Scientists at the University of Manchester have developed a graphene-based brain monitoring technology that could help doctors understand what happens in the brain during a stroke and identify areas at risk of further damage.
The research, published in the journal Brain, was conducted by experts in neuroscience, stroke research, engineering and advanced materials from the University of Manchester, the Institute of Microelectronics of Barcelona (IMB-CNM, CSIC) and the Catalan Institute of Nanoscience and Nanotechnology (ICN2) in Barcelona, along with industry partner Multi Channel Systems in Germany.
How the Technology Works
When a person has an ischaemic stroke, a blockage cuts off blood supply to part of the brain. However, the damage does not stop immediately. Waves of disrupted electrical activity, known as cortical spreading depolarizations, travel through the injured brain and can cause additional harm.
Using highly sensitive graphene-based sensors placed on the brain, researchers were able to record these electrical waves in unprecedented detail. The existing technologies poorly capture the very slow electrical changes involved, making this advance significant.
The researchers discovered that the shape of the electrical signals revealed important information about the health of surrounding brain tissue. The signals could distinguish between tissue that was relatively healthy, tissue that was at risk, and tissue that was already severely compromised. These tests were performed in mice.
Blood Flow and Recovery
The team found that the signals could predict how blood flow would respond to the electrical wave. In healthier tissue, blood flow increased to help the brain recover from the event. In vulnerable tissue, blood flow could instead further decrease, worsening the injury.
Importantly, the researchers showed that these harmful responses could be altered using a low dose of ketamine, a drug already used in medicine. Ketamine reduced the duration of the damaging electrical waves, shifted the associated blood flow response from potentially harmful vasoconstriction towards vasodilation, and reduced the overall area of brain damage.
Future Clinical Applications
The findings suggest that graphene-based brain monitoring could one day provide doctors with a real-time window into the condition of brain tissue during a stroke. This could help identify patients at greatest risk of further injury and support the development of new treatments aimed at protecting the brain and improving recovery.
Dr Rob Wykes, Senior Lecturer at the University of Manchester, said: "More broadly, the study demonstrates how cutting-edge technologies can not only improve the way brain activity is measured but also reveal important new insights into how brain injuries develop and how they might be treated."
The study's first author was Dr Samuel Flaherty from the University of Manchester. Corresponding authors were Dr Anton Guimerà-Brunet from the Institute of Microelectronics of Barcelona and Dr Rob Wykes from the University of Manchester and UCL Queen Square Institute of Neurology.
Years of Development
Dr Guimerà-Brunet stated: "Recording these ultraslow signals remains highly challenging with current technologies. We have been developing our graphene-based technology for years, with our first results published in 2018, and the challenge has been to standardise it and make it mature for use in relevant preclinical research."
This research marks a new milestone in a long-standing collaboration between IMB-CNM, the University of Manchester and ICN2, which began with the development of graphene microtransistor technology for recording ultraslow brain signals, first published in Nature Materials in 2018. Since then, the teams have continued to develop graphene-based technologies for neural interfaces, with studies published in Nature Nanotechnology and Nature Communications.
The research was published in Brain with the full title "Monitoring ischaemic tissue vulnerability through perfusion-dependent signatures of spreading depolarizations" (DOI: 10.1093/brain/awag305).