Ladan Shahshahani

This paper introduces a hierarchical Bayesian framework that fuses task-based and resting-state neuro-imaging datasets to create a population-based atlas of the human cerebellum, achieving better individual parcellations with limited data.

This paper presents a hierarchical functional atlas of the human cerebellum integrating multiple datasets, improving individual precision mapping and enabling analysis at different levels of granularity.

The paper investigates task-dependent gating of neocortical inputs to the cerebellum using fMRI, finding that cerebellar activity increases more than expected during speed-related tasks and working memory encoding.

The paper builds and compares cortico-cerebellar connectivity models using task-based fMRI to determine if cerebellar regions receive convergent or sparse cortical inputs, finding convergence varies across functional cerebellar areas.