Development and Characterization of PEDOT:PSS/Alginate Soft Microelectrodes for Application in Neuroprosthetics

Reducing the mechanical mismatch between the stiffness of a neural implant and the softness of the neural tissue is still an open challenge in neuroprosthetics. The emergence of conductive hydrogels in the last few years has considerably widened the spectrum of possibilities to tackle this issue. Ne...

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Published in:Frontiers in neuroscience Vol. 12; p. 648
Main Authors: Ferlauto, Laura, D'Angelo, Antonio Nunzio, Vagni, Paola, Airaghi Leccardi, Marta Jole Ildelfonsa, Mor, Flavio Maurizio, Cuttaz, Estelle Annick, Heuschkel, Marc Olivier, Stoppini, Luc, Ghezzi, Diego
Format: Journal Article
Language:English
Published: Switzerland Frontiers Research Foundation 19-09-2018
Frontiers Media S.A
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Summary:Reducing the mechanical mismatch between the stiffness of a neural implant and the softness of the neural tissue is still an open challenge in neuroprosthetics. The emergence of conductive hydrogels in the last few years has considerably widened the spectrum of possibilities to tackle this issue. Nevertheless, despite the advancements in this field, further improvements in the fabrication of conductive hydrogel-based electrodes are still required. In this work, we report the fabrication of a conductive hydrogel-based microelectrode array for neural recording using a hybrid material composed of poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate), and alginate. The mechanical properties of the conductive hydrogel have been investigated using imaging techniques, while the electrode arrays have been electrochemically characterized at each fabrication step, and successfully validated both and . The presence of the conductive hydrogel, selectively electrodeposited onto the platinum microelectrodes, allowed achieving superior electrochemical characteristics, leading to a lower electrical noise during recordings. These findings represent an advancement in the design of soft conductive electrodes for neuroprosthetic applications.
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This article was submitted to Neural Technology, a section of the journal Frontiers in Neuroscience
Edited by: Jeffrey R. Capadona, Case Western Reserve University, United States
Reviewed by: David Martin, University of Delaware, United States; Jit Muthuswamy, Arizona State University, United States
ISSN:1662-4548
1662-453X
1662-453X
DOI:10.3389/fnins.2018.00648