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

Area of Science:

• Biomedical Engineering
• Neuroscience
• Materials Science

Background:

• Conventional rigid electrocorticography (ECoG) electrodes lack conformability to the brain's complex topography, leading to poor contact, signal loss, and adverse tissue reactions.
• Patient-specific neural interfaces are crucial for effective neuromodulation, but current technologies struggle to meet this demand due to limitations in electrode design and material properties.

Purpose of the Study:

• To develop a novel platform for fabricating patient-specific neural interfaces that overcome the limitations of traditional rigid electrodes.
• To create highly conformable electrodes that precisely match individual brain gyral patterns for enhanced therapeutic outcomes.

Main Methods:

• Integrated platform combining MRI-based anatomical mapping, finite element analysis (FEA)-optimized mechanical design, and direct ink writing (DIW) 3D printing.
• Fabrication of honeycomb-inspired printable gel electrodes (HiPGE) using ultra-soft hydrogels engineered to match brain tissue stiffness (0.1–10 kPa).

Main Results:

• The developed HiPGE exhibits exceptional cortical conformability and adaptive interfacing due to its mechanical congruence with brain tissue.
• The honeycomb architecture and soft hydrogel composition ensure cost-efficiency, long-term durability, and reduced foreign body response.
• The patient-specific design and scalable fabrication approach offer a transformative framework for neural interface engineering.

Conclusions:

• The novel platform enables the creation of patient-specific, highly conformable neural interfaces (HiPGE) that significantly improve upon conventional rigid electrodes.
• This approach enhances precision, biocompatibility, and functional performance, paving the way for advanced neuromodulation therapies and neuroprosthetic applications.