 This research paper proposes a new method to characterize neural activity during robot-assisted bimanual training. This method combines electroencephalogram, EEG, and functional near-infrared spectroscopy, FNIRS, data to provide more accurate measurements of brain activity. The authors found that the combined data provided better discrimination between different types of bimanual training tasks compared to either EEG or FNIRS data alone. This suggests that combining these two modalities could be useful for measuring changes in brain activity associated with bimanual training. This article was authored by Yichuan Jiang, Rui Ma, Shurchin Qi, and others.