Our brain is a highly-structured but very complex network of a vast number of biological neurons. The brain is established on a completely different information processing principle from that of current digital computers, realizing its high cognitive performance through a physicochemical system.

We are working on a novel high-performance, highly-efficient, flexible, and robust “brainmorphic” computing paradigm. In particular, we focus on information processing through physical complex-networked dynamical process. Towards the final goal, we are developing integrated circuit and device technologies suitable for the brain-inspired computer systems such as VLSI technologies for high-dimensional chaotic networks and large-scale complex systems, VLSI circuits and architectures for ultra-low-power asynchronous neural network systems, and compact and low-power devices/circuits, e.g., spintronics devices, for neuron and adaptive synaptic connections. At the same time, we are developing a massively-parallel brain-inspired computational system architecture, in which processing and memory are not separated but integrated, and memorizing and retrieval occur at the same time. We further intend to realize an autonomous brainmorphic computer with a sense of self and consciousness based on a complex network with dynamic change in spatiotemporal network state and structure.