Grant: Discovery Grants Program - Individual

One of the greatest challenges faced by the brain is predicting the dynamic behaviours of other individuals, meanwhile updating motor plans according to those predictions. The potential variability of others means that social interaction is inherently uncertain, particularly between strangers. Research in human and non-human primates suggest that the premotor cortex uses social information to form movement plans; however, these studies primarily require movements to be restricted, reducing the dimensions of uncertainty and raising questions about ethological validity. The overarching goal of our research program will be to understand how freely moving animals dynamically update movement plans according to their expectations and uncertainties about another individual. We will develop and apply novel behavioural analysis methods and record from neuron population of the premotor cortex to test how actions are dynamically influenced by other individuals. In order to understand the role of uncertainty on social planning and updating, we will compare patterns between conditions of putatively higher versus lower uncertainty using, respectively, novel versus familiar social contexts. In many species, encounters with strangers can quickly result in aggressive behaviour. To minimize this, while also broadening the significance and impact of the experiments, we will leverage the gregariousness and nuanced social behaviours of a non-traditional rodent model, Octodon degus (the degu). The research program will generate a new, openly available software package for analyzing social movement while also testing several specific hypotheses on how motor regions of the brain use information about other individuals to determine behaviour. Sex differences in movement updating will also be examined, as our past work shows that male and female degus engage differently in new relationships. This research program will add to our understanding of social coordination and intelligence, and may even guide efforts to engineer interactive artificial systems. The projects are also ideally suited for diverse and inclusive training at undergraduate, graduate, and postdoctoral stages. Trainees will have individual projects and mentoring, with emphasis on communication, organization, and problem-solving skills, while also developing expertise in behavioural neuroscience and computer programming. The scope of research topic and training fill a niche within Canada, with promise for future impact and successful HQPs.