Conceived and designed the experiments: MVK RH. Performed the experiments: MVK SC. Analyzed the data: MVK. Contributed reagents/materials/analysis tools: JK. Wrote the paper: MVK JK SC RH.
Current address: Lyon Neuroscience Research Center, INSERM U1028 – CNRS UMR5292, Bron, France
The authors have declared that no competing interests exist.
We read conspecifics' social cues effortlessly, but little is known about our abilities to understand social gestures of other species. To investigate the neural underpinnings of such skills, we used functional magnetic resonance imaging to study the brain activity of experts and non-experts of dog behavior while they observed humans or dogs either interacting with, or facing away from a conspecific. The posterior superior temporal sulcus (pSTS) of both subject groups dissociated humans facing toward each other from humans facing away, and in dog experts, a distinction also occurred for dogs facing toward
Inspecting social interaction between two people from a third-person viewpoint engages brain areas supporting the analysis of human bodies, facial expressions, biological motion, and theory of mind
Earlier results propose that the brain mechanisms underlying human social cognition are utilized in the perception of non-human animals. For example, humans distinguish the direction of apparent movement from point-light walkers, irrespective of whether the walker represents a human or a non-human animal
Here, we investigated brain processes involved during observation of social interaction between two humans or two dogs. Since dog enthusiasts have a vast experience of observing dog behavior, we specifically tested whether such expertise would affect the observer's brain activity during observation of interaction of dogs. For this purpose, we measured functional magnetic resonance imaging (fMRI) signals from subjects observing photos of two humans or two dogs either interacting (facing towards each other) or not interacting (facing away); crystallized photos served as control stimuli (
Left column: Examples of stimuli where dogs and humans were either engaged in face-to-face interaction (toward) or facing away from each other (away); the pixelated and crystallized versions of the human and dog photos (pixel) served as controls. Middle and right columns: The average eye gaze maps for experts and control subjects, respective to the stimuli on the left. The average fixation durations are color-coded (minimum of 5 ms indicated by light blue and the maximum of 200 ms or over by bright red).
Two subject groups participated in the study:
The background questionnaire quantified the group differences in expertise of dog behavior
The empathy scale (IRI) scores did not differ between expert and control groups in any subcategory (mean ± SD scores on
The free written commentaries in the background questionnaire were answered by 89% of the dog experts and 67% of the control subjects. Dog experts made more inferences of dogs' mental states than did control subjects (18 and 5 inferences, respectively, Z = 3.1,
In general, the experts commented the dog photos in more detail, e.g. “
Stimulus condition | Part | Experts (N = 12) | Controls (N = 11) |
Dog_toward | Head | 878±123 | 1096±140 |
Body | 477±47 | 337±47 | |
Tail | 35±7 | 32±8 | |
Head+body+tail | 1390±95 | 1465±150 | |
Background | 395±58 | 300±47 | |
Dog_away | Head | 451±68 | 597±82 |
Body | 619±37 | 534±41 | |
Tail | 42±10 | 54±12 | |
Head+body+tail | 1111±90 | 1184±81 | |
Background | 494±51 | 471±53 | |
Human_toward | Head | 588±112 | 858±141 |
Body | 698±114 | 460±97 | |
Head+body+tail | 1285±105 | 1318±114 | |
Background | 439±56 | 461±92 | |
Human_away | Head | 311±58 | 473±111 |
Body | 666±118 | 549±108 | |
Head+body+tail | 977±114 | 1022±108 | |
Background | 479±73 | 577±83 |
Based on data from all stimulus pictures.
