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Boch M, Huber L, Lamm C. Domestic dogs as a comparative model for social neuroscience: Advances and challenges. Neurosci Biobehav Rev 2024; 162:105700. [PMID: 38710423 DOI: 10.1016/j.neubiorev.2024.105700] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 03/19/2024] [Accepted: 04/30/2024] [Indexed: 05/08/2024]
Abstract
Dogs and humans have lived together for thousands of years and share many analogous socio-cognitive skills. Dog neuroimaging now provides insight into the neural bases of these shared social abilities. Here, we summarize key findings from dog fMRI identifying neocortical brain areas implicated in visual social cognition, such as face, body, and emotion perception, as well as action observation in dogs. These findings provide converging evidence that the temporal cortex plays a significant role in visual social cognition in dogs. We further briefly review investigations into the neural base of the dog-human relationship, mainly involving limbic brain regions. We then discuss current challenges in the field, such as statistical power and lack of common template spaces, and how to overcome them. Finally, we argue that the foundation has now been built to investigate and compare the neural bases of more complex socio-cognitive phenomena shared by dogs and humans. This will strengthen and expand the role of the domestic dog as a powerful comparative model species and provide novel insights into the evolutionary roots of social cognition.
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Affiliation(s)
- Magdalena Boch
- Social, Cognitive and Affective Neuroscience Unit, Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna 1010, Austria; Department of Cognitive Biology, Faculty of Life Sciences, University of Vienna, Vienna 1090, Austria.
| | - Ludwig Huber
- Comparative Cognition, Messerli Research Institute, University of Veterinary Medicine Vienna, Medical University of Vienna and University of Vienna, Vienna 1210, Austria
| | - Claus Lamm
- Social, Cognitive and Affective Neuroscience Unit, Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna 1010, Austria; Vienna Cognitive Science Hub, University of Vienna, Vienna 1010, Austria
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2
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Isparta S, Töre-Yargın G, Wagner SC, Mundorf A, Cinar Kul B, Da Graça Pereira G, Güntürkün O, Ocklenburg S, Freund N, Salgirli Demirbas Y. Measuring paw preferences in dogs, cats and rats: Design requirements and innovations in methodology. Laterality 2024:1-37. [PMID: 38669348 DOI: 10.1080/1357650x.2024.2341459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Accepted: 04/04/2024] [Indexed: 04/28/2024]
Abstract
Studying behavioural lateralization in animals holds great potential for answering important questions in laterality research and clinical neuroscience. However, comparative research encounters challenges in reliability and validity, requiring new approaches and innovative designs to overcome. Although validated tests exist for some species, there is yet no standard test to compare lateralized manual behaviours between individuals, populations, and animal species. One of the main reasons is that different fine-motor abilities and postures must be considered for each species. Given that pawedness/handedness is a universal marker for behavioural lateralization across species, this article focuses on three commonly investigated species in laterality research: dogs, cats, and rats. We will present six apparatuses (two for dogs, three for cats, and one for rats) that enable an accurate assessment of paw preference. Design requirements and specifications such as zoometric fit for different body sizes and ages, reliability, robustness of the material, maintenance during and after testing, and animal welfare are extremely important when designing a new apparatus. Given that the study of behavioural lateralization yields crucial insights into animal welfare, laterality research, and clinical neuroscience, we aim to provide a solution to these challenges by presenting design requirements and innovations in methodology across species.
