The research, published in the journal Brain, has created a tool that captures electrical brain changes during an ischemic stroke, something that has been extremely difficult until now. This technology allows for the identification of brain areas at risk of further damage, thereby improving treatments.
The team, comprising experts from the University of Manchester, the Institute of Microelectronics of Barcelona (IMB-CNM, CSIC), and the Catalan Institute of Nanotechnology (ICN2), along with the company Multi Channel Systems, utilized high-sensitivity graphene sensors.
These sensors recorded in detail the spreading cortical depolarizations, altered electrical waves that travel through the injured brain and can cause additional damage. The shape of these electrical signals revealed information about the state of the surrounding brain tissue, distinguishing between healthy, at-risk, or already affected tissue. Tests were conducted on mouse models.
Furthermore, it was discovered that these signals could predict the blood flow response. In healthy tissue, blood flow increased to aid recovery, whereas in vulnerable tissue, it could decrease further, worsening the injury. Researchers observed that a low dose of ketamine, an existing drug, could modify these detrimental responses, reducing the duration of harmful electrical waves and improving the blood flow response.
These findings suggest that graphene-based brain monitoring could one day offer the medical community a real-time window into the state of brain tissue during a stroke, helping to identify patients at higher risk and supporting the development of new neuroprotective treatments.
The first author of the study is Samuel Flaherty from the University of Manchester. Corresponding authors are Anton Guimerà-Brunet from IMB-CNM (CSIC) and Rob Wykes from the University of Manchester and the UCL Queen Square Institute of Neurology.
This breakthrough marks a new milestone in the long-standing collaboration between IMB-CNM, the University of Manchester, and ICN2, which previously published pioneering results on graphene micro-transistors for ultralow brain signals in 2018 in Nature Materials.
