Title: Investigating the role of the cerebellum in hippocampal state estimation during spatial navigation

The cerebellum is increasingly recognized as contributing to cognition as well as motor control, yet how cerebellar computations interact with hippocampal networks to support spatial navigation remains unclear. This project will test whether cerebellar output contributes causally to hippocampal state estimation, a process that integrates self-motion-based prediction with landmark-based error correction to maintain accurate spatial representations. Using a virtual reality environment, we will impose controlled mismatches between self-motion and visual landmark cues while recording hippocampal activity with Neuropixels 2.0 probes and transiently perturbing the deep cerebellar nuclei output with optogenetics. By combining causal circuit manipulation, large-scale neural recording, and a quantitative state-estimation framework (Kalman filter), this work will define how cerebellar output supports the stability and adaptive updating of hippocampal spatial codes, providing new insight into cerebellar-hippocampal interactions in spatial cognition.