The total fixation durations to the heads and bodies of the creatures (both humans and dogs) did not differ between experts and control subjects (between-subjects factor
The fixation durations to dog tails did not differ between groups nor conditions. However, the head/body ratios of fixation durations were smaller in experts than control subjects in both Dog_toward and Dog_away conditions (head/body ratio of experts 2.2±0.4 and controls 4.2±0.7 during Dog_toward: F21 = 5.3,
The overall brain activations were very similar in both groups: dogs (“Dogs vs. Rest”;
Top panel: Dogs (Dog_toward+Dog_away). Middle panel: Activation to Dogs
The contrast “Dogs
Both groups exhibited stronger activation to human than dog stimuli in the amygdala and the right pSTS, and control subjects also in the left pSTS and inferior temporal gyrus (ITG); the difference was most prominent in the right pSTS of the control subjects (see the blue-green color in the bottom section of
Brain processing influenced by the social interaction within the observed snapshot photos was inspected by contrasting conditions in which humans and dogs were facing toward a conspecific with the conditions in which they were facing away from a conspecific (Human_toward
Brain activation in pSTS in the contrasts Dog_toward>Dog_away (red) and Human_toward>Human_away (blue) and their overlap (yellow) in experts and control subjects. The location of the axial plane is indicated in the coronal image. All contrasts are shown at
In both groups, the pSTS was activated more strongly in the Human_toward than Human_away condition (blue color in
Dog_toward>Dog_away | Dog_toward>Human_toward | ||||||||
Experts | Controls | Experts | Controls | ||||||
Brain area | mm3 | Peak(x, y, z) | mm3 | Peak(x, y, z) | mm3 | Peak(x, y, z) | mm3 | Peak(x, y, z) | |
Supramarginal gyrus (TPJ) | 3952 | 59, −29, 30 | 270 | −59, 28, 28 | |||||
Superior frontal gyrus | 1476 | −4, 49, 30 | |||||||
279 | 2, −5, 60 | ||||||||
1258 | −7, 55, 39 | ||||||||
1343 | −19, −20, 63 | ||||||||
279 | −4, 16, 57 | ||||||||
Middle frontal gyrus | 273 | −22, −14, 39 | 486 | 51, 17, 41 | |||||
Inferior frontal gyrus | 1335 | 41, 16, 15 | 540 | 43, 35, 13 | |||||
37786 | −40, 37, 21 | ||||||||
Inferior frontal sulcus | |||||||||
Cingulate gyrus | 282 | 23, −47, 24 | |||||||
431 | −1, 43, 6 | ||||||||
Insula | 6319 | 47, −11, 6 | |||||||
1946 | 32, −14, 3 | ||||||||
Inferior temporal gyrus | 8515a | 44, −56, −3 | |||||||
Precentral gyrus | 1583 | −46, −8, 39 | |||||||
Superior parietal gyrus | 297 | 23, −59, 60 | |||||||
11186 | −58, −29, 27 | ||||||||
Intraparietal sulcus | 567 | 43, −33, 44 | |||||||
Superior occipital gyrus | 270 | −13, −95, 6 | |||||||
Precuneus | 297 | −3, −70, 56 | |||||||
Parieto-occipital sulcus | 621 | 15, −52, 6 | |||||||
Middle occipital gyrus | 12535b | −28, −80, −18 | 2430 | 27,−84,5 | |||||
4752 | −32, −81, 7 | ||||||||
Calcarine sulcus | 310 | 2, −89, 0 | 23949 | −12,−80,−16c | |||||
Hippocampus | 517 | 26, −29, 12 | 594 | 22, −30, 1 | |||||
431 | −16, −38, −3 | ||||||||
Lingual gyrus | 349 | −10, −86, −18 | 88452c | 10, −76, −19 | |||||
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|
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Amygdala | 324 | 18, −10, −12 | 1566 | 21,−12,−10 | |||||
675 | −18, −16, −13 | ||||||||
pSTS | 9342 | 46,−58,11 | |||||||
756 | −48,−64,6 | ||||||||
351 | −65, −52, 5 | ||||||||
Angular gyrus | 1242 | 51,−66,28 | |||||||
Superior frontal gyrus | 1242 | 6,59,37 | |||||||
Lingual gyrus | 525 | −7,−65,−3 |
extends to middle occipital and fusiform gyrus.
extends to inferior temporal and fusiform gyrus and superior temporal sulcus.
extends to calcarine and intraparietal sulcus. All contrasts
Additionally, the the scores of the expertise questionnaires were positively correlated with the magnitudes of brain activity within the pSTS during the “Dog_toward>Dog_away” contrast: all measures correlated statistically significantly with the right pSTS (
Furthermore, the difference between Dog_toward
Left: The locations of the three ROIs vertically adjacent to each other overlaid on the cortical surface. Right: Experts had stronger differences between Dog_toward – Dog_away conditions than control subjects at the two most ventral ROIs of right hemisphere (z = −1 and z = −6). There were no group differences in the signal change between Human_toward – Human_away conditions. ** p = 0.01, *** p<0.001.
Instead, the groups had equal response differences between Human_toward
In the Dog_toward vs. Human_toward contrast (
Differences in brain activation between Dog_toward and Human_toward at
In agreement with our expectations, the brain regions involved in processing of social interaction between humans also seemed to support observation of social interaction of dogs. The overall activation during observation of dogs (“Dogs vs. Rest”) was very similar in dog experts and control subjects, comprising areas that have been previously associated with socio-emotional processing, such as analysis of human bodies
Both dog experts and control subjects had stronger activation to dog than pixel images (“Dogs vs. Pixels”) in the temporal poles, pSTS, and posterior cingulate cortex,
Previously, dmPFC activation has been often observed during tasks that require the subjects to make mental state inferences of persons whose gestures they do not see (e.g.
