To investigate the brain, think like a neuron
Technological innovations in brain-machine interfaces could enable the diagnosis and treatment of neurological diseases like epilepsy or Parkinson’s or potentially restore motor function. However, inserting these devices without damaging the brain poses a monumental challenge.
Ferro et al. developed NeuroRoots, a bio-inspired brain-machine interface that can record signals from the cerebellum without harming brain tissue during implantation.
“We designed the flexible NeuroRoots to self-assemble around a very thin, yet very stiff tungsten microwire,” said author Nicholas Melosh. “This allowed the insertion of a very slender bundle of devices into a delicate area of the brain that cannot normally be targeted. Once inside the tissue, the weak van der Waals forces that keep the probes attached to the wire weaken, allowing the tungsten wire to be removed, leaving only the flexible devices behind.”
The device mimics axons, the fibers that transmit signals to and from nerves. This model facilitates easy insertion in addition to the comfort of a flexible device. Its small size also aids in minimizing damage upon insertion.
In in vitro testing, NeuroRoots was inserted without causing any ruptures to the agar gel representing brain tissue. Based on these promising results, they conducted in vivo tests, inserting the device into the cerebellum, the part of the brain that controls motor function. They successfully obtained high-quality electrical recordings.
“Our next steps are to increase the number of recording sites and distribution of these probes to map out signaling in the cerebellum,” said Melosh. “This could open up many areas for understanding the kinds of processing the brain does for motor control, potentially adding insight into how to improve prosthetic interfaces.”
Source: “NeuroRoots, a bio-inspired, seamless brain machine interface for long-term recording in delicate brainregions,” by Marc D. Ferro, Christopher M. Proctor, Alexander Gonzalez, Sriram Jayabal, Eric Tianjiao Zhao, Maxwell Gagnon, Andrea Slézia, Jolien Pas, Gerwin Dijk, Mary Jocelyn Donahue, Adam Williamson, Jennifer Raymond, George Malliaras, Lisa Giocomo, and Nicholas A. Melosh, AIP Advances (2024). The article can be accessed at https://doi.org/10.1063/5.0216979 .