Peter Dayan is Professor of Computational Neuroscience at the Gatsby Unit in University College London. He studied mathematics at the University of Cambridge, and did a PhD in Cognitive Science at the University of Edinburgh, focusing on statistical and neural network models of learning. After postdoctoral training at the Salk Institute and the University of Toronto, he was an assistant professor at MIT. He moved to London in 1998 to help found the Gatsby Unit.
Honors and awards
I build mathematical and computational models of neural processing, with a particular emphasis on representation and learning. The main focus is on reinforcement learning and unsupervised learning, covering the ways that animals come to choose appropriate actions in the face of rewards and punishments, and the ways and goals of the process by which they come to form neural representations of the world. The models are informed and constrained by neurobiological, psychological and ethological data. A more recent interest is failure modes of decision making and the nascent field of computational psychiatry.
I have long worked on the main neuromodulatory systems in the brain: acetylcholine, dopamine, serotonin and norepinephrine. I have modelled their involvement in appetitive and aversive reinforcement, vigour, uncertainty and interruption.
I collaborate with a wide range of theoretical and experimental groups.