Thomas Mehari Kinfe

The paper investigates how syntactic processing, predictive coding, and semantic grounding interact in real time using MEG-EEG and compares neural responses to a large language model.

The paper tracks motor units in non-human primates during force contractions, finding stable recruitment order and a dominant neural component for force control.

This paper develops a deep learning method to predict hand kinematics and forces from EMG signals, showing accurate prediction of unseen movements and learned anatomical neural features.

The study identifies two neural modules underlying motor unit discharge rates in synergistic muscles, showing heterogeneous distribution of common synaptic inputs among motor neurons.