Neural Information Analysis Laboratories

~Analyze brain function using statistical and machine learning theory~

The goal of our research is to develop analysis tools to clarify human brain functions and communication techniques based on brain activities.

Department of Computational Brain Imaging(CBI)

Integrating multiple brain imaging data
We are developing statistical methods to integrate existing non-invasive brain imaging modalities such as fMRI, MEG, EEG, and NIRS. We aim to enhance the spatial and temporal resolution that brain imaging techniques cannot achieve by themselves. Multimodal integration is dispensable to noninvasively understand the neural mechanism of humans.
●Combining large-scale and high-resolution brainimaging(MEG and fMRI) data
MEG has high temporal resolution, even though it cannot provide the location of brain activities. On the other hand, fMRI provides the precise location of brain activities, but it lacks temporal resolution. To measure brain activities with both high temporal and spatial resolution, we are developing a statistical method to combine these two complementary brain techniques. Further, we are developing software with graphical user interface for experimenters.
●Combining easy-to-use and portable brain imaging (EEG and NIRS) data
Although MEG and fMRI provide brain activity data with high temporal/spatial resolution, they are not practical for daily use because of their large-scale instruments. On the other hand, since EEG and NIRS are portable, they allow brain activity measurements outside examination rooms. To estimate brain activities accurately under open environments, we are also developing methods that combine EEG with NIRS.