Major goal:  Enhance human performance through neural decoding and brain-machine interfaces (BMIs)

     We have been working on neural decoding using non-invasive brain signals such as EEG and fMRI to develop brain-machine interfaces (BMIs). Targets for the decoding include motor control, speech, and emotion, and we have succeeded in decoding detailed information that was considered to be difficult for EEG, such as classifying and reconstructing individual muscle activity signals and heard speech sounds. Based on the achievements and accumulated our techniques, one of our plans is to develop a BMI that enhances human physical and mental performance through decoding and feedback to maintain motor coordination skills of people for keeping their health through their life and to prevent all people from mental disorders by monitoring daily physical and mental data through brain activity signals. Besides them, we have been working to develop a BMI for completely locked-in patients suffering from amyotrophic lateral sclerosis (ALS) through international collaboration.