Some of the most challenging issues in printable large-area electronics (LAE) are related to the reliability, variability and relatively low speed of individual devices, which make it difficult to implement more complex functionality, especially analogue signal processing circuits. Remarkably, biological systems have evolved solutions to these problems: neurons are slow, highly variable, volatile, and yet brains have an amazing ability to achieve robust operation, and process information at high speed and with low power consumption. Hence a question arises: can circuits based on neural principles be able to provide useable solutions to coping with device issues in LAE?
Conversely, as the interest in brain-inspired systems continues to grow, with potential applications ranging from machine intelligence to brain interfacing and prosthesis, one of the challenges is to find suitable implementation technologies for the ‘neuromorphic’ (i.e. brain-mimicking) systems. These are usually implemented using conventional silicon integrated circuits, however, these have been optimised for high-speed numerical computation, and are not necessarily a most natural fit. Perhaps low-cost large-area printed electronics, with its inherently more “neuron-like” devices, could provide an ideal alternative technology for implementing such systems?
Printed Electronics for Neuromorphic Computing (pNeuron) project will start to explore these questions. The project goal is to demonstrate spiking neuron circuits, mimicking biological behaviour, using printed electronics technology. These initial proof-of-concept experiments will prepare the ground for future research, including larger collaborative research proposals.