Exploring the dog–human relationship by combining fMRI, eye-tracking and behavioural measures

Karl, Sabrina, Boch, Magdalena, Zamansky, Anna, van der Linden, Dirk, Wagner, Isabella C., Völter, Christoph J., Lamm, Claus and Huber, Ludwig (2020) Exploring the dog–human relationship by combining fMRI, eye-tracking and behavioural measures. Scientific Reports, 10 (1). p. 22273. ISSN 2045-2322

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Official URL: https://doi.org/10.1038/s41598-020-79247-5

Abstract

Behavioural studies revealed that the dog–human relationship resembles the human mother–child bond, but the underlying mechanisms remain unclear. Here, we report the results of a multi-method approach combining fMRI (N = 17), eye-tracking (N = 15), and behavioural preference tests (N = 24) to explore the engagement of an attachment-like system in dogs seeing human faces. We presented morph videos of the caregiver, a familiar person, and a stranger showing either happy or angry facial expressions. Regardless of emotion, viewing the caregiver activated brain regions associated with emotion and attachment processing in humans. In contrast, the stranger elicited activation mainly in brain regions related to visual and motor processing, and the familiar person relatively weak activations overall. While the majority of happy stimuli led to increased activation of the caudate nucleus associated with reward processing, angry stimuli led to activations in limbic regions. Both the eye-tracking and preference test data supported the superior role of the caregiver’s face and were in line with the findings from the fMRI experiment. While preliminary, these findings indicate that cutting across different levels, from brain to behaviour, can provide novel and converging insights into the engagement of the putative attachment system when dogs interact with humans.

Item Type: Article
Subjects: C100 Biology
C800 Psychology
D900 Others in Veterinary Sciences, Agriculture and related subjects
G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Elena Carlaw
Date Deposited: 18 Dec 2020 09:05
Last Modified: 31 May 2021 14:45
URI: http://nrl.northumbria.ac.uk/id/eprint/45046

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