From the field to the lab and back: neuroethology of primate social behavior

Abstract

Social mammals with more numerous and stronger social relationships live longer, healthier lives. Despite the established importance of social relationships, our understanding of the neurobiological mechanisms by which they are pursued, formed, and maintained in primates remains largely confined to highly controlled laboratory settings which do not allow natural, dynamic social interactions to unfold. In this review, we argue that the neurobiological study of primate social behavior would benefit from adopting a neuroethological approach, that is, a perspective grounded in natural, species-typical behavior, with careful selection of animal models according to the scientific question at hand. We highlight macaques and marmosets as key animal models for human social behavior and summarize recent findings in the social domain for both species. We then review pioneering studies of dynamic social behaviors in small animals, which can inspire studies in larger primates where the technological landscape is now ripe for an ethological overhaul.

Figure 1.. Neural synchrony in socially interacting bats (A-B), mice (C-F) and birds (G-I).

(A-B) Wireless recordings from the frontal cortex of freely behaving pairs of bats, which exhibited a range of both social and non-social behaviors, such as grooming or foraging (A), and showed high inter-brain synchrony. (B) Mean normalized LFP power in the 30–150 Hz band during an example session, simultaneously recorded from two bats. Annotated behaviors are shown above. (C-F) Calcium imaging of neural activity from dmPFC neurons in freely behaving mice revealed inter-brain synchrony. Mice were studied in contact or separated (C). (D) Calcium traces of overall dmPFC activity (mean activity) revealed higher inter-brain correlation in mice that were in contact (E) and that were socially interacting (F). (G-I) Electrophysiological recordings from song birds’ HVC during duetting in their natural habitat (G), using wireless vocal and neuronal transmitters (H). (I) Vocalizations were locked to bursts of premotor HVC activity in the singing bird. Male, blue; female, red. Top panel: neural traces. Middle panel: spectrogram. Lower panel: vocal amplitude. Both male and female are shown for exemplary duet bouts initiated by the female. Solid dark blue and dark red lines outline the root-mean-square envelope of neural and vocal signals. Times of spike occurrence are indicated by blue rasters. Note the precise alternation of neural bursts between interacting males and females. Panels A-B adapted from [56], panels C-F adapted from [57] and panels G-I adapted from [59], with permission.

Figure 2.. Pose tracking in naturalistic 3D environments and real-time reinforcement of automatically detected behaviors.

(A) Schematic depiction and spatial arrangement of various EthoLoop components. Multiple infrared cameras (cameras 1–3) with dedicated GPUs process images from different viewing angles. The identity and positions of the detected markers are wirelessly transmitted to a central host computer for 3D reconstruction (triangulation, followed by rotation and transition into real-world 3D coordinates). 3D coordinates are forwarded to control the position and focus of a mounted close-up camera. (B) The images from the close-up system are either saved for offline analysis or processed on-the-fly to trigger optogenetic activation of the animal’s reward system. The close-up camera provides high-resolution live images of the tracked animal, the body parts are then classified in real time using a pre-trained deep-learning network (DeepLabCut). If there is a match between the annotated live image and a geometric model of the posture, a behavioral event is detected. This detection wirelessly triggered the optogenetic stimulation through a portable, battery-powered stimulator. Content adapted from [64], with permission.