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Affiliation(s)
- Sevim Isparta
- Biopsychology, Institute of Cognitive Neuroscience, Department of Psychology, Ruhr University Bochum, Bochum, Germany
- Department of Genetics, Faculty of Veterinary Medicine, Ankara University, Ankara, Turkey
- Division of Experimental and Molecular Psychiatry, Department of Psychiatry, Psychotherapy and Preventive Medicine, LWL University Hospital, Ruhr University Bochum, Bochum, Germany
| | - Gülşen Töre-Yargın
- Brunel Design School College of Engineering Design & Physical Sciences, Brunel University London, Uxbridge, UK
- METU/BILTIR-UTEST Product Usability Unit, Department of Industrial Design, Middle East Technical University, Ankara, Turkey
| | - Selina C Wagner
- Division of Experimental and Molecular Psychiatry, Department of Psychiatry, Psychotherapy and Preventive Medicine, LWL University Hospital, Ruhr University Bochum, Bochum, Germany
| | - Annakarina Mundorf
- Institute for Systems Medicine and Department of Human Medicine, MSH Medical School Hamburg, Hamburg, Germany
- Department of Neurology, Division of Cognitive Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Bengi Cinar Kul
- Department of Genetics, Faculty of Veterinary Medicine, Ankara University, Ankara, Turkey
| | - Goncalo Da Graça Pereira
- Egas Moniz Center for Interdisciplinary Research (CiiEM), Egas Moniz School of Health & Science, Almada, Portugal
| | - Onur Güntürkün
- Biopsychology, Institute of Cognitive Neuroscience, Department of Psychology, Ruhr University Bochum, Bochum, Germany
- Research Center One Health Ruhr, Research Alliance Ruhr, Ruhr University Bochum, Bochum, Germany
| | - Sebastian Ocklenburg
- Biopsychology, Institute of Cognitive Neuroscience, Department of Psychology, Ruhr University Bochum, Bochum, Germany
- Department of Psychology, MSH Medical School Hamburg, Hamburg, Germany
- ICAN Institute for Cognitive and Affective Neuroscience, MSH Medical School Hamburg, Hamburg, Germany
| | - Nadja Freund
- Division of Experimental and Molecular Psychiatry, Department of Psychiatry, Psychotherapy and Preventive Medicine, LWL University Hospital, Ruhr University Bochum, Bochum, Germany
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Deshpande G, Zhao S, Waggoner P, Beyers R, Morrison E, Huynh N, Vodyanoy V, Denney TS, Katz JS. Two Separate Brain Networks for Predicting Trainability and Tracking Training-Related Plasticity in Working Dogs. Animals (Basel) 2024; 14:1082. [PMID: 38612321 PMCID: PMC11010877 DOI: 10.3390/ani14071082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 03/28/2024] [Accepted: 03/29/2024] [Indexed: 04/14/2024] Open
Abstract
Functional brain connectivity based on resting-state functional magnetic resonance imaging (fMRI) has been shown to be correlated with human personality and behavior. In this study, we sought to know whether capabilities and traits in dogs can be predicted from their resting-state connectivity, as in humans. We trained awake dogs to keep their head still inside a 3T MRI scanner while resting-state fMRI data was acquired. Canine behavior was characterized by an integrated behavioral score capturing their hunting, retrieving, and environmental soundness. Functional scans and behavioral measures were acquired at three different time points across detector dog training. The first time point (TP1) was prior to the dogs entering formal working detector dog training. The second time point (TP2) was soon after formal detector dog training. The third time point (TP3) was three months' post detector dog training while the dogs were engaged in a program of maintenance training for detection work. We hypothesized that the correlation between resting-state FC in the dog brain and behavior measures would significantly change during their detection training process (from TP1 to TP2) and would maintain for the subsequent several months of detection work (from TP2 to TP3). To further study the resting-state FC features that can predict the success of training, dogs at TP1 were divided into a successful group and a non-successful group. We observed a core brain network which showed relatively stable (with respect to time) patterns of interaction that were significantly stronger in successful detector dogs compared to failures and whose connectivity strength at the first time point predicted whether a given dog was eventually successful in becoming a detector dog. A second ontologically based flexible peripheral network was observed whose changes in connectivity strength with detection training tracked corresponding changes in behavior over the training program. Comparing dog and human brains, the functional connectivity between the brain stem and the frontal cortex in dogs corresponded to that between the locus coeruleus and left middle frontal gyrus in humans, suggestive of a shared mechanism for learning and retrieval of odors. Overall, the findings point toward the influence of phylogeny and ontogeny in dogs producing two dissociable functional neural networks.