In one of the rare studies where subjects were observing two-person interactions, dmPFC activation differentiated “communicative intentions” from “private intentions”
According to the IRI scores, the general empathy and perspective-taking abilities of our dog expert and control groups did not differ. Although the IRI samples empathy and perspective-taking toward humans instead of animals, one could have assumed that dog experts have over-developed perspective-taking abilities. Our results do not support this view, as the perspective-taking scores were not different between the groups. Altogether, our data thus suggest that expertise in dog behavior is not explained by differences in the mentalizing abilities between dog experts and control subjects. Instead, dog expertise seems to be more related to improved visual reading of the dogs' body postures. This interpretation is supported by the eye-tracking data that showed that the experts, compared with the control group, gazed relatively more the dog bodies than dog heads.
The main aim of the present study was to investigate how the experience-derived expertise in dog behavior affects brain activation related to inspection of body postures reflecting social interaction between dogs. During observation of dog photos, activity in the frontal, temporal and parietal areas in the expert group, but not in the control subjects, differed between dogs facing toward and dogs facing away from each other. Furthermore, the lateral temporo-occipital cortex (pSTS region) was activated similarly in both groups to human photos but differently to dog photos. The dog experts' pSTS activation overlapped in the Human_toward>Human_away and in the Dog_toward>Dog_away contrasts, whereas in control subjects, the pSTS was activated only in the Human_toward>Human_away contrast.
The voxel cluster that showed a significant signal change in dog experts in the Dog_toward
Recently, the pSTS has been shown to differentiate human motion from dog motion
Additionally, the positive correlation between the pSTS activation of both hemispheres with the involvement of the subjects in dog behavior (the questionnaire factor
Furthermore, the group comparison of signal changes within the ROIs in the temporo-occipital cortex showed that the signal difference between the Dog_toward and Dog_away conditions was stronger in experts than in control subjects in all ROIs of the left hemisphere and in the two most ventral ROIs of the right hemisphere. Thus also the lateral occipital cortex that is sensitive to object processing seems to be involved in the expertise of other species, especially in the right hemisphere. In fact, the common stimuli used in functional localization of the object-selective cortex include pictures of living creatures such as cats
Earlier, expertise-related modulation of brain activity has been demonstrated in the fusiform gyrus in
The total fixation durations to ROI regions (heads, bodies or tails) did not differ statistically significantly between experts and control subjects. In general, dog heads were fixated longer than human heads regardless of the condition, which may be due to the relatively bigger area of the stimuli covered by dog than human heads (mean 4704 vs. 2942 pixels, respectively). The total fixation time to both human and dog heads was longer in the toward than away conditions. The differences may be affected by the structure of the photos: in the toward conditions, the heads of both dogs and humans were close to each other–and close to the center of the photo–whereas in the away conditions, the distance between the heads was longer (as was the time between the fixations to the creatures). Alternatively, since gaze following is rather automatic (for a review, see
Independently of the above low-level visual factors, the head/body ratio of fixation durations was smaller for experts than control subjects in both Dog_toward and Dog_away conditions, suggesting that the dog experts' gaze, compared with the control subjects' gaze, landed relatively longer to dog bodies than dog heads. The eye gaze is strongly task-dependent
Importantly, the head/body ratio effect applied both to Dog_toward and Dog_away conditions, suggesting that the differences in brain activation observed in the pSTS and inferior temporo-occipital regions of experts between Dog_toward and Dog_away conditions were not due to differences in the fixation duration. However, the eye gaze data suggest that the experts were able to extract the social bodily gestures in both conditions better than control subjects, enabling them to distinguish the social situation.
