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 and molecular dye-based network systems 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:

• Objective 1: 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.

  

• Objective 2: 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 and molecular dyes.
• Objective 3: 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.
• Objective 4: Show upscaling, on-chip assembly and market potential. Working on scalability, energy efficiency and potential for optimization, we will show the generality of the approach and the next steps towards large-scale commercialization.  

Our approach to develop nanophotonic computational devices inspired by neural circuits in insect brains combines four advanced lines of research:

1. The rapidly developing understanding of insect neurological and sensory systems
2. An extremely advanced III-V semiconductor nanowire platform.
3. Circuit technology developed for quantum computing.
4. Optically efficient, stable molecular dyes.

The combined circuits can be directly placed on the Silicon technology platform

Detailed electrical and optical modelling of an initial nanophotonic implementation of a decision-making circuit from the insect brain shows three main advantages of our approach:

1. Weighted component interconnectivity can be achieved by controlling light emission patterns and physical placement of individual neural nodes of the system. This bypass the huge amounts of physical connections needed in standard implementations of neural circuits.
2. The energy expenditure can be kept significantly below present computing systems by using nano-optoelectronic components.
3. The underlying network models are extremely robust to noise and cross-talk, making implementation feasible with weak signals and non-ideal components/connections.