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AI-driven brain-wide computational models 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 detail. At the same time, new theoretical frameworks are starting to reveal how rich behaviours arise from synaptic, circuit and systems computations (Richards et al. Nature Neuroscience 2019). Our group is 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 learning 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 this end and in order 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.

You can find more details on our external website

We co-organise the Oxford NeuroTheory Forum.

Our team

What's new

Cosyne success

Rui Ponte Costa receives EPSRC New Investigator Award

Rui Ponte Costa has received an EPSRC New Investigator award for research exploring Cerebellum-inspired parallel deep learning

Computational neuroscientist Rui Ponte Costa joins DPAG

This September, Dr Rui Ponte Costa relocates his Neural and Machine Learning group to DPAG. He was previously a Senior Lecturer in Computational Neuroscience and Machine Learning at the University of Bristol. His research group focuses on producing AI-driven brain-wide computational models of learning.

Related research themes

We host a number of internationally recognised neuroscience groups, with expertise in a wide range of experimental and computational methods.

We host a number of internationally recognised ...