Dissecting brain-wide functional circuits underlying social decision making by developing a naturalistic virtual reality platform of juvenile zebrafish
Aperçu du projet
Understanding how the brain works when we make decisions during social interactions has been difficult for neuroscientists. This is because our brains process multiple things all at once all the time, and different regions of the brain need to communicate with each other to process information. Previous studies have found some brain areas involved, and their neural activities have been characterized. But there remain two major issues: first, neuroscientists often study these brain areas separately, one by one, and thus not knowing how they work together; and second, the behavioral experiments that have been designed to understand social interactions are usually static, and less natural like in real life. Therefore, we want to know how the whole brain works together when we make decisions during social interactions moment-by-moment in a more natural configuration.
For this, we will solve two problems: first, we need to be able to look at the whole brain at once at high speed and monitor each neuron; and second, we need to create a more natural experience for animals in the experiments, so they will behave like they would in the real world. We will develop a virtual reality platform for juvenile zebrafish, where zebrafish can have virtual social interactions, and at the same time, we can monitor their whole-brain neural activity. We will focus on their shoaling behavior, and test how they will behave in response to fish-like moving dots, and fish-like appearance.
Together, we hope to understand how the brain as a whole system regulates social interactions. Because many involved brain regions and neural pathways are highly conserved across vertebrates, what we learn from studying zebrafish could help us understand social behavior in mammals like us. This knowledge will be very useful in understanding and treating disorders that affect social skills.
Chef d'équipe
Qian Lin , The University of Toronto