# 3D-Printable, Honeycomb-Inspired Tissue-Like Bioelectrodes for Patient-Specific Neural Interface

## TL;DR

Researchers developed 3D-printed, soft, patient-specific bioelectrodes inspired by honeycombs to improve brain interface performance and safety.

## Contribution

A novel 3D-printed, honeycomb-inspired, ultra-soft electrode platform tailored to individual brain anatomy using MRI and FEA.

## Key findings

- HiPGE electrodes match brain tissue stiffness (0.1–10 kPa) for better conformability and signal quality.
- The platform combines MRI mapping, FEA, and 3D printing for scalable, patient-specific neural interfaces.
- The design overcomes limitations of rigid electrodes, improving biocompatibility and therapeutic outcomes.

## Abstract

The unique gyral patterns of the human brain demand patient-specific neural interfaces to achieve precise neuromodulation, mitigate adverse tissue responses, and optimize therapeutic efficacy and safety. One-size-fits-all, conventional rigid electrocorticography (ECoG) electrodes, standardized for mass production through lithographic techniques, exhibit limited conformability to the brain’s heterogeneous cortical topography. This mechanical mismatch results in poor electrode-tissue contact, signal loss, and foreign body responses. To address these limitations, we present an integrated novel platform, synergizing MRI-based anatomical mapping, finite element analysis (FEA)—optimized mechanical design, and direct ink writing (DIW) 3D printing to fabricate electrodes customized to individual gyral patterns. The resulting honeycomb-inspired printable gel electrode (HiPGE) employs a bioinspired honeycomb architecture with ultra-soft hydrogels, engineered to match the bending stiffness of brain tissue (0.1–10 kPa) while maintaining cost-efficiency and long-term durability. This mechanical congruence ensures exceptional cortical conformability and adaptive interfacing, circumventing the geometric and material limitations of traditional rigid electrodes. By combining patient-specific design with scalable fabrication, our platform establishes a transformative framework for neural interface engineering, enhancing precision, biocompatibility, and functional performance in neuromodulation therapies and neuroprosthetic applications.