Neural signatures of virtual and real-world navigation and spatial learning

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PROJECT SUMMARY Navigation is one of our most foundational behavioral capacities, and substantial work using rodent models has established the hippocampus as a critical contributor to this complex behavior. However, efforts to model these effects in humans have been limited, both in scope and generalizability. Little work has explored the interaction in the hippocampus between navigation and foundational non-navigation learning processes, like statistical learning, and it therefore remains unclear how navigation processes are integrated with and may be supported by these learning mechanisms. Further, studies in humans have primarily consisted of virtual navigation, limiting applicability and relevance of the established neural signals to real-world navigation behavior. Understanding how navigation and statistical learning compete or cooperate in the human hippocampus will significantly inform models of memory systems and consolidation, and addressing these questions in a real-world paradigm will close a wide gap in our understanding of human navigation. This requires a multimodal approach, coupling the high temporal and spatial resolution of intracranial EEG (iEEG) in epilepsy patients with quantitative behavioral measures of human navigation and learning. In my doctoral dissertation work thus far, I have used behavioral, computational, and iEEG methods to test hypotheses about the interaction between statistical learning and spatial navigation in the human hippocampus and related structures. My work has produced impactful findings via novel computational modeling techniques and innovative multivariate iEEG analyses. In my proposed research and training program, I will use a cutting-edge research method to collect direct neural recordings from chronic brain implants in human participants as they physically ambulate in the real world. Through my multidisciplinary research mentors, this experience will provide me training with novel research methodology and ecologically valid experiment design, as well as clinical perspectives, considerations, and practices for working with patients with epilepsy. In my proposed postdoctoral training phase, I will pursue a more clinical focus, returning to the question of how modern cognitive neuroscience can guide assessments and therapies for hippocampal disease. I will gain theoretical and practical experience with high-resolution imaging and data collection with hippocampal atrophy populations, including epilepsy and Alzheimer’s patients. This research program has the potential to inform and substantially extend models of human navigation and memory by exploring the intersection of multiple processing demands on the hippocampus as a shared neural resource, and how these processes operate in the real world. This work represents the convergence of disparate literatures on hippocampal function, and informs diagnosis and treatment of hippocampal patients. This program will equip me not only with expertise in behavioral, computational, and neuroscientific methodologies, but the basic and clinical theoretical acumen necessary to conduct independent investigation as a principal investigator across disciplines.