Spencer A. Arbuckle

This study uses fMRI to show non-linear interactions between fingers in human S1 and M1, revealing how sensory inputs are integrated for dexterous manipulation.

The paper compares fMRI and electrophysiological data to explore how primary motor cortex organizes activity for finger flexion and extension, finding similar patterns for same-finger movements but distinct patterns in monkeys.

The paper tests the stability of representational geometry in fMRI data across varying activation levels in sensory-motor and visual regions, finding it remains consistent despite large changes in average activity.

This study investigates whether human primary motor cortex represents sequences of finger movements and finds no evidence for true sequence representation, instead showing patterns explainable by individual movement components.

This paper introduces pattern component modeling (PCM), a Bayesian approach for evaluating representational models of brain activity, and provides an open-source Matlab toolbox for implementation.