Abstract 
How does the brain generate and refine predictions to guide behavior? Although both the cerebellum and neocortex have been independently linked to predictive processing, their interaction remains poorly understood. Understanding this coordination is essential for uncovering how distributed brain networks support flexible motor and cognitive functions, and how their dysfunction contributes to disorders such as ataxia and autism. 

In this talk, I will share emerging work from my lab at Georgia Institute of Technology that begins to address this gap. Using a set of temporally structured behavioral paradigms in mice, ranging from passive to active perception to self and externally timed movements, we combine two-photon calcium imaging, circuit-targeted optogenetics, and computational work to study predictive dynamics in the cerebellum and parietal cortex. Early results suggest that temporal information in the parietal cortex may be modulated by cerebellar output, particularly during active behaviors. Specific neuronal subtypes, such as VIP interneurons, appear to play distinct roles in shaping prediction-related signals. 

These findings motivate a broader framework for cerebello-cortical mutual interaction during predictive processing. I will outline our long-term vision to uncover the circuit mechanisms and computational principles that govern this interaction, and discuss how this work could reshape our understanding of large-scale brain function across health and disease.