Editorial: Emerging Technologies and Systems for Biologically Plausible Implementations of Neural Functions

The human brain is a complex and fascinating biological machine. With 20 W only, the activity of 100 billion neurons and 3 orders of magnitude more (10^15) synapses in a volume as small as a shoebox allow us to learn, process, sense, and perceive a vast amount of information from the external environment in real-time. The human brain features a distributed system based on slow and unreliable components. Yet, it is able to learn from experience and compute unstructured data reliably with extreme energy efficiency. Therefore, our brain's real-time and low-power cognitive processes have always been the ultimate ambition in terms of building artificial systems for Edge Information-Extraction and Computing, User-Specific Applications such as Healthcare, Autonomous vehicles, Robotics, and the Internet of Things. Studies on the brain lead to models describing its operating and computational principles, which in turn can be used as a guideline to build new devices, circuits, and systems emulating brain functionality.