple factors.
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
Testing a Claim about Mean: Unknown Population SD
A complete procedure of testing a hypothesis about a population mean when the population standard deviation is unknown is explained here.
Estimating a population mean requires the samples to be approximately normally distributed. The data should be collected from the randomly selected samples having no sampling bias. There is no specific requirement for sample size. But if the sample size is less than 30, and we don't know the population standard deviation, a different approach is used; instead...
Estimating a population mean requires the samples to be approximately normally distributed. The data should be collected from the randomly selected samples having no sampling bias. There is no specific requirement for sample size. But if the sample size is less than 30, and we don't know the population standard deviation, a different approach is used; instead...
Sign Test for Nominal Data
The sign test is a nonparametric method used to evaluate hypotheses about the median of a single sample or to compare the medians of two related samples. The sign test is particularly useful when dealing with nominal data, which includes distinct categories without an inherent order, such as names, labels, and preferences. Nominal data restricts statistical analysis to evaluating population proportions rather than mean or median values that require continuous data.
For example, consider a...
For example, consider a...

