AI-driven brain-wide principles of learning

We are at an exciting turning point in neuroscience. New technologies now allow us to measure and control neural activity and behaviour with unprecedented. At the same time, new theoretical frameworks are starting to reveal how rich behaviours arise from synaptic, circuit and systems computations. In our group, we are contributing directly to the latter by aiming to understand how we learn. To this end, we are developing a new generation of computational models of brain function driven by recent machine learning developments.

We focus on understanding how a given behavioural outcome ultimately leads to credit being assigned to trillions of synapses across multiple brain areas – credit assignment problem. To have a unified understanding of how we learn to produce adaptable behaviours it is important to jointly study the contribution of three different systems: (i) cortical circuits, (ii) neuromodulation and (iii) subcortical regions. In this talk I will give an overview of these complementary lines of research.