Christopher Summerfield, PhD
Professor of Cognitive Neuroscience, University of Oxford
*Speaker will join remotely; audience is encouraged to participate in-person or on Zoom
Humans can learn about how objects are related and generalise this information to solve new tasks. In my talk, I will ask how this is possible. I will discuss recent work in which brain imaging was used to ask how neural representations change when humans learn new relational information. I will describe a computational theory of how this happens using connectionist models.
Rich and lazy learning of task representations in brains and neural networks
Neural state space alignment for magnitude generalisation in humans and recurrent networks