ARIA Opportunity Space: Scalable Neural Interfaces

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.