New Technique Pave the Way to Longer-Lived and Better Brain Implants
Could we create better brain implants in the future? It's certainly a possibility. Scientists have developed a technique that tackles two challenges inherent in brain-implantation technology--gauging the property changes that occur during implantation and measuring on a micro-scale. This could eventually help researchers solve future challenges, such as crafting a device that can withstand the physiological conditions in the brain for the long-term.
Implanted devices face many challenges in a biological system. They have to withstand high temperatures, moisture and other in-vivo properties that can test longevity. If the implanted device changes to any degree--for example, becoming stiffer--there's the possibility that an inflammatory response will be triggered. This, in turn, can cause the device to prematurely fail and in some cases, patients can require brain surgery to replace or revise the implants. In this case, though, the researchers may have found a solution to this problem.
"We created an instrument to measure the mechanical properties of micro-scale biomedical implants, after being explanted from living animals," said Jeffrey R. Capadona, the lab's principal investigator, in a news release. By preserving the changing properties that occurred during implantation even after removal, the technique offer potential to create and test new materials for brain implant devices. This could, in turn, result in highly-tailored and longer lasting devices.
So what can brain implants do? New implantation materials may help find solutions to restore motor functions in individuals who have spinal cord injuries or have suffered from a stroke.
"Microelectrodes embedded chronically in the brain could hold promise for using neural activity to restore motor function in individuals who have suffered from spinal cord injuries," said Capadona in a news release.
The new technique also has a few other benefits. It also allows for measurement of mechanical properties using microsize scales. In contrast, previous methods typically required large or nano-sized samples of material, which didn't always work.
The findings are published in the Journal of Visualized Experiments.
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