Long‐Term Stable Subdural Recordings Enabled by Fibrosis‐Resistant Hydrogel‐Integrated µECoG Arrays

The long-term performance of microscale subdural arrays is often compromised by adverse tissue responses, leading to increased electrochemical impedance and signal deterioration during chronic applications. Here, the study presents an adhesive hydrogel-integrated micro-electrocorticography (aGel-µECoG) array that improves mechanical compatibility and adhesion to brain tissue, effectively mitigating tissue responses and enabling stable, high-performance electrical communication over days to months. The hydrogel consists of a hydrophilic polyvinyl alcohol and hydrophobic poly3-(trimethoxysilyl) propyl methacrylate heteronetwork, serving as a biological and mechanical bridging to enable seamless, anti-fibrotic, long-term integration with brain tissue. The aGel-µECoG achieves robust tissue adhesion (25.2 ± 3.8 kPa) with reversible and safe removal, enabling sutureless implantation. With an ultrathin 10-µm ionic conductive hydrogel coating, the array exhibits high electrical fidelity, effectively preserving fine-grained sub-millimeter spatial resolution and maintaining unattenuated signal strength for functional cortical mapping. Compared to conventional µECoG arrays, aGel-µECoG exhibits a 20-fold reduction in acute-phase impedance increases, attributed to significantly reduced neuroinflammation and fibrotic tissue formation, as confirmed by histological analyses. Long-term recordings further reveal that aGel-µECoG maintained 94.8% of the signal-to-noise ratio for steady-state visually evoked potentials over 16 weeks, whereas uncoated µECoG arrays declined to 69.5%. These findings establish aGel-µECoG as a durable and high-performance neural interface.

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Publication Details

Journal
Advanced Science
Published
2025-10-08
DOI
https://doi.org/10.1002/advs.202515453
Citations
1
Primary Topic
Neuroscience and Neural Engineering
Type
article
Field-Weighted Citation Impact
0.91
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article

Long‐Term Stable Subdural Recordings Enabled by Fibrosis‐Resistant Hydrogel‐Integrated µECoG Arrays

Xin Fu, Hao Zhong, Ting Wu, Liju Xu et al.
1 citations
Advanced Science
Neuroscience and Neural Engineering
0.91
article

Long‐Term Stable Subdural Recordings Enabled by Fibrosis‐Resistant Hydrogel‐Integrated µECoG Arrays

Xin Fu, Hao Zhong, Ting Wu, Liju Xu, Kaichun Wu, Ke Li, Lei Wang, Lin Chen, Jin Min Guo, Yongpeng Zhao, Yang Shen, Dong Qiu, Wu Fan, Huiling Zhang
article en
1 citations

Abstract

The long-term performance of microscale subdural arrays is often compromised by adverse tissue responses, leading to increased electrochemical impedance and signal deterioration during chronic applications. Here, the study presents an adhesive hydrogel-integrated micro-electrocorticography (aGel-µECoG) array that improves mechanical compatibility and adhesion to brain tissue, effectively mitigating tissue responses and enabling stable, high-performance electrical communication over days to months. The hydrogel consists of a hydrophilic polyvinyl alcohol and hydrophobic poly3-(trimethoxysilyl) propyl methacrylate heteronetwork, serving as a biological and mechanical bridging to enable seamless, anti-fibrotic, long-term integration with brain tissue. The aGel-µECoG achieves robust tissue adhesion (25.2 ± 3.8 kPa) with reversible and safe removal, enabling sutureless implantation. With an ultrathin 10-µm ionic conductive hydrogel coating, the array exhibits high electrical fidelity, effectively preserving fine-grained sub-millimeter spatial resolution and maintaining unattenuated signal strength for functional cortical mapping. Compared to conventional µECoG arrays, aGel-µECoG exhibits a 20-fold reduction in acute-phase impedance increases, attributed to significantly reduced neuroinflammation and fibrotic tissue formation, as confirmed by histological analyses. Long-term recordings further reveal that aGel-µECoG maintained 94.8% of the signal-to-noise ratio for steady-state visually evoked potentials over 16 weeks, whereas uncoated µECoG arrays declined to 69.5%. These findings establish aGel-µECoG as a durable and high-performance neural interface.

Advanced ScienceVol. 12(47)
Capital Medical University (CN), Chinese Academy of Sciences (CN), Chinese Academy of Medical Sciences & Peking Union Medical College (CN), Chinese Institute for Brain Research (CN), Beijing National Laboratory for Molecular Sciences (CN), University of Chinese Academy of Sciences (CN)
Openalex Percentile: Top 21%
Neuroscience and Neural Engineering
0.91
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