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Affiliation(s)
- Gopikrishna Deshpande
- Auburn University Neuroimaging Center, Department of Electrical & Computer Engineering, Auburn University, Auburn, AL 36849, USA; (S.Z.); (R.B.); (N.H.); (T.S.D.J.)
- Department of Psychological Sciences, Auburn University, Auburn, AL 36849, USA
- Alabama Advanced Imaging Consortium, Birmingham, AL 36849, USA
- Center for Neuroscience, Auburn University, Auburn, AL 36849, USA
- Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore 560029, India
- Department of Heritage Science and Technology, Indian Institute of Technology, Hyderabad 502285, India
| | - Sinan Zhao
- Auburn University Neuroimaging Center, Department of Electrical & Computer Engineering, Auburn University, Auburn, AL 36849, USA; (S.Z.); (R.B.); (N.H.); (T.S.D.J.)
| | - Paul Waggoner
- Canine Performance Sciences Program, College of Veterinary Medicine, Auburn University, Auburn, AL 36849, USA;
| | - Ronald Beyers
- Auburn University Neuroimaging Center, Department of Electrical & Computer Engineering, Auburn University, Auburn, AL 36849, USA; (S.Z.); (R.B.); (N.H.); (T.S.D.J.)
| | - Edward Morrison
- Department of Anatomy, Physiology & Pharmacology, Auburn University, Auburn, AL 36849, USA; (E.M.); (V.V.)
| | - Nguyen Huynh
- Auburn University Neuroimaging Center, Department of Electrical & Computer Engineering, Auburn University, Auburn, AL 36849, USA; (S.Z.); (R.B.); (N.H.); (T.S.D.J.)
| | - Vitaly Vodyanoy
- Department of Anatomy, Physiology & Pharmacology, Auburn University, Auburn, AL 36849, USA; (E.M.); (V.V.)
| | - Thomas S. Denney
- Auburn University Neuroimaging Center, Department of Electrical & Computer Engineering, Auburn University, Auburn, AL 36849, USA; (S.Z.); (R.B.); (N.H.); (T.S.D.J.)
- Department of Psychological Sciences, Auburn University, Auburn, AL 36849, USA
- Alabama Advanced Imaging Consortium, Birmingham, AL 36849, USA
- Center for Neuroscience, Auburn University, Auburn, AL 36849, USA
| | - Jeffrey S. Katz
- Auburn University Neuroimaging Center, Department of Electrical & Computer Engineering, Auburn University, Auburn, AL 36849, USA; (S.Z.); (R.B.); (N.H.); (T.S.D.J.)
- Department of Psychological Sciences, Auburn University, Auburn, AL 36849, USA
- Alabama Advanced Imaging Consortium, Birmingham, AL 36849, USA
- Center for Neuroscience, Auburn University, Auburn, AL 36849, USA
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Hong H, Guo C, Liu X, Yang L, Ren W, Zhao H, Li Y, Zhou Z, Lam SM, Mi J, Zuo Z, Liu C, Wang GD, Zhuo Y, Zhang YP, Li Y, Shui G, Zhang YQ, Xiong Y. Differential effects of social isolation on oligodendrocyte development in different brain regions: insights from a canine model. Front Cell Neurosci 2023; 17:1201295. [PMID: 37538851 PMCID: PMC10393781 DOI: 10.3389/fncel.2023.1201295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 06/07/2023] [Indexed: 08/05/2023] Open
Abstract
Social isolation (SI) exerts diverse adverse effects on brain structure and function in humans. To gain an insight into the mechanisms underlying these effects, we conducted a systematic analysis of multiple brain regions from socially isolated and group-housed dogs, whose brain and behavior are similar to humans. Our transcriptomic analysis revealed reduced expression of myelin-related genes specifically in the white matter of prefrontal cortex (PFC) after SI during the juvenile stage. Despite these gene expression changes, myelin fiber organization in PFC remained unchanged. Surprisingly, we observed more mature oligodendrocytes and thicker myelin bundles in the somatosensory parietal cortex in socially isolated dogs, which may be linked to an increased expression of ADORA2A, a gene known to promote oligodendrocyte maturation. Additionally, we found a reduced expression of blood-brain barrier (BBB) structural components Aquaporin-4, Occludin, and Claudin1 in both PFC and parietal cortices, indicating BBB disruption after SI. In agreement with BBB disruption, myelin-related sphingolipids were increased in cerebrospinal fluid in the socially isolated group. These unexpected findings show that SI induces distinct alterations in oligodendrocyte development and shared disruption in BBB integrity in different cortices, demonstrating the value of dogs as a complementary animal model to uncover molecular mechanisms underlying SI-induced brain dysfunction.
