Towards a Seamless and Stable Neural Tissue-Electrode Interface

Tracy Cui
University of Pittsburgh


Abstract: Micro-fabricated neural electrode arrays, placed in the nervous system to record neural activity or detect neurotransmitters have tremendous research and clinical significance.  Current arrays experience chronic failure including signal drift and degradation due to biochemical, mechanical and electrical mismatch between the artificial device and brain tissue. Several bioengineering strategies are being investigated towards a seamless and stable neural electrode-tissue interface. The first strategy is to camouflage the abiotic implant with biomolecules. Neural adhesion molecule L1 has been coated onto the implant surface and showed to improve neuronal growth on and around the implant while reducing microglia activation. Preliminary experiments showed that L1 drastically improved the recording yield and longevity of neural electrode arrays. The mechanism and longevity of the coating as well as alternative biomolecules for coating are currently being investigated. Secondly, therapeutics that target inflammation, degeneration, BBB breach and oxidative stress are being examined while on demand drug delivery technologies based on nanostructured electroactive conductive polymers. Thirdly, it has been hypothesized that the mechanical mismatch between the stiff device and soft brain tissue acerbates the chronic tissue responses. Current arrays are mostly made of materials that are 3-6 orders of magnitude stiffer than the brain tissue. To overcome this issue, new materials and designs are being developed that matches the mechanical properties of the brain. To facilitate the implantation of ultracompliant devices, bio-dissolvable shuttle will be used. Lastly, to better characterize the cellular and vascular response at the interface and better understand the relationship between tissue reactions and recording performance, new methods of chronic neural recording evaluation as well as live-animal multi-photon imaging have been developed. The ultimate solution to a reliable and seamlessly integrated neural interface may be a combinatorial approach that takes advantage of multiple strategies discussed above and beyond.

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