Featuring: John Rogers, PhD
A new high-resolution brain mapping technology exceeds the lifespans of current platforms and may enhance how brain function is measured and how efficiently neurological diseases are diagnosed and treated.
The novel neural interface, detailed in a study published in Science Translational Medicine, was co-developed by John Rogers, PhD, the Louis Simpson and Kimberly Querrey Professor of Materials Science and Engineering, Biomedical Engineering and Neurological Surgery and a co-author of the study.
Called “Neural Matrix”, the technology takes on the form of a thin, flexible sheet that rests on the surface of the brain, using more than 1,000 measurement sites sampling a centimeter-scale brain region to map brain function and the development of neural networks.
Current high-resolution neural interfaces that are implanted and rely on encapsulation programming strategies have short implant lifetimes and are restricted to sampling a small neuronal volume because they have a limited number of measurement sites.
In comparison, Neural Matrix lasts over one year and contains more channels of measurement at higher densities and over larger areas, according to Rogers.
“As neurotechnologists, we are constantly motivated to advance capabilities in merging man-made electronic systems with biology’s most sophisticated form of electronics – the brain,” Rogers said.
“We view this area as an important frontier in engineering science, with implications that span neuroscience investigations of the fundamental operating principles of the brain to new schemes for passing information to and from the brain via external computer systems,” Rogers said.
Active electronics, flexible construction and insulating layers allow the paper-thin technology to measure the brain’s electrical activity from its surface, all while softly binding to the curvature of the brain and remaining isolated from surrounding biofluids to prevent wear and tear over time.
Now, Rogers said that his team is interested in using the technology in humans for a wide variety of applications, such as diagnosing neurological disorders and electrical stimulation to treat such disorders.
“We view our system as a powerful new tool for neuroscience research, but it also has potential applications as a surgical diagnostic to guide resections in the context of treatments for epilepsy and, in the future, systems like this one might serve as implants for brain-computer interfaces,” said Rogers.
This work was funded by a National Institute of Neurological Disorders and Stroke award U01 NS099697 and the Defense Advanced Research Programs Agency awards DARPA-BAA-16-09 and DARPA-BAA-13-20.
This article was originally published in the Feinberg School of Medicine News Center on April 27, 2020 .
John Rogers, PhD, the Louis Simpson and Kimberly Querrey Professor of Materials Science and Engineering, Biomedical Engineering and Neurological Surgery, was a co-author of the study published in Science Translational Medicine.
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