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'Hydrogel-based flexible brain-machine interface'

The interface is easy to insert into the body when dry, but behaves 'stealthily' inside the brain when wet

'Hydrogel-based flexible brain-machine interface'
2021-07-13
(Press-News.org) A KAIST research team and collaborators revealed a newly developed hydrogel-based flexible brain-machine interface. To study the structure of the brain or to identify and treat neurological diseases, it is crucial to develop an interface that can stimulate the brain and detect its signals in real time. However, existing neural interfaces are mechanically and chemically different from real brain tissue. This causes foreign body response and forms an insulating layer (glial scar) around the interface, which shortens its lifespan.

To solve this problem, the research team of Professor Seongjun Park developed a 'brain-mimicking interface' by inserting a custom-made multifunctional fiber bundle into the hydrogel body. The device is composed not only of an optical fiber that controls specific nerve cells with light in order to perform optogenetic procedures, but it also has an electrode bundle to read brain signals and a microfluidic channel to deliver drugs to the brain.

The interface is easy to insert into the body when dry, as hydrogels become solid. But once in the body, the hydrogel will quickly absorb body fluids and resemble the properties of its surrounding tissues, thereby minimizing foreign body response.

The research team applied the device on animal models, and showed that it was possible to detect neural signals for up to six months, which is far beyond what had been previously recorded. It was also possible to conduct long-term optogenetic and behavioral experiments on freely moving mice with a significant reduction in foreign body responses such as glial and immunological activation compared to existing devices.

"This research is significant in that it was the first to utilize a hydrogel as part of a multifunctional neural interface probe, which increased its lifespan dramatically," said Professor Park. "With our discovery, we look forward to advancements in research on neurological disorders like Alzheimer's or Parkinson's disease that require long-term observation."

INFORMATION:

The research was published in Nature Communications on June 8, 2021. (Title: Adaptive and multifunctional hydrogel hybrid probes for long-term sensing and modulation of neural activity) The study was conducted jointly with an MIT research team composed of Professor Polina Anikeeva, Professor Xuanhe Zhao, and Dr. Hyunwoo Yook.

This research was supported by the National Research Foundation (NRF) grant for emerging research, Korea Medical Device Development Fund, KK-JRC Smart Project, KAIST Global Initiative Program, and Post-AI Project.

-Publication Park, S., Yuk, H., Zhao, R. et al. Adaptive and multifunctional hydrogel hybrid probes for long-term sensing and modulation of neural activity. Nat Commun 12, 3435 (2021). https://doi.org/10.1038/s41467-021-23802-9

-About KAIST KAIST is the first and top science and technology university in Korea. KAIST was established in 1971 by the Korean government to educate scientists and engineers committed to industrialization and economic growth in Korea.

Since then, KAIST and its 67,000 graduates have been the gateway to advanced science and technology, innovation, and entrepreneurship. KAIST has emerged as one of the most innovative universities with more than 10,000 students enrolled in five colleges and seven schools including 1,039 international students from 90 countries.

On the precipice of its semi-centennial anniversary in 2021, KAIST continues to strive to make the world better through its pursuits in education, research, entrepreneurship, and globalization. For more information about KAIST, please visit http://www.kaist.ac.kr/


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'Hydrogel-based flexible brain-machine interface'

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[Press-News.org] 'Hydrogel-based flexible brain-machine interface'
The interface is easy to insert into the body when dry, but behaves 'stealthily' inside the brain when wet