Article
Development of 3D-penetrating neural stacks for intraneural recording and stimulation
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Published: | May 9, 2025 |
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Objective: In recent years, flexible neural implants are gaining in popularity as a means to reduce the mechanical mismatch with soft neural tissues. However, the realization of flexible microelectrode arrays (MEAs) that can capture the laminar structure of neural tissues across regions and with high spatial resolution remains a challenge. In this work we develop a flexible penetrating neural implant which combines high channel density with a three-dimensional electrode arrangement to target various neural structures, ranging from the retina to cortical and subcortical regions.
Materials and Methods: Individual parylene-C-based 2D MEAs comprising multiple shanks are fabricated and integrated with custom-made spacers produced through a two-photon polymerization process. Leveraging self-alignment features, the probes can be vertically stacked, creating a high-density 3D implant with minimal footprint, while dissolvable polymers and needles are utilized to aid the insertion of the device.
Results: A 64-channel 3D stacked intraretinal implant was successfully fabricated and validated in-vitro, demonstrating single-unit sampling capability along every axis inside an explanted rat retina. Additionally, we demonstrate that the stacking approach can be seamlessly combined with insertion aids to enable the simultaneous implantation of 3D shank arrays in a single step into deeper neural layers.
Discussion: This approach offers a scalable solution for deploying intralaminar neural probes to various neural targets. The flexible 3D architecture enables seamless integration with the tissue and mapping of neural activity across all spatial dimensions. Compared to alternatives, such as 3D kirigami- and 3D printed needle MEAs, 3D stack designs provide greater shank and electrode density, enabling single-cell modulation in high-density neuronal regions, regardless of penetration depth.
Acknowledgement: This work was supported by the Deutsche Forschungsgemeinschaft – RTG2610.