Understanding of the neuro-architecture of key areas in the insect brain and its attached sensory systems will be used to create III-V nanowire/nanopillar and molecular dye-based network circuits that mimic neural computations underlying specific behaviours (in particular, navigation). Insights into how the sensory array of the insect eye couples to navigation control circuits will drive the development of coupled nanostructure sensor arrays and navigation systems. We will demonstrate and explore three main functionalities: connectivity, memory, and sensing; as well as concurrently develop the upscaling/commercial aspects:
• Demonstrate superior connectivity using overlapping light signals in a nanoscale system. To use light for connectivity we apply a broadcasting concept sensitizing the neural nodes to specific light signals and by sub-wavelength light manipulation of emission patterns using III-V nanowire-based components as well as molecular dyes. We will experimentally implement circuits step-by-step using a theoretically proven concept from the insect brain Central Complex. The aim to demonstrate how light for interneuron communication can have very high error tolerance and orders of magnitude better energy and spatial footprint compared to present technologies.
• Explore neuromorphic memory functionalities from nanoelectronics and molecular dyes. Based on neurobiology studies of the insect working memory we will explore how several different memory concepts can be implemented using III-V Nanowires/nanopillars and molecular dyes. The aim is to develop both an internal neural node memory, and memory in the network connections. Both short and long term memories will be explored.
• Integrate optical sensor systems and information processing. The same nanostructures used for computing will be used for optical sensing. A neural network unit will extract global orientation information from polarised skylight and time of day. The objective is to create a sensor array that output compass heading directly.
• Show upscaling, on-chip assembly and market potential. Working on scalability, energy efficiency and potential for optimization, we investigate the generality of the approach and the next steps towards commercialization. An additional outcome will be a computational approach for simulating the performance various III-V nanostructure and molecular dyes neural networks circuits.