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When Bio Meets Technology: Biohybrid Neural Interfaces.

Accepted version
Peer-reviewed

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Type

Article

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Authors

Rochford, Amy E 
Carnicer-Lombarte, Alejandro 
Curto, Vincenzo F 
Malliaras, George G  ORCID logo  https://orcid.org/0000-0002-4582-8501
Barone, Damiano G 

Abstract

The development of electronics capable of interfacing with the nervous system is a rapidly advancing field with applications in basic science and clinical translation. Devices containing arrays of electrodes can be used in the study of cells grown in culture or can be implanted into damaged or dysfunctional tissue to restore normal function. While devices are typically designed and used exclusively for one of these two purposes, there have been increasing efforts in developing implantable electrode arrays capable of housing cultured cells, referred to as biohybrid implants. Once implanted, the cells within these implants integrate into the tissue, serving as a mediator of the electrode-tissue interface. This biological component offers unique advantages to these implant designs, providing better tissue integration and potentially long-term stability. Herein, an overview of current research into biohybrid devices, as well as the historical background that led to their development are provided, based on the host anatomical location for which they are designed (CNS, PNS, or special senses). Finally, a summary of the key challenges of this technology and potential future research directions are presented.

Description

Keywords

biohybrid interfaces, cell transplantation, implantable devices, nervous system injury, neural interfaces, Animals, Cochlear Implantation, Electrodes, Implanted, Humans, Microarray Analysis, Microfluidics, Neurons, Regenerative Medicine, Stem Cell Transplantation, Tissue Engineering

Journal Title

Adv Mater

Conference Name

Journal ISSN

0935-9648
1521-4095

Volume Title

32

Publisher

Wiley
Sponsorship
Engineering and Physical Sciences Research Council (EP/S009000/1)
European Commission Horizon 2020 (H2020) Future and Emerging Technologies (FET) (732032)
King Abdullah University of Science and Technology (KAUST) (OSR-2016-CRG5-3003.2)
The authors acknowledge funding from EPSRC (EP/S009000/1 and DTP program), European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No. 732032 (BrainCom) (G.G.M.) and from the King Abdullah University of Science and Technology (KAUST) Office of sponsored Research (OSR) under award No. OSR‑2016‑CRG5‑3003.