Topic: social interactions

Liz Fearon describes a project that involves members of the public as equal participants in creating mathematical models. The discussion asks how models used in public-health policy and other decisions can reflect lived experience, social interactions and community priorities. It explores the motivation, working methods and aims of co-production in epidemiological modelling.

Effectively modeling and quantifying behavior is essential for our understanding of the brain. Modeling behavior in naturalistic settings in social and multi-subject tasks in a unified manner remains a significant challenge. Modeling the behavior of different subjects performing the same task requires partitioning the behavioral data into features that are common across subjects, and others that are distinct to each subject. Modeling social interactions between multiple individuals in a freely-moving setting requires disentangling effects due to the individual as compared to social investigati

Peripersonal space (PPS) defines the portion of space where interactions between our body and the external environment more likely occur. There is no physical boundary defining the PPS with respect to the extrapersonal space, but PPS is continuously constructed by a dedicated neural system integrating external stimuli and tactile stimuli on the body, as a function of their potential interaction. This mechanism represents a primary interface between the individual and the environment. In this talk, I will present most recent evidence and highlight the current debate about the neural and computa

This talk will focus on the importance of using natural behaviors in neuroscience research – the “Natural Neuroscience” approach. I will illustrate this point by describing studies of neural codes for spatial behaviors and social behaviors, in flying bats – using wireless neurophysiology methods that we developed – and will highlight new neuronal representations that we discovered in animals navigating through 3D spaces, or in very large-scale environments, or engaged in social interactions. In particular, I will discuss: (1) A multi-scale neural code for very large environments, which we dis

My lab is focused on how brain encodes and modulates social interactions. Intraspecific social interactions are integral for survival and maintenance of society among all mammalian species. Despite the importance of social interactions, we lack a complete understanding of the brain circuitry involved in processing social behaviour. My lab investigates how the hypothalamic orexin (hypocretin) neurons and their downstream circuits participate in social interaction behaviours. These neurons are located exclusively in the hypothalamus that regulates complex and goal-directed behaviours. We recentl

Body motion is a fundamental signal of social communication. This includes facial as well as full-body movements. Combining advanced methods from computer animation with motion capture in humans and monkeys, we synthesized highly-realistic monkey avatar models. Our face avatar is perceived by monkeys as almost equivalent to a real animal, and does not induce an ‘uncanny valley effect’, unlike all other previously used avatar models in studies with monkeys. Applying machine-learning methods for the control of motion style, we were able to investigate how species-specific shape and dynamic cues

Our research explores the neural mechanisms underlying flexibility during natural social interactions - how animals process dynamic sensory cues from a partner, make decisions, and pattern the appropriate action for the current context. During Drosophila social interactions, males produce time-varying songs via wing vibration, while females arbitrate mating decisions. We discovered that male song structure and intensity are continually sculpted by the movements of the female, over timescales ranging from tens of milliseconds to minutes, and we have investigated the underlying circuit mechanism