Wilson Truccolo

The paper shows top-down semantic predictions align phonetic neuronal dynamics in the human superior temporal gyrus during speech processing.

The paper introduces a diffusion-approximation framework to model and interpret neuronal spiking dynamics using nonlinear Hawkes processes, showing its accuracy and applicability to human and nonhuman primate data.

The paper identifies distinct neural subspaces in motor cortex dynamics during obstacle avoidance, showing locomotion and volitional adjustments are separated into different subspaces.

This paper demonstrates that intracortical signals from areas distant from seizure onset can predict focal seizures with 90% accuracy using machine learning.

This study decodes English words from neural activity in macaques' secondary auditory cortex using spike-based machine learning, showing the auditory cortex processes complex sounds as a distributed network.