What can deep neural networks learn from neuromodulatory systems?

Hosted by the Neural Computation Hub

Neuromodulators are signaling 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.

Srikanth is a member of the Neuroscience, Neurodisability and Neurological Disorders group at Newcastle. He is a Computational Neuroscientist, Marie Curie Fellow and Fulbright Scholar who works in the area of neuromodulation, neocortex, and deep learning. 

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Contact information

Contact Rui Ponte Costa with any questions.