Attila Andics

Voice-sensitive regions in the dog and human brain are revealed by comparative fMRI

During the approximately 18-32 thousand years of domestication, dogs and humans have shared a similar social environment. Dog and human vocalizations are thus familiar and relevant to both species, although they belong to evolutionarily distant taxa, as their lineages split approximately 90-100 million years ago. In this first comparative neuroimaging study of a nonprimate and a primate species, we made use of this special combination of shared environment and evolutionary distance. We presented dogs and humans with the same set of vocal and nonvocal stimuli to search for functionally analogous voice-sensitive cortical regions. We demonstrate that voice areas exist in dogs and that they show a similar pattern to anterior temporal voice areas in humans. Our findings also reveal that sensitivity to vocal emotional valence cues engages similarly located nonprimary auditory regions in dogs and humans. Although parallel evolution cannot be excluded, our findings suggest that voice areas may have a more ancient evolutionary origin than previously known.

Neural mechanisms for lexical processing in dogs

During speech processing, human listeners can separately analyze lexical and intonational cues to arrive at a unified representation of communicative content. The evolution of this capacity can be best investigated by comparative studies. Using functional magnetic resonance imaging, we explored whether and how dog brains segregate and integrate lexical and intonational information. We found a hemispheric bias for processing meaningful words, independently of intonation; an auditory brain region for distinguishing intonationally marked and unmarked words; and increased activity in primary reward regions only when both lexical and intonational information were consistent with praise. Neural mechanisms to separately analyze and integrate word meaning and intonation in dogs suggest that this capacity can evolve in the absence of language.

Humans rely on the same rules to assess emotional valence and intensity in conspecific and dog vocalizations

Humans excel at assessing conspecific emotional valence and intensity, based solely on non-verbal vocal bursts that are also common in other mammals. It is not known, however, whether human listeners rely on similar acoustic cues to assess emotional content in conspecific and heterospecific vocalizations, and which acoustical parameters affect their performance. Here, for the first time, we directly compared the emotional valence and intensity perception of dog and human non-verbal vocalizations. We revealed similar relationships between acoustic features and emotional valence and intensity ratings of human and dog vocalizations: those with shorter call lengths were rated as more positive, whereas those with a higher pitch were rated as more intense. Our findings demonstrate that humans rate conspecific emotional vocalizations along basic acoustic rules, and that they apply similar rules when processing dog vocal expressions. This suggests that humans may utilize similar mental mechanisms for recognizing human and heterospecific vocal emotions.

Canis familiaris As a Model for Non-Invasive Comparative Neuroscience

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.

Neural processes of vocal social perception: Dog-human comparative fMRI studies

HIGHLIGHTSDog is an emerging new model in comparative social cognitive neuroscience.Dogs’ vocal repertoire, cooperativity and trainability make them an ideal model species.Dog‐human comparative fMRI reveals mammalian neural mechanisms for voice processing.Dog‐human comparative fMRI studies may shed new light on language evolution. ABSTRACT In this review we focus on the exciting new opportunities in comparative neuroscience to study neural processes of vocal social perception by comparing dog and human neural activity using fMRI methods. The dog is a relatively new addition to this research area; however, it has a large potential to become a standard species in such investigations. Although there has been great interest in the emergence of human language abilities, in case of fMRI methods, most research to date focused on homologue comparisons within Primates. By belonging to a very different clade of mammalian evolution, dogs could give such research agendas a more general mammalian foundation. In addition, broadening the scope of investigations into vocal communication in general can also deepen our understanding of human vocal skills. Being selected for and living in an anthropogenic environment, research with dogs may also be informative about the way in which human non‐linguistic and linguistic signals are represented in a mammalian brain without skills for language production.

Erratum: Voice-Sensitive Regions in the Dog and Human Brain Are Revealed by Comparative fMRI (Current Biology (2014) 24(5) (574–578) (S0960982214001237) (10.1016/j.cub.2014.01.058))

Attila Andics,1,* Márta Gácsi,1 Tamás Faragó,1 Anna Kis,2,3 and Ádám Miklósi1,2 1MTA-ELTE Comparative Ethology Research Group, Pázmány Péter sétány 1/C, 1117 Budapest, Hungary 2Department of Ethology, Eötvös Loránd University, Pázmány Péter sétány 1/C, 1117 Budapest, Hungary 3Research Centre for Natural Sciences, Institute of Cognitive Neuroscience and Psychology, Hungarian Academy of Sciences, Magyar tudósok körútja 2, 1117 Budapest, Hungary

Resting-state fMRI data of awake dogs (Canis familiaris) via group-level independent component analysis reveal multiple, spatially distributed resting-state networks

Resting-state networks are spatially distributed, functionally connected brain regions. Studying these networks gives us information about the large-scale functional organization of the brain and alternations in these networks are considered to play a role in a wide range of neurological conditions and aging. To describe resting-state networks in dogs, we measured 22 awake, unrestrained animals of either sex and carried out group-level spatial independent component analysis to explore whole-brain connectivity patterns. Using resting-state functional magnetic resonance imaging (rs-fMRI), in this exploratory study we found multiple resting-state networks in dogs, which resemble the pattern described in humans. We report the following dog resting-state networks: default mode network (DMN), visual network (VIS), sensorimotor network (SMN), combined auditory (AUD)-saliency (SAL) network and cerebellar network (CER). The DMN, similarly to Primates, but unlike previous studies in dogs, showed antero-posterior connectedness with involvement of hippocampal and lateral temporal regions. The results give us insight into the resting-state networks of awake animals from a taxon beyond rodents through a non-invasive method.