The present study explored similarities and differences in neural processing of socially relevant body postures of humans and dogs. Both in experts and control subjects, observing photos of two interacting dogs elicited activation in the social brain circuitry in a very similar fashion than was previously shown for observing two interacting humans
The contrasts “Dogs vs. Humans” and “Dog_toward vs. Human_toward” also show stronger activations to humans than dogs in pSTS and amygdala. The pSTS activity was modified by expertise in dog behavior, but the activity in the amygdala was stronger for humans than dogs in both groups, regardless of the dog expertise. Activation in amygdala was stronger for humans than dogs in general (Dogs
Altogether 42 healthy subjects participated in the measurements: 3 subjects in the pilot recordings, and 20 dog experts and 19 control subjects in the main study that comprised simultaneous fMRI and eye gaze measurements; subsequently, the subjects filled in behavioral questionnaires sampling empathy, exposure to dog behavior and mental state attribution (see details of the participants in
Measurement | Group | Subjects analyzed | Age/years (mean ± SD) | Females | Males |
fMRI+Behavioral questionnaires | Dog experts | 19 | 30.1±5.3 | 11 | 8 |
Control subjects | 18 | 28.3±6.8 | 9 | 9 | |
Eye tracking | Dog experts | 12 | 30.1±5.4 | 8 | 4 |
Control subjects | 11 | 27.0±7.3 | 4 | 7 |
Since experience plastically modifies neural function
In the fMRI analysis, data from 2 female subjects were discarded due to excessive head motion, and thus both fMRI data and behavioral questionnaires were fully analyzed from 19 experts (11 females and 8 males, 18–39 years, mean ± SD 30.1±5.3 years) and 18 control subjects (9 females and 9 males, 19–41 years, mean ± SD 28.3±6.8 years). The subject age did not differ statistically significantly between the groups (t36 = 0.9,
Successful eye gaze recordings were obtained from 12 dog experts (8 females, 4 males, 18–43 years, mean ± SD 30.1±5.4 years) and 11 control subjects (4 females, 7 males, 19–41 years, mean ± SD 27.0±7.3). The subject ages did not differ between the groups (t21 = 1.9,
After the fMRI acquisition, the subjects filled in a background questionnaire concerning their expertise of dog behavior, with answers distributed to a five-point scale from 0 (min) to 4 (max), and an empathy questionnaire (Interpersonal Reactivity Index, IRI by
The questionnaire also included free space for elaborating the subject's dog- training expertise or other involvement in dog breeding, agility sports, obedience training, or equivalent. Moreover, the subjects were encouraged to write free commentaries on stimulus photos or the experiment to reveal their attention and reasoning during the scan. To check whether participants inferred the mental states of the individuals, one of the experimenters reviewed the free recall answers for descriptions of mental states or social references (“happy”, “playful”, “acting like they don't notice the other”, “were getting along well”), and tested them with the nonparametric independent-samples Mann-Whitney U-tests and Wilcoxon signed ranks tests.
Multivariate general linear model (GLM) was used to reveal possible statistically significant differences in empathy subscales between experts and control subjects, as well as between males and females, and the statistical significance of differences between experts and control subjects in the questionnaire scores was tested with the nonparametric Kolmogorov-Smirnov test.
For stimulus materials, students from the Theatre Academy of Finland and dogs and their owners from the local dog club (Espoon koirakerho) were recruited as “actors” in two separate filming sessions in the sand fields of nearby recreational parks. Both humans and dogs were filmed and photographed individually while they were inspecting their surroundings, and together with a conspecific while they were either ignoring or interacting with one another. This procedure resulted in 3810 still photos.
Ten photos from 4 actor pairs and 4 dog pairs were selected in both conditions, resulting in 40 photos per category. The pictures fulfilled the following criteria:
Some digital manipulation (e.g. removing human owners and the leash from a few dog photos) was done using Adobe® Photoshop® (version 7.0). The color schemes of the photos were equalized using Adobe® Photoshop® Lightroom® (version 1.3). Finally, a random sample of 40 stimulus photos from all human and dog categories were pixelated and crystallized (25 of them turned upside down to make identification of figures harder) to create a visual control category of pixel photos showing no social communication nor complete objects, yet consisting of separate observable shapes (see
This process resulted in 200 photos, comprising 5 categories of 40 images in each. The images were of 4 different actors per species, each appearing in 20 stimuli per category:
The images, displayed on a projection screen by a data projector (Christie Vista ×3, Christie Digital Systems Inc., USA), were 640×480 pixels in size (width×height, 20 cm×14 cm on the screen), overlaid on a gray background of 1024×768 pixels and presented with a frame rate of 75 Hz. Stimulus presentation was controlled with Presentation® software (
The stimuli were viewed binocularly at a distance of 34 cm within a block design. Each stimulus was shown for 2.5 s in a continuous 25-s stimulus block, 10 stimuli per block, and the block alternated with 25-s rest blocks with a fixation cross on a grey background. The recording sessions started and ended with rest blocks, so that each session comprised 14 stimulus blocks and 15 rest blocks. The stimulus sequence also included blocks of photos of single humans and dogs in the same surroundings to establish a baseline of visual object perception. However, to emphasize the results between stimulus classes of “toward” and “away” categories, the single human and dog photos were excluded from the present study. The data were gathered in two successive recording sessions (each 12 min 5 s in duration, with 140 different stimuli presented in a pseudorandomized order). The order of the sessions was counterbalanced across subjects.
