Project Jenkins: Turning Monkey Neural Data into Robotic Arm Movement, and Back
This work addresses the challenge of creating flexible brain-computer interfaces for robotics and prosthetics, though it appears incremental as it builds on existing neural decoding and encoding methods.
The researchers tackled the problem of decoding neural activity from a macaque monkey into robotic arm movements and encoding movement patterns into synthetic neural data, achieving a step towards brain-controlled robotics and prosthetics with open-source tools for reproducibility.
Project Jenkins explores how neural activity in the brain can be decoded into robotic movement and, conversely, how movement patterns can be used to generate synthetic neural data. Using real neural data recorded from motor and premotor cortex areas of a macaque monkey named Jenkins, we develop models for decoding (converting brain signals into robotic arm movements) and encoding (simulating brain activity corresponding to a given movement). For the interface between the brain simulation and the physical world, we utilized Koch v1.1 leader and follower robotic arms. We developed an interactive web console that allows users to generate synthetic brain data from joystick movements in real time. Our results are a step towards brain-controlled robotics, prosthetics, and enhancing normal motor function. By accurately modeling brain activity, we take a step toward flexible brain-computer interfaces that generalize beyond predefined movements. To support the research community, we provide open source tools for both synthetic data generation and neural decoding, fostering reproducibility and accelerating progress. The project is available at https://www.808robots.com/projects/jenkins