Recent advances in experimental and analytical techniques have revealed that biological systems are organized more precisely than ever imagined to perform various functions. We have been developing measurement methods and theories for dynamical systems to elucidate the underlying mechanisms of complex biological phenomena. We also applied the fundamental biological findings to a wide range of fields such as diagnosis and human interfaces.
Specifically, we have conducted studies on: (a) developing theoretical methods for nonlinear and time-delayed stochastic systems on complex networks, (b) understanding working memory and other cognitive functions using multi-scale brain models and noninvasive brain measurements, and (c) high-speed brain-machine interfaces using virtual reality.

Biological systems express their functions with hierarchical structures at various scales, such as molecule-cell-tissue. We aim to experimentally elucidate biological phenomena from the microscopic level and to develop experiment-based mathematical models toward understanding macroscopic biological systems. We are mainly working on cultured neuronal networks and sliced brain tissues using multi-site electrical recording of neural activity and microfabrication techniques.
Specifically, we have been (a) developing measurement techniques to evaluate neuronal functions, types, and structures in an integrated manner, (b) constructing experimental models that mimic biological functions such as pain transmission, (c) devising analysis methods to integrate acquired multi-scale data, and (d) elucidating the pathogenic mechanisms of neurological diseases using human iPS cells.