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Affiliation(s)
- Huilin Hong
- State Key Laboratory for Molecular and Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
| | - Chao Guo
- Division of Life Sciences and Medicine, School of Life Sciences, University of Science and Technology of China, Hefei, China
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Xueru Liu
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Liguang Yang
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
- Bio-Med Big Data Center, Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Wei Ren
- State Key Laboratory for Molecular and Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Hui Zhao
- State Key Laboratory for Molecular and Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
| | - Yuan Li
- Beijing Sinogene Biotechnology Co., Ltd., Beijing, China
| | - Zhongyin Zhou
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Sin Man Lam
- State Key Laboratory for Molecular and Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
| | - Jidong Mi
- Beijing Sinogene Biotechnology Co., Ltd., Beijing, China
| | - Zhentao Zuo
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Cirong Liu
- Institute of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
- Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China
| | - Guo-Dong Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Yan Zhuo
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Ya-Ping Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Yixue Li
- Bio-Med Big Data Center, Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Guanghou Shui
- State Key Laboratory for Molecular and Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Yong Q. Zhang
- State Key Laboratory for Molecular and Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Ying Xiong
- State Key Laboratory for Molecular and Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
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Prichard A, Chhibber R, King J, Athanassiades K, Spivak M, Berns GS. Decoding Odor Mixtures in the Dog Brain: An Awake fMRI Study. Chem Senses 2021; 45:833-844. [PMID: 33179730 DOI: 10.1093/chemse/bjaa068] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
In working and practical contexts, dogs rely upon their ability to discriminate a target odor from distracting odors and other sensory stimuli. Using awake functional magnetic resonance imaging (fMRI) in 18 dogs, we examined the neural mechanisms underlying odor discrimination between 2 odors and a mixture of the odors. Neural activation was measured during the presentation of a target odor (A) associated with a food reward, a distractor odor (B) associated with nothing, and a mixture of the two odors (A+B). Changes in neural activation during the presentations of the odor stimuli in individual dogs were measured over time within three regions known to be involved with odor processing: the caudate nucleus, the amygdala, and the olfactory bulbs. Average activation within the amygdala showed that dogs maximally differentiated between odor stimuli based on the stimulus-reward associations by the first run, while activation to the mixture (A+B) was most similar to the no-reward (B) stimulus. To clarify the neural representation of odor mixtures in the dog brain, we used a random forest classifier to compare multilabel (elemental) versus multiclass (configural) models. The multiclass model performed much better than the multilabel (weighted-F1 0.44 vs. 0.14), suggesting the odor mixture was processed configurally. Analysis of the subset of high-performing dogs' brain classification metrics revealed a network of olfactory information-carrying brain regions that included the amygdala, piriform cortex, and posterior cingulate. These results add further evidence for the configural processing of odor mixtures in dogs and suggest a novel way to identify high-performers based on brain classification metrics.
