Parietal Cortex Networks for Sensorimotor Processing During Navigation - Project Summary Spatial navigation is essential for the survival of most animals. It requires an understanding of the spatial relationships within an environment and the ability to make decisions about goal locations and how to reach those locations. In our previous grant period, we discovered a multi-area cortical network, with dense inter- communication, that is critical for the decision-making and planning functions in navigation. Our findings revealed that a central component of this network is the posterior parietal cortex (PPC), which is essential for behaviors requiring navigation decisions and has activity at the interface of sensation and action. Despite our work revealing the importance of PPC and a long literature studying the role of PPC in decision-making, remarkably little is known about the mechanisms by which PPC performs its computations, including the connectivity motifs it contains, how these connectivity motifs relate to its function, if and how molecular cell types contribute in distinct ways, and what plasticity programs control its changes over learning. These topics have not been addressed in depth largely because of a lack of tools to provide detailed mechanistic investigation in the context of cognitive behaviors like those for navigational decision-making. Here, we propose to build and use a toolset to study the connectivity, cell types, and plasticity pathways in PPC to discover the mechanisms underlying PPC’s contribution to navigational decision-making. In a first aim, we will use cellular resolution optogenetics to map the effective connectivity between functionally characterized neurons in PPC during a navigation decision task in virtual reality. We will test for connectivity motifs proposed by theoretical models of decision-making and information propagation. In a second aim, we will study the activity patterns and connectivity motifs of inhibitory neurons in PPC and test their causal roles in computations related to navigational decision-making. In a third aim, we will investigate the molecular plasticity mechanisms that are activated during navigational learning and that give rise to the activity patterns in PPC. We will study how these plasticity mechanisms reorganize the connectivity within the circuit. Together, the proposed research will be some of the first to understand PPC and decision-making at a detailed mechanistic level of connectivity motifs, cell types, and plasticity programs. Furthermore, we anticipate that the findings and approaches will be of interest for understanding mechanisms of cognitive function more generally.
