Grant: Discovery Grants Program - Individual

The long-term vision of my research program is to understand how spatiotemporal dynamics in cortex drive sensory perception and cognition. My lab pursues this vision through a combined theory- and data-driven approach. In this research, my team develops new computational algorithms to study moment-by-moment dynamics in neural recordings at the single-trial level. The signal processing techniques I have developed have revealed stimulus-evoked traveling waves in primary visual cortex of the awake monkey, global rotating waves associated with learning and memory during sleep, and even spontaneous traveling waves occurring in the absence of sensory input. These results have shaped our fundamental understanding of the dynamic structure in cortical activity during wake and sleep. In this Discovery Program, we will develop new computational and mathematical approaches to understand general spatiotemporal patterns of activity. We define patterns that repeat more often than chance to be spatiotemporal motifs. These are more general than traveling waves, which represent activity patterns smoothly traveling across neural systems, and can represent complex spatiotemporal patterns of activation. The new computational tools we will develop in this Program will allow us to detect and analyze spatiotemporal motifs, providing substantial insight into the structure of spontaneous and stimulus-evoked neural activity. In Objective 1, we will develop new and general computational tools to detect and analyze repeated spatiotemporal motifs in multisite recordings. In Objective 2, we will use these techniques to characterize the spatiotemporal structure of cortical activity across cortical areas, across species, and across wake and sleep. In Objective 3, we will leverage recent computational and theoretical advances from my team to understand the underlying network mechanisms for spatiotemporal motifs in single cortical regions and at the whole-brain scale. We will use simulations of spiking network models and networks of nonlinear oscillators to understand how repeated spatiotemporal motifs can occur in neural recordings. Results from this research will provide fundamental insight into the spatiotemporal dynamics of cortical circuits, which we have recently found to have significant impacts on sensory and cognitive processing.