CBI | ATR NIA Labs

Welcome to The Department of Computational Brain Imaging (CBI)

CBI’s mission is to develop innovative data analytics tools for neuroscience. We study brain data analysis and modeling methods to elucidate the mechanisms of brain information processing.

In particular, using cutting-edge machine learning algorithms and Bayesian learning theories, we are developing accurate brain imaging methods by integrating multimodal brain measurements, such as magnetoencephalography (MEG), functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and near-infrared spectroscopy (NIRS).

Based on these measurements, we are also modeling brain dynamics.

In a research project commissioned by the National Institute of Information and Communications Technology (NICT) (FY 2013–2019), we developed a “brain data simulator” that predicts brain measurement data (MEG, fMRI, EEG, and NIRS) using a brain dynamics model.

In the subsequent research project commissioned by NICT (FY 2018–2022), we developed an MEG measurement system using Optically Pumped Magnetometers (OPMs) as a new fundamental technology for brain-machine interface (BMI) and an innovative decoding technology based on the brain data simulator.

Main Research Themes

• • • Analysis of multimodal brain measurements and applying analysis to BMI open innovation
    • Innovative brain dynamics imaging using whole-brain network model
    • Cortical current estimation with high spatial and temporal resolutions by integrating multimodal brain measurements
    • Brain network dynamics estimation
    • Diffuse optical tomography
    • Decoding of brain information
    • Simulator for brain activity data
    • Brain-Machine Interface