Electrode sharpness and insertion speed reduce tissue damage near high-density penetrating arrays
I. N. McNamara, S. M. Wellman, L. Li, J. R. Eles, S. Savya, H. Sohal, M. Angle, T. D. Y. Kozai
Abstract
ObjectiveOver the past decade, neural electrodes have played a crucial role in bridging biological tissues with electronic and robotic devices. This study focuses on evaluating the optimal tip profile and insertion speed for effectively implanting Paradromics high-density Fine Microwire Arrays (FA) prototypes into the primary visual cortex (V1) of mice and rats, addressing the challenges associated with the "bed-of-nails" effect and tissue dimpling. ApproachTissue response was assessed by investigating the impact of electrodes on the blood-brain barrier (BBB) and cellular damage, with a specific emphasis on tailored insertion strategies to minimize tissue disruption during electrode implantation. Main ResultsElectro-sharpened arrays demonstrated a marked reduction in cellular damage within 50 m of the electrode tip compared to blunt and angled arrays. Histological analysis revealed that slow insertion speeds led to greater BBB compromise than fast and pneumatic methods. Successful single-unit recordings validated the efficacy of the optimized electro-sharpened arrays in capturing neural activity. SignificanceThese findings underscore the critical role of tailored insertion strategies in minimizing tissue damage during electrode implantation, highlighting the suitability of electro-sharpened arrays for long-term implant applications. This research contributes to a deeper understanding of the complexities associated with high-channel-count microelectrode array implantation, emphasizing the importance of meticulous assessment and optimization of key parameters for effective integration and minimal tissue disruption. By elucidating the interplay between insertion parameters and tissue response, our study lays a strong foundation for the development of advanced implantable devices with a reduction in reactive gliosis and improved performance in neural recording applications.
02 /Specification & Classification
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