Honeycomb-inspired 3D-printed electrodes for personalized brain monitoring
When it comes to neural interfaces, one size doesn’t fit all. Thankfully, scientists have now designed 3D-printed soft electrodes, inspired by honeycomb, to perfectly match an individual’s brain surface and, with any luck, improve neurological disease monitoring and treatment.
Led by researchers at Penn State (PA, USA), a new study has introduced a honeycomb-esque printable gel electrode, aka HiPGE, which uses a bio-inspired architecture and ultra-soft hydrogels enabling it to mold to 3D-printed models of patients’ brains. Outperforming traditional electrode designs, the devices remained effective and biologically compatible in animal models, opening up an exciting avenue toward personalized neuromodulation therapies and neuroprosthetics.
The unique folds of the human cerebral cortex are formed through a process called gyrification, which packs billions of neurons into a complex, multi-layered structure. We each have our own gyral pattern – think of it as a fingerprint for the brain – shaped by factors including sex, age, weight and height, and as such, require individualized interfaces to achieve precise neuromodulation and optimize therapeutic efficacy and safety.
Despite this, conventional neural interfaces tend to be one-size-fits-all, relying on rigid electrodes standardized for mass production, which can result in poor electrode–tissue contact, signal loss and foreign body responses.
“This motivated us to create electrodes that are tailored for each individual, based on the structure of their brain,” corresponding author Tao Zhou explained of the study’s rationale.
Zhou and co-authors developed a novel neural interface platform, combining MRI scanning, finite element analysis and 3D printing, for scalable, patient-specific device fabrication. Key to its success is HiPGE, a hydrogel-based electrode engineered with a honeycomb-like structure that offers flexibility and durability, while maintaining exceptional cost and material efficiency.
Production kicked off with MRI scans of 21 patients’ brains, from which the researchers reconstructed 3D models, each with unique gyral complexity. Then, they integrated MRI-based surface curvature analysis and region-of-interest mapping to design electrodes tailored to fit each individual cerebral cortex.
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Finite element analysis was used to optimize device geometry, enhancing electrode design efficiency and precision. This revealed that the stiffness of HiPGE closely matched brain tissue, outperforming rigid controls. Meanwhile, distance contour maps and strain distribution analysis demonstrated that HiPGE maintained closer contact with brain tissue and induced minimal tissue deformation when compared to controls. Next, in silico modeling was used to show that the device achieved a near-perfect connectivity to electrical signals in the brain.
After this validation, five patients were randomly selected, and their complementary electrodes were 3D printed using direct ink writing. The researchers also 3D-printed models of the patients’ brains to assess how well the neural interfaces matched each individual’s distinctive brain anatomy, indicating that the personalized HiPGEs exhibited precise conformity to the shapes and spatial arrangements of the cortex.
Finally, the team tested their system in rats, designing and creating personalized electrodes to closely fit the rodents’ brains. The animals were each fitted with a personalized HiPGE on the left side of their brain and a conventional electrode on the right side, with the personalized system consistently exhibiting superior electrical activity recording performance.
After 4 weeks, fluorescent imaging of excised brain tissue illustrated that there was no obvious immune response to the implanted HiPGE.
Taken together, these findings indicate that the 3D-printed electrodes seamlessly conform to cortical contours, eliminating mechanical mismatch and providing high-fidelity electrophysiological recording with minimal adverse effects. As a result, the research establishes a transformative framework for neural interface engineering, which will hopefully enhance the precision, biocompatibility and performance of neuroprosthetics and personalized neuromodulation therapies.
“We are looking to further improve this technology to optimize the electrodes to monitor for specific diseases,” Zhou added. “In the future, we would really like to work with patients to see how this approach could support brain monitoring and disease treatment in clinical settings.”