Objective: Neural electrophysiology is often conducted with traditional, rigid depth probes. The mechanical mismatch between these probes and soft brain tissue is unfavorable for tissue interfacing. Making probes compliant can improve biocompatibility, but as a consequence, they become more difficult to insert into the brain. Therefore, new methods for inserting compliant neural probes must be developed. \n Approach: Here, we present a new bioresorbable shuttle based on the hydrolytically degradable poly(vinyl alcohol) (PVA) and poly(lactic-co-glycolic acid) (PLGA). We show how to fabricate the PVA/PLGA shuttles on flexible and thin parylene probes. The method consists of PDMS molding used to fabricate a PVA shuttle aligned with the probe and to also impart a sharp tip necessary for piercing brain tissue. The PVA shuttle is then dip-coated with PLGA to create a bi-layered shuttle. \n Main results: While single layered PVA shuttles are able to penetrate agarose brain models, only limited depths were achieved and repositioning was not possible due to the fast degradation. We demonstrate that a bilayered approach incorporating a slower dissolving PLGA layer prolongs degradation and enables facile insertion for at least several millimeters depth. Impedances of electrodes before and after shuttle preparation were characterized and showed that careful deposition of PLGA is required to maintain low impedance. Facilitated by the shuttles, compliant parylene probes were also successfully implanted into anaesthetized mice and enabled the recording of high quality local field potentials. \n Significance: This work thereby presents a solution towards addressing a key challenge of implanting compliant neural probes using a two polymer system. PVA and PLGA are polymers with properties ideal for translation: commercially available, biocompatible with FDA-approved uses and bioresorbable. By presenting new ways to implant compliant neural probes, we can begin to fully evaluate their chronic biocompatibility and performance compared to traditional, rigid electronics.
|Original language||English (US)|
|Journal||Journal of Neural Engineering|
|State||Published - Sep 11 2018|
Bibliographical noteKAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): OSR-2016-CRG5-3003
Acknowledgements: The authors acknowledge support from the “Fondation pour la Recherche Médicale” under grant agreement DBS20131128446, the Whitaker International Program (A.R.), the European Union's Horizon 2020 Research and Innovation Programme under grant agreement No. 732032 (BrainCom), and the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under award No. OSR-2016-CRG5-3003. In addition, A.S., A.K. and A.W. acknowledge support from the European Research Council (ERC) under the European Union’s Horizon 2020 research and Innovation Program (grant agreement No 716867). A.K. was financed by EC Marie Curie Intra-European Fellowship (ImagINE, grant agreement No 625372).
This publication acknowledges KAUST support, but has no KAUST affiliated authors.