Dogs’ reactions to motivations and emotions in conspecific and heterospecific vocalizations

Vocalizations convey information about both emotional valence (negative/positive) and motivational states (hostile/non-hostile). However, it remains unclear which of these dimensions primarily determines what the listener decodes from vocalizations as social messages, guiding their reaction (approach/withdraw). To test this question, we presented agonistic (negative|hostile), play/comfort (positive|non-hostile), and distress sounds (negative|non-hostile) to dogs. In Study 1, the motivational state encoded in conspecific calls better explained dogs' reactions than emotional valence. Distress calls evoked faster approaches but slower withdrawal than agonistic calls, indicating that dogs primarily decode conspecific social messages based on the caller's motivation. In Study 2, we tested cross-species decodability with chimpanzee and human calls and speech. Neither the callers' motivational state nor emotional valence explained dogs' reactions, which did not support predictions based on Morton's rules and other proposed universal principles of emotion encoding. These findings suggest that the caller's motivation may have been more significant in close-contact call evolution than emotions, and the mechanisms underlying the processing of conspecific vocalizations do not directly generalize to cross-species vocalizations. Consequently, decoding social messages from vocalizations may rely less on universal rules than previously thought.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2026-04-01
DOI
https://doi.org/10.1038/s41598-026-46906-y
Primary Topic
Human-Animal Interaction Studies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Dogs’ reactions to motivations and emotions in conspecific and heterospecific vocalizations

Katie E. Slocombe, Tamás Faragó, Beatrix Laczi, Paula Pérez Fraga et al.
Scientific Reports
Human-Animal Interaction Studies
article

Dogs’ reactions to motivations and emotions in conspecific and heterospecific vocalizations

Katie E. Slocombe, Tamás Faragó, Beatrix Laczi, Paula Pérez Fraga, Soufiane Bel Rhali, Enikő Kubinyi, Morgane Audiguier, Attila Andics, Lilla Kocsis, Irene Rojas Atares
article en

Abstract

Vocalizations convey information about both emotional valence (negative/positive) and motivational states (hostile/non-hostile). However, it remains unclear which of these dimensions primarily determines what the listener decodes from vocalizations as social messages, guiding their reaction (approach/withdraw). To test this question, we presented agonistic (negative|hostile), play/comfort (positive|non-hostile), and distress sounds (negative|non-hostile) to dogs. In Study 1, the motivational state encoded in conspecific calls better explained dogs' reactions than emotional valence. Distress calls evoked faster approaches but slower withdrawal than agonistic calls, indicating that dogs primarily decode conspecific social messages based on the caller's motivation. In Study 2, we tested cross-species decodability with chimpanzee and human calls and speech. Neither the callers' motivational state nor emotional valence explained dogs' reactions, which did not support predictions based on Morton's rules and other proposed universal principles of emotion encoding. These findings suggest that the caller's motivation may have been more significant in close-contact call evolution than emotions, and the mechanisms underlying the processing of conspecific vocalizations do not directly generalize to cross-species vocalizations. Consequently, decoding social messages from vocalizations may rely less on universal rules than previously thought.

Scientific Reports
Eötvös Loránd University (HU), University of York (GB)
Eötvös Loránd Tudományegyetem
Reduced inequalities
Openalex Percentile: Top 31%
Human-Animal Interaction 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.