Despite a relatively small number of neurons (around 100,000 for the case of Drosophila melanogaster), insects exhibit an impressive array of abilities, including short term and long term memory, sensory integration, associative and self-learning capabilities, and extremely fine motor skills. Our research uses the insect brain as a model system to understand how to design neuromorphic architectures that can act as smart sensors capable to register, adapt, and respond to changes in the environment.
In this talk we will focus on two fundamental aspects of insect’s brain anatomy and their implication both at the architecture and materials levels: the implementation of context-selective plasticity in order to allow for reinforced learning, and the need to explore heterogeneous architectures integrating components that respond at different time scales in order to create stable feedback loops. From a materials standpoint, the ability to control the volatility of memristive elements and the way charge is stored, released, and dissipated, are key aspects to enable this functionality. We exemplify this by emulating a system inspired on the mushroom body of the insect brain.