PROJECT SUMMARY The hippocampal formation is critically involved in learning and memory. Neurodegenerative disorders such as Alzheimer’s Disease dramatically impact this area, leading to severe and progressive memory loss. The hippocampus appears to be the locus of an allocentric, cognitive map of the external world. This map is critical not only for spatial cognition, but also for the conscious recollection of past experience. The hippocampus is thought to bind the individual items and events of experience within a coherent spatiotemporal framework, allowing the experience to be stored and retrieved as a conscious memory. Decades of investigation of hippocampal place cells and the recent discovery of grid cells have revealed that this cognitive map arises from the interaction of external sensory inputs with endogenously generated neural dynamics (underlying the navigational strategy known as “path integration”). Classical neurophysiological studies with behaving animals have amply characterized the powerful influence of environmental landmarks on the firing locations of these spatial cells. Extending this approach to quantitatively investigate the internal processes of path integration has proven technically challenging. Virtual reality technology, in combination with systems theory, offers opportunities to solve these problems. We have designed and constructed a novel apparatus that allows us to manipulate the visual inputs (both landmarks and optic flow) available to a rat navigating a real circular track as a function of its movements, while preserving normal ambulatory and vestibular experience. Place cells recorded in this apparatus replicate known standard phenomenology. In preliminary experiments, we induced a sustained, increasing conflict between landmark information and path integration. Results demonstrate the capacity of the system to recalibrate the path integrator when challenged with this sustained conflict. Further, we have developed a novel approach for isolating the contribution of optic flow and other self-motion cues to the update of the neural representation of position, free of the competing influence of landmarks. Specifically, we have developed an online population decoder, and used the decoded output to control this cognitive representation during behavior through real-time feedback manipulations of the optic flow. This approach will form the foundation of a novel research program aimed at a comprehensive analysis of the external vs. internal determinants of the cognitive map. Furthermore, this program promises to reveal important principles of neural computation relevant to general problems of how the brain integrates external sensory input with internal, cognitive representations, ultimately generating insights into the disordered thinking and hallucinations that are characteristic of schizophrenia and other mental disorders. 1