Left-to-right spatial-numerical association in domestic dogs

The Spatial Numerical Association (SNA) refers to a spatial representation where smaller numerosities are linked to the left and larger ones with the right. SNA has been documented in humans, infants, primates, chicks, and even insects, supporting the idea that it is biologically rooted, rather than dependent on education or symbolic number systems. Domestic dogs offer a valuable model for cognitive research due to both their accessibility as subjects, given the possibility to involve large samples of pet dogs, and to their inter-individual variability in their life experiences. Studying the SNA in dogs therefore provides a unique opportunity to test whether such numerical spatialization is robust to experiential heterogeneity. In the present study, we investigated the potential presence of bilateral SNA in eighteen domestic dogs, tested in a spontaneous choice task. After ten exposures to a reference numerosity depicting 8 dots, dogs underwent two test trials in which lateral panels displayed either fewer (4) or more (16) dots than the reference numerosity. About 70% of the dogs chose the left panel when presented with fewer-than-reference stimuli and the right panel when presented with more-than-reference stimuli. These results support the presence of a left-to-right oriented SNA in adult dogs, suggesting that numerical spatialization in non-human animals exists despite potentially extensive differences in individual experience.

Publication Details

Journal
Research Padua Archive (University of Padua)
Published
2025-01-01
Primary Topic
Diverse Scientific and Economic Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Left-to-right spatial-numerical association in domestic dogs

Research Padua Archive (University of Padua)
Diverse Scientific and Economic Studies
article

Left-to-right spatial-numerical association in domestic dogs

article en

Abstract

The Spatial Numerical Association (SNA) refers to a spatial representation where smaller numerosities are linked to the left and larger ones with the right. SNA has been documented in humans, infants, primates, chicks, and even insects, supporting the idea that it is biologically rooted, rather than dependent on education or symbolic number systems. Domestic dogs offer a valuable model for cognitive research due to both their accessibility as subjects, given the possibility to involve large samples of pet dogs, and to their inter-individual variability in their life experiences. Studying the SNA in dogs therefore provides a unique opportunity to test whether such numerical spatialization is robust to experiential heterogeneity. In the present study, we investigated the potential presence of bilateral SNA in eighteen domestic dogs, tested in a spontaneous choice task. After ten exposures to a reference numerosity depicting 8 dots, dogs underwent two test trials in which lateral panels displayed either fewer (4) or more (16) dots than the reference numerosity. About 70% of the dogs chose the left panel when presented with fewer-than-reference stimuli and the right panel when presented with more-than-reference stimuli. These results support the presence of a left-to-right oriented SNA in adult dogs, suggesting that numerical spatialization in non-human animals exists despite potentially extensive differences in individual experience.

Research Padua Archive (University of Padua)
Quality Education
Openalex Percentile: Top 39%
Diverse Scientific and Economic Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.