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Affiliation(s)
| | | | - Jon King
- Psychology Department, Emory University, Atlanta, GA, USA
| | | | - Mark Spivak
- Comprehensive Pet Therapy, Inc., Sandy Springs, GA, USA.,Dog Star Technologies, LLC, Sandy Springs, GA, USA
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Boch M, Karl S, Sladky R, Huber L, Lamm C, Wagner IC. Tailored haemodynamic response function increases detection power of fMRI in awake dogs (Canis familiaris). Neuroimage 2021; 224:117414. [PMID: 33011420 DOI: 10.1016/j.neuroimage.2020.117414] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Revised: 08/17/2020] [Accepted: 09/24/2020] [Indexed: 01/06/2023] Open
Abstract
Functional magnetic resonance imaging (fMRI) of awake and unrestrained dogs (Canis familiaris) has been established as a novel opportunity for comparative neuroimaging, promising important insights into the evolutionary roots of human brain function and cognition. However, data processing and analysis pipelines are often derivatives of methodological standards developed for human neuroimaging, which may be problematic due to profound neurophysiological and anatomical differences between humans and dogs. Here, we explore whether dog fMRI studies would benefit from a tailored dog haemodynamic response function (HRF). In two independent experiments, dogs were presented with different visual stimuli. BOLD signal changes in the visual cortex during these experiments were used for (a) the identification and estimation of a tailored dog HRF, and (b) the independent validation of the resulting dog HRF estimate. Time course analyses revealed that the BOLD signal in the primary visual cortex peaked significantly earlier in dogs compared to humans, while being comparable in shape. Deriving a tailored dog HRF significantly improved the model fit in both experiments, compared to the canonical HRF used in human fMRI. Using the dog HRF yielded significantly increased activation during visual stimulation, extending from the occipital lobe to the caudal parietal cortex, the bilateral temporal cortex, into bilateral hippocampal and thalamic regions. In sum, our findings provide robust evidence for an earlier onset of the dog HRF in two visual stimulation paradigms, and suggest that using such an HRF will be important to increase fMRI detection power in canine neuroimaging. By providing the parameters of the tailored dog HRF and related code, we encourage and enable other researchers to validate whether our findings generalize to other sensory modalities and experimental paradigms.
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Affiliation(s)
- Magdalena Boch
- Social, Cognitive and Affective Neuroscience Unit, Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, 1010 Vienna, Austria; Department of Cognitive Biology, Faculty of Life Sciences, University of Vienna, 1090, Vienna, Austria
| | - Sabrina Karl
- Comparative Cognition, Messerli Research Institute, University of Veterinary Medicine Vienna, Medical University of Vienna and University of Vienna, 1210 Vienna, Austria
| | - Ronald Sladky
- Social, Cognitive and Affective Neuroscience Unit, Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, 1010 Vienna, Austria
| | - Ludwig Huber
- Comparative Cognition, Messerli Research Institute, University of Veterinary Medicine Vienna, Medical University of Vienna and University of Vienna, 1210 Vienna, Austria
| | - Claus Lamm
- Social, Cognitive and Affective Neuroscience Unit, Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, 1010 Vienna, Austria.
| | - Isabella C Wagner
- Social, Cognitive and Affective Neuroscience Unit, Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, 1010 Vienna, Austria.
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Karl S, Boch M, Zamansky A, van der Linden D, Wagner IC, Völter CJ, Lamm C, Huber L. Exploring the dog-human relationship by combining fMRI, eye-tracking and behavioural measures. Sci Rep 2020; 10:22273. [PMID: 33335230 PMCID: PMC7747637 DOI: 10.1038/s41598-020-79247-5] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 12/04/2020] [Indexed: 11/08/2022] Open
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.
