(contributed talk)

What can deep neural networks learn from neuromodulatory systems?

Neuromodulators are signalling chemicals in the brain, which control the emergence of adaptive learning and behaviour. Neuromodulators including dopamine, acetylcholine, serotonin and noradrenaline operate on a spectrum of spatio-temporal scales in tandem and in opposition to reconfigure functions of biological neural networks and to regulate global cognition and state transition. Although neuromodulators are important in shaping cognition, their phenomenology is yet to be fully realized in deep neural networks (DNNs). In this talk, I will first give an overview of the biological organizing principles of neuromodulators in adaptive cognition and highlight the competition and cooperation across neuromodulators. I will then discuss ongoing research on bio-inspired mechanisms of neuromodulatory function in DNNs, and propose a computational framework to incorporate their diverse functional settings and inspire new architectures of “neuromodulation-aware” DNNs.

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