Background

A brain–computer interface is a technology that creates a direct connection between the brain and an external device. It works by detecting the tiny electrical signals produced when brain cells communicate, and translating those signals so they can be measured or used to control something outside the body. Developing these interfaces for long-term use is challenging because most current devices are made from stiff materials that do not move naturally with brain tissue. This mismatch can irritate the brain over time, leading to scar-like tissue forming around the device and reducing its ability to function properly. Creating softer, more flexible materials that better match the brain’s natural movement could help overcome this problem. Long-term, reliable brain–computer interfaces could support new treatments for conditions such as Parkinson’s disease and epilepsy, as well as help people control external devices like communication aids or prosthetic limbs.

Research

The PolyGraph project has developed a new type of brain interface that can both record brain activity and, in principle, interact with it. The device uses very small, needle-like structures made from flexible, biocompatible materials that are safe for use in the body. These materials are combined with graphene, a highly conductive form of carbon that helps carry electrical signals. This combination allows the device to detect electrical activity from brain cells while remaining soft and flexible, making it a better physical match for brain tissue than traditional rigid electrodes. We have shown that these devices can successfully record brain signals and can be manufactured in a way that maintains flexibility at both small and larger scales.

Impact

This work could form the foundation for a new generation of brain interfaces that are softer, more adaptable, and more compatible with living tissue. In the longer term, this may lead to more reliable devices for studying and treating neurological conditions. Future work will focus on integrating this technology with other emerging approaches to brain interfacing and further developing it towards safe, long-term use in living systems.