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Affiliation(s)
- Sabrina Karl
- Clever Dog Lab, Comparative Cognition, Messerli Research Institute, University of Veterinary Medicine Vienna, Medical University of Vienna, University of Vienna, 1210, Vienna, Austria.
| | - Magdalena Boch
- Social, Cognitive and Affective Neuroscience Unit, Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, 1010, Vienna, Austria
- Department of Cognitive Biology, Faculty of Life Sciences, University of Vienna, 1090, Vienna, Austria
| | - Anna Zamansky
- Information Systems Department, University of Haifa, 3498838, Haifa, Israel
| | - Dirk van der Linden
- Department of Computer and Information Sciences, Northumbria University, Newcastle-upon-Tyne, NE1 8ST, UK
| | - Isabella C Wagner
- Social, Cognitive and Affective Neuroscience Unit, Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, 1010, Vienna, Austria
| | - Christoph J Völter
- Clever Dog Lab, Comparative Cognition, Messerli Research Institute, University of Veterinary Medicine Vienna, Medical University of Vienna, University of Vienna, 1210, Vienna, Austria
| | - Claus Lamm
- Social, Cognitive and Affective Neuroscience Unit, Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, 1010, Vienna, Austria
| | - Ludwig Huber
- Clever Dog Lab, Comparative Cognition, Messerli Research Institute, University of Veterinary Medicine Vienna, Medical University of Vienna, University of Vienna, 1210, Vienna, Austria
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8
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Csoltova E, Mehinagic E. Where Do We Stand in the Domestic Dog ( Canis familiaris ) Positive-Emotion Assessment: A State-of-the-Art Review and Future Directions. Front Psychol 2020; 11:2131. [PMID: 33013543 PMCID: PMC7506079 DOI: 10.3389/fpsyg.2020.02131] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Accepted: 07/30/2020] [Indexed: 12/19/2022] Open
Abstract
Although there have been a growing number of studies focusing on dog welfare, the research field concerning dog positive-emotion assessment remains mostly unexplored. This paper aims to provide a state-of-the-art review and summary of the scattered and disperse research on dog positive-emotion assessment. The review notably details the current advancement in dog positive-emotion research, what approaches, measures, methods, and techniques have been implemented so far in emotion perception, processing, and response assessment. Moreover, we propose possible future research directions for short-term emotion as well as longer-term emotional states assessment in dogs. The review ends by identifying and addressing some methodological limitations and by pointing out further methodological research needs.
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Liu X, Tian R, Zuo Z, Zhao H, Wu L, Zhuo Y, Zhang YQ, Chen L. A high-resolution MRI brain template for adult Beagle. Magn Reson Imaging 2020; 68:148-157. [DOI: 10.1016/j.mri.2020.01.003] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Revised: 01/08/2020] [Accepted: 01/10/2020] [Indexed: 11/25/2022]
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Abstract
In recent years, two well-developed methods of studying mental processes in humans have been successively applied to dogs. First, eye-tracking has been used to study visual cognition without distraction in unrestrained dogs. Second, noninvasive functional magnetic resonance imaging (fMRI) has been used for assessing the brain functions of dogs in vivo. Both methods, however, require dogs to sit, stand, or lie motionless while yet remaining attentive for several minutes, during which time their brain activity and eye movements are measured. Whereas eye-tracking in dogs is performed in a quiet and, apart from the experimental stimuli, nonstimulating and highly controlled environment, MRI scanning can only be performed in a very noisy and spatially restraining MRI scanner, in which dogs need to feel relaxed and stay motionless in order to study their brain and cognition with high precision. Here we describe in detail a training regime that is perfectly suited to train dogs in the required skills, with a high success probability and while keeping to the highest ethical standards of animal welfare-that is, without using aversive training methods or any other compromises to the dog's well-being for both methods. By reporting data from 41 dogs that successfully participated in eye-tracking training and 24 dogs IN fMRI training, we provide robust qualitative and quantitative evidence for the quality and efficiency of our training methods. By documenting and validating our training approach here, we aim to inspire others to use our methods to apply eye-tracking or fMRI for their investigations of canine behavior and cognition.
