Nanotechnology-Neuroscience Convergence

Abstract

Roco et al. 2013 introduced the convergence of nanotechnology with biotechnology, information technology, and cognitive technology (NBIC) as a main trend in science and technology. They also provided a list of 20 visionary ideas for the next 10–30 years. According to their ideas, in the next 20 years, we expect to have humanlike intelligent robots, smartphones with real-time language translating function, and pocket-sized supercomputers through the advance in the NBIC. To pave the way for this, every computing system should be flexible, mobile, self-programmable, real time, and even self-learning. However, as the miniaturization trend continues following Moore’s law, it would be impractical to apply the current nanoelectronics to future computing systems due to enormous energy consumption and technological limits. Accordingly, the architecture and the functions of transistors used in the present computing system need to be improved and inspired by the human brain. Unfortunately, it is unclear how neural activities in the human brain result in cognitive process es such as learning and reasoning. Nevertheless, the convergence of neuroscience with nanotechnology is expected to bring us closer to building neuro-inspired chips for neurocomputers utilizing some clues on neural activity and structure. In this chapter, we will show various scientific problems and challenges in realizing neuro-inspired chips.