Abigail L. Person

The paper investigates how Purkinje cell firing rates and synchrony contribute to motor control by analyzing their relationship with mouse reach kinematics.

The paper shows that corrective sub-movements during mouse reaching are encoded in cerebellar neurons and instructively shape future feedforward control through timing-based learning.

The paper develops a biomechanical model of the mouse forelimb to predict muscle activity during reaching movements, finding strong similarity between simulated and empirical muscle patterns.

The paper introduces Myomatrix arrays, a high-resolution electrode technology for recording muscle activity from motor units across species during natural behaviors.

This study trains a minimalist cerebellar cortex model to learn time-series data, revealing that dense granule cell activity and task-specific pattern separation features underlie temporal learning.

The paper investigates how cerebellar associative learning influences skilled reach adaptation in mice by analyzing neural responses and optogenetic perturbations.

The paper maps inhibitory projections from the cerebellar interposed nucleus, finding they target diverse brainstem nuclei, contrasting with previously assumed excitatory outputs.

The paper quantifies mouse reach kinematics using analytical frameworks and machine learning, finding conserved primate-like features with notable differences and highlighting kinematic adjustments in motor control.

The paper identifies monosynaptic inputs to excitatory and inhibitory neurons in the intermediate and deep layers of the superior colliculus, revealing differences in input strength and distribution.

This study shows that cerebellar output modulates reach velocity in mice with graded and bidirectional control, acting as a scalable kinematic command signal.

The paper investigates how Golgi cells integrate mossy fiber inputs to regulate granule cell activity in mice, revealing the dominance of slow spillover inhibition.

This study models cerebellar granule cell combinatorial diversity, showing that anatomical constraints lead to input redundancy and support both combinatorial and temporal expansion.