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Recent advances in neural interfaces—Materials chemistry to clinical translation

Published online by Cambridge University Press:  10 August 2020

Christopher J. Bettinger
Affiliation:
Department of Materials Science and Engineering, and Department of Biomedical Engineering, Carnegie Mellon University, USA; [email protected]
Melanie Ecker
Affiliation:
Department of Biomedical Engineering, University of North Texas, USA
Takashi Daniel Yoshida Kozai
Affiliation:
Department of Bioengineering, University of Pittsburgh, USA
George G. Malliaras
Affiliation:
University of Cambridge, UK; [email protected]
Ellis Meng
Affiliation:
Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, USA
Walter Voit
Affiliation:
Department of Mechanical Engineering, The University of Texas at Dallas, USA
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Abstract

Implantable neural interfaces are important tools to accelerate neuroscience research and translate clinical neurotechnologies. The promise of a bidirectional communication link between the nervous system of humans and computers is compelling, yet important materials challenges must be first addressed to improve the reliability of implantable neural interfaces. This perspective highlights recent progress and challenges related to arguably two of the most common failure modes for implantable neural interfaces: (1) compromised barrier layers and packaging leading to failure of electronic components; (2) encapsulation and rejection of the implant due to injurious tissue–biomaterials interactions, which erode the quality and bandwidth of signals across the biology–technology interface. Innovative materials and device design concepts could address these failure modes to improve device performance and broaden the translational prospects of neural interfaces. A brief overview of contemporary neural interfaces is presented and followed by recent progress in chemistry, materials, and fabrication techniques to improve in vivo reliability, including novel barrier materials and harmonizing the various incongruences of the tissue–device interface. Challenges and opportunities related to the clinical translation of neural interfaces are also discussed.

Type
Technical Feature
Copyright
Copyright © Materials Research Society 2020

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Footnotes

This article is based on the Materials Research Society/Kavli Future of Materials workshop: Brain–Machine Interfaces: Materials to Clinical Translation, presented at the 2019 MRS Spring Meeting in Phoenix, Ariz.

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