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Neuroinformatics Lab
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The lab uses AI to decode biosignals such as EEG and apply them to medicine.
AboutAbout the lab
Decoding and controlling neural information by fusing the brain and AI.
The Neuroinformatics Lab applies artificial intelligence to brain signals such as EEG and magnetoencephalography to develop new diagnostic and therapeutic methods.
The lab regards physiological signals obtained from implanted devices, wearable devices, and the like as neural information in a broad sense, and aims to decode and control them.
By developing new technologies together with researchers in fields such as informatics, engineering, and neuroscience, and putting them into clinical use, the lab aims to create new medicine.
On the lab's website, it is presented under the name "Yanagisawa Lab."
Key terms
- Brain-Machine Interface
- Technology that reads brain signals to operate machines such as robots or screens. Abbreviated as BMI
- Intracranial EEG
- EEG measured with electrodes implanted inside the head
- Neurofeedback
- A therapy in which a person is trained while receiving feedback on their own brain activity, encouraging changes in that activity
- Phantom limb pain
- A condition in which pain is felt in an arm that is no longer there after it has been lost
NewsLab news
Paper by Project Lecturer Naoki Hirose published in Cell Reports
Paper from the lab published in Neurobiology of Disease
Paper by a doctoral student published in Communications Biology
Paper by Project Assistant Professor Huixiang Yang published in Scientific Data
First paper on the endovascular EEG being developed under the JST Moonshot program published
ResearchResearch themes
The lab aims to elucidate how the nervous system represents information, develop technologies to decode and control neural information, and apply them to medicine. This page covers the research of the Yanagisawa Group featured on the research introduction page.
*Illustrative imageBMIs that move robots with brain signals
The lab has developed Brain-Machine Interfaces (BMIs) that decode brain information from intracranial EEG to control robots and display imagined images. These technologies are applied in medicine to restore motor function and support communication for patients who cannot move their bodies, and the lab is also developing BMIs that use endovascular EEG, which is extremely minimally invasive.
*Illustrative imageNeurofeedback therapy
Using BMIs, the lab connects robots or avatars to brain activity in place of the body, guides changes in that activity, and investigates the relationship between motor control and brain activity. The lab has shown that training to move a robot with a BMI can reduce phantom limb pain, the pain felt after losing an arm, and this method is called neurofeedback (NF) therapy.
*Illustrative imageDecoding neural information in EEG
Applying AI to big data of EEG makes it possible to automatically diagnose conditions such as dementia and epilepsy. The lab mathematically investigates what brain information is represented in EEG, and uses large volumes of intracranial EEG to identify the EEG features that characterize human thought.
*Illustrative imageHealth promotion and functional restoration with biosignals
The lab aims to support health management and health promotion using biosignals measured in daily life with wearable sensors and similar devices. It builds big data that includes not only EEG but also electromyography and motion analysis data as neural information, and aims for diverse medical applications ranging from health promotion to restoring neural function.
MembersFaculty
The members of the Neuroinformatics Lab consist of faculty, JSPS Research Fellows, researchers, project technical staff, doctoral and master's students, research students, student researchers, and technical assistants.As of 2026
- ProfessorTakufumi Yanagisawa
- Associate ProfessorTomoyuki Matsuo
- Associate ProfessorTomoyuki Naito
- Associate ProfessorIssei Ogasawara
- LecturerShoji Chikata
- Project Associate ProfessorRyohei Fukuma
- Project LecturerNaoki Hirose
- Project Assistant ProfessorHuixiang Yang
- Project Assistant ProfessorBetty Wutzl
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “EEG Experiment (cropped)” Flexagoon / CC0 (cropped)
- BMIs that move robots with brain signals: “SCARA robot 2R” Mitsubishi Electric Automation, Inc. 500 Corporate Woods Pkwy - Vernon Hills, IL - 60061 - US / CC BY-SA 4.0 (cropped)
- Neurofeedback therapy: “EEG Recording Cap” Chris Hope / CC BY 2.0 (cropped)
- Decoding neural information in EEG: “EEG Absence seizure” Bromfield EB, Cavazos JE, Sirven JI, editors. / CC BY-SA 4.0 (cropped)
- Health promotion and functional restoration with biosignals: “SmartCare wrist-worn pulse oximeter” Peter H Charlton / CC BY 4.0 (cropped)
- Related lab (Neurology Lab): “Neuron (100x magnification)” Ns takes photos / CC BY 4.0 (cropped)
- Related lab (Advanced AI Medicine Lab): “CSIRO ScienceImage 2465 Sequencing DNA” Health Sciences and Nutrition, CSIRO / CC BY 3.0 (cropped)
- Related lab (Gastroenterological Surgery I Lab): “Breast surgery in operating room” Tyler Frew MD / CC BY-SA 4.0 (cropped)
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