Pupillary contagion is an involuntary change in the observer’s pupil size in response to the pupil size of another person. This effect, presumed to be an important adaption for individuals living in groups, has been documented in both typical infants and adults. Here, for the first time, we report pupillary contagion in individuals with autism, a disorder of social communication. We found that, compared with a typical group ( n = 63), individuals with autism ( n = 54) exhibited comparable pupillary contagion when observing pictures of emotional faces, despite less spontaneous attention toward the eye region. Furthermore, the magnitude of the pupillary response in the autism group was negatively correlated with time spent fixating the eye region. The results suggest that even with less looking toward the eyes, individuals with autism respond to the affective and arousal levels transmitted from other individuals. These results are discussed in the context of an overarousal account of socioaffective-processing differences in autism.

Typically, developing humans innately place subjective value on social information and orient attention to it. This can be shown through tracking of gaze patterns and pupil size, the latter of which taps into an individual's cognitive engagement and affective arousal. People with Autism Spectrum Disorder (ASD) present with atypical social, communicative and behavioral patterns, but underlying substrates of these behavioral differences remain unclear. Moreover, due to high comorbidity with other neurodevelopmental disorders, it is often difficult to distinguish which differences are distinctive to ASD. In this study, a group of 35 adolescents and young adults with neurodevelopmental disorders were tested to investigate the processing of social and non-social scenes in individuals who meet the diagnostic criteria for autism and those who do not. Eye tracking and pupillometry measures were collected while participants observed images of tightly controlled natural scenes with or without a human being. Contrary to individuals without autism diagnosis, participants with autism did not show greater pupillary response to images with a human. Participants with autism were slower to fixate on social elements in the social scenes, and this latency metric correlated with clinical measures of poor social functioning. The results confirm the clinical relevance of eye-tracking and pupillometric indices in the field of ASD. We discuss the clinical implications of the results and propose that analysis of changes in visual attention and physiological level to social stimuli might be an integral part of a neurodevelopmental assessment.

Do infants perceive other people's interactions by means of a mechanism that integrates biological motion information across the observed individuals? In support of this view, the present study demonstrates that infants (N = 28, Age  = 14 months) discriminate between point light displays representing disrupted and non-disrupted interactions between people, even though the two interaction types are identical at the level of individual point light agents. Moreover, a second experiment (sample 2: N = 28, Age  = 14 months) indicated that visual preference in this context is influenced by an audiovisual integration processes that takes into account the presence of an interaction between people. All these results were found exclusively for upright displays – when stimuli were shown upside-down (disrupting biological motion processing), performance was random. Collectively, these findings point to an important role for biological motion in social perception in human infants.

No abstract

Quantification of face-to-face interaction can provide highly relevant information in cognitive and psychological science research. Current commercial glint-dependent solutions suffer from several disadvantages and limitations when applied in face-to-face interaction, including data loss, parallax errors, the inconvenience and distracting effect of wearables, and/or the need for several cameras to capture each person. Here we present a novel eye-tracking solution, consisting of a dual-camera system used in conjunction with an individually optimized deep learning approach that aims to overcome some of these limitations. Our data show that this system can accurately classify gaze location within different areas of the face of two interlocutors, and capture subtle differences in interpersonal gaze synchrony between two individuals during a (semi-)naturalistic face-to-face interaction.