Michał did his PhD at Oxford, exploring the dimentionality of prefrontal cortex representations over learning. His research focuses on using a machine-learning oriented framework to understand how biological circuits give rise to higher cognition. He is especially interested in the processes of abstraction and generalisation and how their learning dynamics can be explained and predicted by neural networks models. To capture how neural activity changes over the course of learning, he uses human electroencephalography (EEG) and high resolution neural population recordings from non-human primates.
