Injectable Antifouling Adhesive Hydrogel Enables Robust Neural Interfaces for Stable ECoG Recording

Micro-electrocorticography (micro-ECoG) provides high-spatiotemporal-resolution cortical sensing for brain-computer interfaces, but stable subdural recording remains difficult because dural opening disrupts barrier integrity, cortical micromotion weakens device-tissue coupling, and biofouling triggers foreign body responses (FBR) that isolate the array. Here, we present an injectable, in situ-forming multifunctional hydrogel designed to treat these failure modes as one integrated interface problem rather than three separate ones. The hydrogel combines dopamine-grafted sodium alginate (SA-DA) and branched poly(ethylene imine) (PEI) in a charge-balanced pseudozwitterionic macromolecular network that resists nonspecific protein adsorption while providing catechol-mediated wet adhesion. Through dual macromolecular crosslinking, the hydrogel undergoes rapid gelation under surgically compatible conditions, conformally seals dural defects, fills interfacial gaps, and provides wet tissue adhesion without relying on diffusible small-molecule monomers. When integrated with a 128-channel flexible micro-ECoG mesh array, this platform reduced glial activation and fibrotic encapsulation and preserved stable, high-fidelity cortical recordings over a 3-week early-chronic period. More broadly, this study establishes a design principle for sustained soft bioelectronics: long-term function can be improved by co-engineering barrier restoration, interfacial adhesion, and antifouling protection within a single interface material.

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Publication Details

Journal
Advanced Healthcare Materials
Published
2026-06-29
DOI
https://doi.org/10.1002/adhm.71397
Primary Topic
Neuroscience and Neural Engineering
Type
article
Field-Weighted Citation Impact
0.00

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article

Injectable Antifouling Adhesive Hydrogel Enables Robust Neural Interfaces for Stable ECoG Recording

X W Li, Zhonghao Zou, Zhiqiang Luo, Xinyu Wang et al.
Advanced Healthcare Materials
Neuroscience and Neural Engineering
article

Injectable Antifouling Adhesive Hydrogel Enables Robust Neural Interfaces for Stable ECoG Recording

X W Li, Zhonghao Zou, Zhiqiang Luo, Xinyu Wang, Bing Liu, Jie Peng, Chuan Gao, Wenlong Li, Chong Ma, Yu Yang
article en

Abstract

Micro-electrocorticography (micro-ECoG) provides high-spatiotemporal-resolution cortical sensing for brain-computer interfaces, but stable subdural recording remains difficult because dural opening disrupts barrier integrity, cortical micromotion weakens device-tissue coupling, and biofouling triggers foreign body responses (FBR) that isolate the array. Here, we present an injectable, in situ-forming multifunctional hydrogel designed to treat these failure modes as one integrated interface problem rather than three separate ones. The hydrogel combines dopamine-grafted sodium alginate (SA-DA) and branched poly(ethylene imine) (PEI) in a charge-balanced pseudozwitterionic macromolecular network that resists nonspecific protein adsorption while providing catechol-mediated wet adhesion. Through dual macromolecular crosslinking, the hydrogel undergoes rapid gelation under surgically compatible conditions, conformally seals dural defects, fills interfacial gaps, and provides wet tissue adhesion without relying on diffusible small-molecule monomers. When integrated with a 128-channel flexible micro-ECoG mesh array, this platform reduced glial activation and fibrotic encapsulation and preserved stable, high-fidelity cortical recordings over a 3-week early-chronic period. More broadly, this study establishes a design principle for sustained soft bioelectronics: long-term function can be improved by co-engineering barrier restoration, interfacial adhesion, and antifouling protection within a single interface material.

Advanced Healthcare Materials
Wuhan University of Technology (CN), Center for Excellence in Brain Science and Intelligence Technology (CN), Huazhong University of Science and Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 11%
Neuroscience and Neural Engineering
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