Building neuromodulation-aware deep neural networks

Our brains have evolved the ability to configure and adapt their processing states to match the unique challenges of acting and learning in diverse environments and behavioral contexts. In biological nervous systems, such state specification and adaptation arise in part from neuromodulators, including acetylcholine, noradrenaline, serotonin, and dopamine, whose diffuse release fine-tunes neuronal and synaptic dynamics and plasticity to complement the behavioral context in real-time. Despite the demonstrated effectiveness of deep neural networks for specific tasks, they remain relatively inflexible at generalizing across tasks or adapting to ever-changing behavioral demands. We recently outlined a framework to integrate principles of neuromodulatory systems into deep neural networks. The goal of this internship would be to further enhance this framework to systematically add biological detail and explore how neuromodulatory principles endow artificial intelligence with the flexibility and learning capability of biological intelligence.