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Affiliation(s)
- Sabrina Karl
- Clever Dog Lab, Comparative Cognition, Messerli Research Institute, University of Veterinary Medicine Vienna, Medical University of Vienna, University of Vienna, Vienna, Austria.
| | - Magdalena Boch
- Social, Cognitive and Affective Neuroscience Unit, Department of Basic Psychological Research and Research Methods, Faculty of Psychology, University of Vienna, Vienna, Austria
- Department of Cognitive Biology, Faculty of Life Sciences, University of Vienna, Vienna, Austria
| | - Zsófia Virányi
- Clever Dog Lab, Comparative Cognition, Messerli Research Institute, University of Veterinary Medicine Vienna, Medical University of Vienna, University of Vienna, Vienna, Austria
| | - Claus Lamm
- Social, Cognitive and Affective Neuroscience Unit, Department of Basic Psychological Research and Research Methods, Faculty of Psychology, University of Vienna, Vienna, Austria
| | - Ludwig Huber
- Clever Dog Lab, Comparative Cognition, Messerli Research Institute, University of Veterinary Medicine Vienna, Medical University of Vienna, University of Vienna, Vienna, Austria
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11
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Separate brain areas for processing human and dog faces as revealed by awake fMRI in dogs (Canis familiaris). Learn Behav 2019; 46:561-573. [PMID: 30349971 DOI: 10.3758/s13420-018-0352-z] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Functional magnetic resonance imaging (fMRI) has emerged as a viable method to study the neural processing underlying cognition in awake dogs. Working dogs were presented with pictures of dog and human faces. The human faces varied in familiarity (familiar trainers and unfamiliar individuals) and emotional valence (negative, neutral, and positive). Dog faces were familiar (kennel mates) or unfamiliar. The findings revealed adjacent but separate brain areas in the left temporal cortex for processing human and dog faces in the dog brain. The human face area (HFA) and dog face area (DFA) were both parametrically modulated by valence indicating emotion was not the basis for the separation. The HFA and DFA were not influenced by familiarity. Using resting state fMRI data, functional connectivity networks (connectivity fingerprints) were compared and matched across dogs and humans. These network analyses found that the HFA mapped onto the human fusiform area and the DFA mapped onto the human superior temporal gyrus, both core areas in the human face processing system. The findings provide insight into the evolution of face processing.
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Prichard A, Chhibber R, Athanassiades K, Spivak M, Berns GS. Fast neural learning in dogs: A multimodal sensory fMRI study. Sci Rep 2018; 8:14614. [PMID: 30279481 PMCID: PMC6168449 DOI: 10.1038/s41598-018-32990-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2018] [Accepted: 09/19/2018] [Indexed: 01/11/2023] Open
Abstract
Dogs may follow their nose, but they learn associations to many types of sensory stimuli. Are some modalities learned better than others? We used awake fMRI in 19 dogs over a series of three experiments to measure reward-related learning of visual, olfactory, and verbal stimuli. Neurobiological learning curves were generated for individual dogs by measuring activation over time within three regions of interest: the caudate nucleus, amygdala, and parietotemporal cortex. The learning curves showed that dogs formed stimulus-reward associations in as little as 22 trials. Consistent with neuroimaging studies of associative learning, the caudate showed a main effect for reward-related stimuli, but not a significant interaction with modality. However, there were significant differences in the time courses, suggesting that although multiple modalities are represented in the caudate, the rates of acquisition and habituation are modality-dependent and are potentially gated by their salience in the amygdala. Visual and olfactory modalities resulted in the fastest learning, while verbal stimuli were least effective, suggesting that verbal commands may be the least efficient way to train dogs.
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Affiliation(s)
- Ashley Prichard
- Psychology Department, Emory University, Atlanta, GA, 30322, USA
| | - Raveena Chhibber
- Psychology Department, Emory University, Atlanta, GA, 30322, USA
| | | | - Mark Spivak
- Comprehensive Pet Therapy, Atlanta, GA, 30328, USA
| | - Gregory S Berns
- Psychology Department, Emory University, Atlanta, GA, 30322, USA.
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Roles for referential focus in effective and efficient canine signaling: Do pet and working dogs differ? J Vet Behav 2018. [DOI: 10.1016/j.jveb.2018.07.005] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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Abstract
Recent pioneering work has shown the great promise that scanning awake, nonsedated dogs holds for both understanding the canine and the human brain and mind. A number of technological and methodological challenges, however, still need to be overcome to fully tap this potential.
