A Andics

AM Thompkins

Claus Lamm

GS Berns

L Huber

Ludwig Huber

English

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OUTLOOKUnderstanding dog cognition by functional magneticresonance imagingLudwig Huber1 & Claus Lamm2Published online: 25 February 2017# The Author(s) 2017. This article is published with open access at Springerlink.comSummary Recent pioneering work has shown the great prom-ise that scanning awake, nonsedated dogs holds for both under-standing the canine and the human brain and mind. A number oftechnological andmethodological challenges, however, still needto be overcome to fully tap this potential.Keywords Dog . fMRI . Canine brainFor both practical and theoretical reasons, one of the most highlyinvestigated species in comparative psychology is the domestic dog(Canis familiaris). They are available in great numbers, but moreimportantly, they show surprisingly complex socio-cognitive skills,such as understandingheterospecific (human) gestures and discrim-inating facial expressions, which enable dogs to outperform evenour closest primate relatives (e.g., Huber 2016). Pioneers of caninecognition research have thus proposed that the social abilities ofdogs are functional matches of corresponding human abilities.The reasons for the similarities between dogs and humans aremanifold. Dogs, as a species, have a history of several thousandyears alongside humans, and as individuals are raised in and livewith human families. They have a common ancestry with wolves(Canis lupus), whose dependency on close cooperation with con-specifics, for breeding and hunting, presumably created similarselection pressures on their motivational and cognitive processesas on our human ancestors. This likely provided a good basis forthe evolution of dog–human communication and cooperation.Dogs have been tested not only for key abilities of humansocial cognition, such as imitation and perspective taking, butalso for their understanding of human gestures, expressions, andeven voice. But behavioral data alone are insufficient to deter-mine whether similar behaviors across species can be explainedby the same proximate mechanisms. With the advent ofadvanced, noninvasive imaging procedures, brain function relat-ed to the dog–human relationship and interspecies understand-ing may now be studied and compared in vivo, in both species.This, however, requires dogs to lie motionless in a noisy andshaky MRI scanner without anesthesia or sedation, as the latterwould negatively affect both brain function and cognition. Abreakthrough in this respect was achieved only a few years ago.Four independent research groups—two in the USA (Atlantaand Auburn), one in Mexico (Querétaro), and one in Europe(Budapest)—have captured images of nonsedated and largely un-restrained dog brains, and their work and publications indicate theinterest in and importance of this new frontier in functional neuro-imaging (see Berns & Cook, 2016; Thompkins, Deshpande,Waggoner, & Katz, 2016, for review). Starting with investigationsof reward processing, a few studies looked at perceptual (olfactory,auditory, and visual) processing, and very recently researchers ex-amined executive functions (inhibitory control) and social and com-munication processes in the dog’s brain. Concerning the last do-main, a group of canine researchers teamed upwith neurobiologistsspecifically to test dog’s understanding of human speech. First, theyfound functionally analogous voice-sensitive cortical regions in thedog and human brain with a similar sensitivity to vocal emotionalvalence cues (Andics, Gacsi, Farago, Kis, &Miklosi, 2014). Morerecently, they also investigated how dog brains segregate and inte-grate lexical and intonational information from human speech(Andics, Gabor, Gacsi, Farago, Szabo, & Miklosi, 2016). Thatstudy suggests that brain activations in dogs processing linguisticcues are similar to those observed in humans, as indicated bydifferences in hemispheric lateralization, as well as the fact thatpraise words activated areas associated with reward processing.The latter two studies are particularly exciting as investigatinghow a nonhuman species responds to linguistic cues enablesunprecedented insights into the origins of a skill thought to beuniquely human. Thus, they highlight the great potential that dogfunctional MRI (fMRI) offers, from a comparative perspective.Challenges and limitationsDog fMRI clearly has the potential to result in major breakthroughsin understanding the sensory and cognitive processes of dogs.However, the evidence presented so far necessarily remains prelim-inary, because of its pioneering character and a number of method-ological challenges that still need to be overcome. These are briefly* Ludwig Huberludwig.huber@vetmeduni.ac.at1 Comparative Cognition, Messerli Research Institute, University ofVeterinary Medicine Vienna, Medical University of Vienna,University of Vienna, Veterinaerplatz 1, A- 1210 Vienna, Austria2 Social, Cognitive and Affective Neuroscience Unit, Department ofBasic Psychological Research and Research Methods, Faculty ofPsychology, University of Vienna, Liebiggasse 5,A-1010 Vienna, AustriaLearn Behav (2017) 45:101–102DOI 10.3758/s13420-017-0261-6described below in order to clarify that there are still ways to gobefore canine fMRI is comparable to human fMRI. This lag is basedon the fact that so far all published studies have relied on measure-ment protocols and hardware developed for human imaging.Image qualityIn comparison to the quality achieved with humans, the imagequality in canine fMRI is rather low. This is mainly because radiofrequency (RF) coils and imaging protocols have not been tailoredto the specifics of dogs and their neuroanatomy. The dog’s brain ismaximally one third the size of the human brain, with some criticalbrain areas deviating largely from the human counterparts, and itsphysiology (respiration