Jeremy Dan Schmahmann

The paper creates a high-resolution digital anatomical atlas of the human cerebellum at the level of individual folia, enabling detailed analysis and visualization of cerebellar data.

The paper identifies structural covariation patterns between cerebellum subregions and cerebral cortex in a large cohort, revealing dissociations and novel associations with phenotypes.

This study quantifies volumetric morphometry and optical properties of human cerebellar cortex at micrometer resolution using as-PSOCT, revealing layer-specific variations and cross-subject variability.

The paper investigates interhemispheric functional symmetry in human subcortical structures using fMRI data, finding that direct cortical connectivity correlates with stronger subcortical symmetry in some regions, while connectivity to symmetric cortical areas correlates with symmetry in others.

This paper identifies three functional territories in the human dentate nucleus using resting-state MRI, showing their unique contributions to default-mode, salience-motor, and visual brain networks.

LittleBrain visualizes cerebellar neuroimaging data along newly identified functional gradients to enhance topographical interpretation.

The paper tests the UCT theory by showing that cerebellar functional specialization is independent of microstructural variation, unlike the cerebral cortex.

The paper identifies two functional gradients in the cerebellum using diffusion map embedding on resting-state data, revealing a progression from motor to transmodal regions and task-unfocused to task-focused processing.

The paper analyzes cerebellar fMRI task activation and resting-state connectivity in a large cohort, revealing triple representations for non-motor cognitive and affective tasks.