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15
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Olsen MR. A case for methodological overhaul and increased study of executive function in the domestic dog (Canis lupus familiaris). Anim Cogn 2018; 21:175-195. [PMID: 29380086 DOI: 10.1007/s10071-018-1162-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2017] [Revised: 01/14/2018] [Accepted: 01/19/2018] [Indexed: 12/13/2022]
Abstract
Executive function (EF) allows for self-regulation of behavior including maintaining focus in the face of distraction, inhibiting behavior that is suboptimal or inappropriate in a given context, and updating the contents of working memory. While EF has been studied extensively in humans, it has only recently become a topic of research in the domestic dog. In this paper, I argue for increased study of dog EF by explaining how it might influence the owner-dog bond, human safety, and dog welfare, as well as reviewing the current literature dedicated to EF in dogs. In "EF and its Application to "Man's Best Friend" section, I briefly describe EF and how it is relevant to dog behavior. In "Previous investigations into EF in dogs" section, I provide a review of the literature pertaining to EF in dogs, specifically tasks used to assess abilities like inhibitory control, cognitive flexibility, and working memory capacity. In "Insights and limitations of previous studies" section, I consider limitations of existing studies that must be addressed in future research. Finally, in "Future directions" section, I propose future directions for meaningful research on EF in dogs.
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Bunford N, Andics A, Kis A, Miklósi Á, Gácsi M. Canis familiaris As a Model for Non-Invasive Comparative Neuroscience. Trends Neurosci 2017; 40:438-452. [PMID: 28571614 DOI: 10.1016/j.tins.2017.05.003] [Citation(s) in RCA: 67] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2017] [Revised: 04/28/2017] [Accepted: 05/02/2017] [Indexed: 02/06/2023]
Abstract
There is an ongoing need to improve animal models for investigating human behavior and its biological underpinnings. The domestic dog (Canis familiaris) is a promising model in cognitive neuroscience. However, before it can contribute to advances in this field in a comparative, reliable, and valid manner, several methodological issues warrant attention. We review recent non-invasive canine neuroscience studies, primarily focusing on (i) variability among dogs and between dogs and humans in cranial characteristics, and (ii) generalizability across dog and dog-human studies. We argue not for methodological uniformity but for functional comparability between methods, experimental designs, and neural responses. We conclude that the dog may become an innovative and unique model in comparative neuroscience, complementing more traditional models.
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Affiliation(s)
- Nóra Bunford
- Eötvös Loránd University (ELTE), Institute of Biology, Department of Ethology, Pázmány Péter sétány 1/C, 1117 Budapest, Hungary.
| | - Attila Andics
- Eötvös Loránd University (ELTE), Institute of Biology, Department of Ethology, Pázmány Péter sétány 1/C, 1117 Budapest, Hungary; Hungarian Academy of Sciences, MTA-ELTE Comparative Ethology Research Group, Pázmány Péter sétány 1/C, 1117 Budapest, Hungary
| | - Anna Kis
- Hungarian Academy of Sciences, Institute of Cognitive Neuroscience and Psychology, Magyar tudósok körútja 2, 1117 Budapest, Hungary
| | - Ádám Miklósi
- Eötvös Loránd University (ELTE), Institute of Biology, Department of Ethology, Pázmány Péter sétány 1/C, 1117 Budapest, Hungary; Hungarian Academy of Sciences, MTA-ELTE Comparative Ethology Research Group, Pázmány Péter sétány 1/C, 1117 Budapest, Hungary
| | - Márta Gácsi
- Eötvös Loránd University (ELTE), Institute of Biology, Department of Ethology, Pázmány Péter sétány 1/C, 1117 Budapest, Hungary; Hungarian Academy of Sciences, MTA-ELTE Comparative Ethology Research Group, Pázmány Péter sétány 1/C, 1117 Budapest, Hungary
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