Kavli Affiliate: Anirvan Nandy
| Authors: Feng Xing, Alec Graham Sheffield, Monika P. Jadi, Steve W. C. Chang and Anirvan S. Nandy
| Summary:
Social communication relies on the ability to perceive and interpret the direction of others’ attention, which is commonly conveyed through head orientation and gaze direction in both humans and non-human primates. However, traditional social gaze experiments in non-human primates require restraining head movements, which significantly limit their natural behavioral repertoire. Here, we developed a novel framework for accurately tracking facial features and three-dimensional head gaze orientations of multiple freely moving common marmosets (Callithrix jacchus). To accurately track the facial features of marmoset dyads in an arena, we adapted computer vision tools using deep learning networks combined with triangulation algorithms applied to the detected facial features to generate dynamic geometric facial frames in 3D space, overcoming common occlusion challenges. Furthermore, we constructed a virtual cone, oriented perpendicular to the facial frame, to model the head gaze directions. Using this framework, we were able to detect different types of interactive social gaze events, including partner-directed gaze and jointly-directed gaze to a shared spatial location. We observed clear effects of sex and familiarity on both interpersonal distance and gaze dynamics in marmoset dyads. Unfamiliar pairs exhibited more stereotyped patterns of arena occupancy, more sustained levels of social gaze across inter-animal distance, and increased gaze monitoring. On the other hand, familiar pairs exhibited higher levels of joint gazes. Moreover, males displayed significantly elevated levels of gazes toward females’ faces and the surrounding regions irrespective of familiarity. Our study lays the groundwork for a rigorous quantification of primate behaviors in naturalistic settings.