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Integrating living biomaterials into neuroelectronic systems

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Title
Integrating living biomaterials into neuroelectronic systems
Issued Date
2026-03
Citation
BIOMEDICAL ENGINEERING LETTERS, v.16, no.2, pp.307 - 328
Type
Article
Author Keywords
BiohybridNeural InterfacesMicroelectrode arrayLiving biomaterials-integrated neuroelectronics
Keywords
MICROELECTRODE ARRAY TECHNOLOGYNEURAL INTERFACEBRAIN-TISSUENEURONSCELLSMOTORELECTRODERODENTMODELINTERNEURONS
ISSN
2093-9868
Abstract

Neural interface technologies stand at the threshold of a revolution, offering new possibilities for seamless, high-bandwidth interconnection between the human brain and computers. Recent progress has been driven by advances in microscale manufacturing, yielding sophisticated neural probes with diverse form factors capable of recording from macroscopic networks down to single units. These platforms span rigid-to-soft architectures and combine inorganic and organic materials, improving compatibility with the brain's mechanical and chemical properties. Despite these advances, the field still relies primarily on nonbiological electrodes, which face inherent limitations in adapting to the dynamic and complex nature of living neural tissue. Living biomaterials-integrated neuroelectronics, on the other hand, could open new possibilities by enabling technologies that adapt to the host environment, actively establish bidirectional interfaces, conform to living tissue, and support repair by leveraging the inherent regenerative and plastic capacities of living systems. This review provides an overview of recent progress, challenges, and emerging directions in the integration of living biomaterials with neuroelectronic systems. We frame biohybrid neural interfaces as the convergence of in vitro microelectrode arrays and in vivo brain interfaces and organize the review around three themes: (i) cell sources for device integration, (ii) advances in in vitro MEA platforms, and (iii) cell-integrated, living electrodes for in vivo neural interfacing. Considered jointly, the themes point to an integrated path to seamless, adaptive biohybrid neural interfaces.

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URI
https://scholar.dgist.ac.kr/handle/20.500.11750/60482
DOI
10.1007/s13534-026-00557-0
Publisher
SPRINGERNATURE
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