‘Smart’ Brain-Machine Interfaces That Adapt to Your Needs and Intent

Machine Learning meets Neural Engineering

I’m going to confess something I’ve never told anyone. The inspiration for much of my current research at the intersection between neuroscience, mathematics, and machine learning was inspired by a single beautiful scene in the movie Ex Machina. There is a scene where the movie’s two protagonists Nathan and Caleb are in the lab where Nathan built Ava, a humanoid artificial intelligence (AI), where they share an exchange about how Nathan engineered Ava’s brain. “Structured gel. I had to get away from circuitry. I needed something that could arrange and re-arrange at a molecular level, but keep its form when required. Holding for memories, shifting for thoughts.” Of course, science fiction has a long history of motivating and inspiring what eventually becomes real science. And nowhere is this more true than when it comes to the brain (okay, other than maybe space), and in particular when it comes to brain-machine interfaces (BMI’s) becoming AI-enabled.

A confluence of technological capabilities is creating an opportunity and setting the conditions for machine learning and AI to enable “smart” brain machine interfaces. Devices and technologies that are designed to adapt and respond to the user’s brain, predicting needs and intent in a…