Prior to the experiment, the subjects were informed that they would see images of people and dogs, as well as abstract pixel compositions. They were instructed to explore the images freely and inspect the attitude of the beings towards one another or towards their surroundings, whenever possible. They were also asked to avoid overt and covert verbalizing and to keep the head still.
The magnetic resonance data were acquired with whole-body General Electric Signa® 3.0T MRI scanner at the Advanced Magnetic Imaging Centre. During the experiment, the subject was resting in the scanner, facing upwards and viewing the stimulus images through a mirror attached to the 8-channel head coil.
Functional MR images were acquired using a gradient-echo planar imaging sequence with field of view = 240×240 mm2, time of repetition = 2500 ms, time to echo = 32 ms, number of excitations = 1, flip angle = 75°, and matrix size = 64×64. Before the presentation of the visual stimuli, six dummy volumes were acquired allowing the MR signal to stabilize. Altogether 42 slices (thickness 3.0 mm) were acquired in an interleaved order. The resulting functional voxels were 3.75×3.75×3 mm3 in size.
Structural T1-weighted images were acquired using a spoiled-gradient echo sequence with a matrix size of 256×256, time of repetition 9.2 ms, field of view 260×260 mm2, flip angle of 15°, and slice thickness of 1 mm, resulting in 1×1.016×1.016 mm3 voxels.
The fMRI data were analyzed with BrainVoyager QX software version 1.10.2/3 (Brain Innovation B.V., The Netherlands). Preprocessing included slice scan time correction and 3D motion correction with first volume as a reference, linear trend removal and high-pass filtering at 0.008 Hz.
Functional and anatomical data were iso-voxelated to 3×3×3 mm3 and 1×1×1 mm3 voxels, respectively, and normalized to the Talairach space
Whole-brain analysis was conducted for identification of the activation differences during different stimulus conditions, separately for expert and control groups. Brain activations were subjected to statistical analysis using random effects general linear model (RFX-GLM), and the individual time courses were normalized using z-transformation. The predictors for RFX-GLM were obtained by convolving the time courses of the stimulus blocks with a canonical hemodynamic response function to reveal blood-oxygenation-level-dependent (BOLD) activations.
Main effects of dog stimuli were inspected with a bi-directional statistical map, showing contrasts in both directions within the whole brain, of “Dogs
All statistical maps were corrected for multiple comparisons according to false discovery rate (FDR,
Since we were specifically interested in the expertise effects within the temporal-lobe areas responsive for perception of body postures and biological motion
The subjects' eye gaze was tracked with SMI MEye Track long-range eye tracking system (Sensomotoric Instruments GmbH, Germany) to compare the number and duration of fixations around human and dog bodies in experts and control subjects. The tracking method is based on video-oculography and dark pupil–corneal reflection.
The infrared camera was set at the foot of the bed to monitor the subject's eye via a mirror attached to the head coil, and an infrared light source was placed on the mirror box to illuminate the eye. The camera was shielded properly (in house) and did not affect the signal-to-noise ratio of the fMRI data. The eye tracker was calibrated prior to the experiment using 5 fixation points, and the data were collected at a sampling rate of 60 Hz.
The eye gaze patterns (successful recordings obtained for 11 control subjects and 12 dog experts) were analyzed with Begaze 2.0 (Sensomotoric Instruments GmbH, Germany). Eye blinks were removed from the data and fixations were detected with a dispersion-threshold identification algorithm, using a 2° dispersion window and 120 ms as the minimum fixation duration. Gaze maps were then calculated separately for individual stimuli, by overlying the fixations of all subjects and by smoothing the data with a gaussian kernel of 70 pixels. Thereafter the average fixation duration was computed across subjects at each pixel and was color-coded for average fixation durations from 5 ms to 200 ms or more (
Eye movements between experts and control subjects were compared from all Human_toward, Human_away, Dog_toward and Dog_away stimuli (40 photos per category). For each photo, regions of interest were drawn manually around human heads and bodies as well as dog heads, bodies and tails and the remaining background image area, for which the subjects' total fixation durations were calculated.
The total fixation durations of experts and control subjects in each ROI were compared with a repeated-measures analysis of variance (ANOVA) with a between-subjects factor “
We thank V.-M. Saarinen for carrying out the eye tracking measurements and the preliminary data analysis, S. Vanni for advice for the control stimuli, M. Kattelus for the help in fMRI measurements, L. Hirvenkari for the assistance with the empathy scales, S. Malinen and M. Seppä for comments on data analysis, and Espoon koirakerho and Theatre Academy Helsinki for the help in producing the stimuli.