Recently developed small neural graphene probes can be used safely to greatly improve understanding of the causes of epilepsy, improving current technologies, which have limited ability to accurately obtain Ultra-slow brain signals with high spatial fidelity.
The ability to record and map the full range of brain signals using electrophysiological probes represents an important advance in the understanding of brain diseases and implies a contribution to the clinical management of patients with various neurological disorders.
New technology to detect brain signals associated with epilepsy
The graphene depth neural probe (gDNP) consists of a linear array of one millimeter long micro-transistors embedded in a flexible micrometer polymeric substrate. The transistors were developed in collaboration with the University of Manchester Neuromedicine Laboratory and the UCL Institute of Neurology.
An article published in the magazine Nature Nanotechnology, shows that the unique flexible brain probes of this project can be used to record pathological brain signals associated with epilepsy, obtaining results with excellent fidelity and high spatial resolution.
Dr Rob Wykes, member of the Nanoneuro team at the University of Manchester commented that “The application of this technology will allow researchers to study the role infraslow oscillations play in promoting the susceptibility windows for the transition to seizure, as well as improving the detection of clinically relevant electrophysiological biomarkers associated with epilepsy.”.
For the first trials, these flexible gDNP devices were chronically implanted in mice with epilepsy. The implanted devices delivered outstanding spatial resolution and very rich bandwidth recording of epileptic brain signals for weeks. Additionally, extensive chronic biocompatibility tests confirmed that there is no significant tissue damage or neuroinflammation, attributed to the biocompatibility of the materials used, including graphene, and the flexible nature of the gDNP device.
If implemented, this new technology could allow researchers to learn more about the role that ultra-slow brain oscillations play in seizures typical of this disease, as well as improve the detection of clinically relevant electrophysiological biomarkers associated with epilepsy.
At a clinical level, in the future this new technology could offer the possibility of identifying and delimiting with much more precision the areas of the brain responsible for the initiation of seizures before performing surgery, which leads to less extensive resections and better results. Similarly, this technology can also be leveraged to gain a better understanding of other neurological diseases associated with ultra-slow brain signals, such as traumatic brain injuries, strokes, and migraines.