rate, etc.) differs. We know from humanneuroimaging that the coil’s performancemust have excellent sen-sitivity and parallel imaging capability to enable the spatial andtemporal resolution envisioned in contemporary canine neuroim-aging. Published studies used different types of humanMRI coils,none of which were designed for dogs. In particular, the coil ge-ometries were not optimized for the canine head, and the numberof RF channels close to the dog’s brainwas limited. Because of thesmall number of channels, the expected imaging performance interms of both temporal and spatial resolution is rather low com-pared to what can be achieved in human fMRI. This calls for thedevelopment of dedicated MRI coils, which in other species (e.g.,in marmosets), has already shown great benefits.Furthermore, the number of datasets acquired during a scan-ning session is limited by the short length of time dogs canrestrain themselves. The limitations are less critical if simpleconditioning and sensory processes are investigated. But it com-promises the tremendous impact that more developed caninebrain imaging could have for models of affect and cognitionand for understanding the mechanisms of human social behav-ior. Thus, future training regimes should aim for longer scanningtimes, or make more extensive use of experimental protocolsand analysis approaches which allow data to be aggregated overrepeated imaging sessions with the same dog participants.MovementA critical issue for achieving high-quality fMRI data in awake dogsismovement. Even the best trained dogsmove their heads (e.g., dueto swallowing, respiration, heartbeat), which can have drastic effectson fMRI data. Especially if small brain regions like specific nuclei,which aremuch smaller than analogue areas in the human brain, arethe focus of future investigation, movement by only a fewmillime-ters is critical. Because these systematic artifacts contaminate thedogdatamore strongly thanhumandata, particular emphasis shouldbe placed on data cleaning (such as discarding scan volumes withexcessive movement) and artifact removal methods. For instance,some researchers used an external infrared camera to track dog headmotion and retrospectively correct for motion-related artifacts in thedata. However, as some forms of motion cannot be corrected usingstandard motion-correction techniques, exploratory data analysismethods including temporal independent component analysis(ICA) and spin-history corrections are necessary. Many of thesecorrection measures will require faster MR data sampling, such asin imaging sequences based on parallel imaging—which, as notedabove, will require optimized head coils.Sample sizeIn contrast to both fMRI studies in humans and behavioral stud-ies in dogs, the sample sizes of all published fMRI studies indogs are small, never exceeding 13 dogs, resulting in strongoutlier effects. This is unfortunate given the huge interindividualdifferences often obtained in cognitive dog research, possibledifferences between breeds (all studies used a mixture of breeds)and sex (spayed, neutered, intact). The time and effort requiredto train dogs for MRI, usually up to 4 months of training until adog is ready for testing (Berns & Cook 2016), constitutes amajor challenge for the future of fMRI in awake dogs.Task and stimulus design, experimental controlsMajor challenges exist for fMRI approaches in dogs, as inhumans, when it comes to linking neural responses to the cogni-tive processes they underpin. Issues such as reverse inference (i.e.,drawing conclusions on cognitive processes based on brain acti-vation only) are aggravated in dog fMRI, as the restrictive scannerenvironment precludes concomitant collection of cognitive or be-havioral measures. Moreover, comparing human with caninebrain responses requires closelymatched stimuli and task designs.The future impact of canine fMRI will thus not only depend onovercoming technological and statistical challenges of the fMRImethod but also on the creativity and rigor of the cognitive andbehavioral scientists developing and implementing appropriateexperimental designs and paradigms.Acknowledgements Open access funding provided by University ofVeterinary Medicine Vienna.Open Access This article is distributed under the terms of the CreativeCommons At t r ibut ion 4 .0 In te rna t ional License (h t tp : / /creativecommons.org/licenses/by/4.0/), which permits unrestricted use,distribution, and reproduction in any medium, provided you give appro-priate credit to the original author(s) and the source, provide a link to theCreative Commons license, and indicate if changes were made.ReferencesAndics, A., Gabor, A., Gacsi, M., Farago, T., Szabo, D., & Miklosi, A.(2016). Neural mechanisms for lexical processing in dogs. Science,353(6303), 1030–1032. doi:10.1126/science.aaf3777Andics, A., Gacsi, M., Farago, T., Kis, A., & Miklosi, A. (2014). Voice-sensitive regions in the dog and human brain are revealed by comparativefMRI. Current Biology, 24(5), 574–578. doi:10.1016/j.cub.2014.01.058Berns, G. S., & Cook, P. F. (2016). Why did the dog walk into the MRI?Current Directions in Psychological Science, 25(5), 363–369. doi:10.1177/0963721416665006Huber, L. (2016). How dogs perceive and understand us.Current Directions inPsychological Science, 25(5), 339–344. doi:10.1177/0963721416656329Thompkins, A. M., Deshpande, G., Waggoner, P., & Katz, J. S. (2016).Functional magnetic resonance imaging of the domestic dog: Research,methodology, and conceptual issues. Comparative Cognition &Behavior Reviews, 11, 63–82. doi:10.3819/CCBR.2016.110004102 Learn Behav (2017) 45:101–102

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Understanding dog cognition by functional magnetic resonance imaging

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Understanding dog cognition by functional magnetic resonance imaging

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