ARIA Opportunity Space: Scalable Neural Interfaces

We are developing AI that predicts how individuals will respond to brain stimulation treatments - therapies that have shown remarkable success in treating depression, Parkinson's disease, and other neurological conditions. While current tools can model where stimulation affects the brain physically, they cannot predict how it will impact a patient's symptoms or functioning. By analyzing brain imaging and treatment response data from over 300 patients across multiple studies, our machine learning system will learn to predict individual treatment outcomes based on each person's unique brain structure and activity patterns. This predictive framework will help clinicians optimize stimulation parameters for each patient, moving neuromodulation therapy from trial-and-error to precision medicine and potentially doubling the number of patients who achieve significant improvement in their symptoms.