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ARIA Opportunity Space: Nature Computes Better
AI for Systems-Behavioral Neuroscience
We are developing an AI-powered technology that can infer the contributions of specific brain regions to behavior by analyzing gameplay data, enabling non-invasive diagnosis and treatment of neurological disorders. Our approach leverages state-of-the-art deep reinforcement learning models, specifically MuZero and Dreamer architectures, which learn to solve complex tasks in ways that mirror human cognitive processes. The system will be trained and validated using a combination of Atari game benchmarks, simulated behavioral data, and real-world functional MRI recordings from collaborators at Harvard University and the University of Oxford. This technology aims to revolutionize neurological treatment by enabling personalized, non-invasive therapies that target specific brain regions, potentially transforming how we diagnose and treat a broad spectrum of neurological conditions from behavioral data alone.
Rui Ponte Costa's Lab
University of Oxford
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Oxford
Costa Lab
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Csabi holds a PhD in core ML (focusing on Continual and Self Supervised Learning) from University of Oxford with collaborations at Apple, Intel and Meta. Prior to his fellowship he worked on Multi-Modal World Models as an ML engineer for Silent Creek, a High Frequency Trading firm.
Rui Ponte Costa
Group Leader, Centre for Neural Circuits and Behaviour, Department of Physiology, Anatomy and Genetics
Rui Ponte Costa leads the Neural & Machine Learning Group at Oxford, bringing together neuroscience, psychology and machine learning.