The Development and Evolution of Substrate Materials for Brain–Computer Interfaces
Brain–Computer Interfaces (BCIs) hold tremendous potential for neurological therapeutics and neuroprosthetics; however, their long-term clinical viability is fundamentally limited by chronic interfacial failure. This failure originates from the profound biomechanical mismatch between synthetic microelectrodes and ultra-soft brain tissue, which inevitably triggers persistent mechanical trauma, severe foreign body response (FBR), and insulating glial scarring. In this review, we systematically trace the material and structural evolution of implantable neural interfaces designed to bridge this critical gap. We detail the chronological paradigm shift from rigid inorganic substrates (e.g., silicon) to flexible yet inextensible polymers (e.g., Polyimide, SU-8) for conformal mapping, and subsequently to intrinsically stretchable elastomers (e.g., polydimethylsiloxane polyurethane) that effectively absorb dynamic physiological micro-shear forces. Most importantly, we highlight the emerging frontier of electrospun nanofibrous microelectrodes. By uniquely combining macroscopic tissue-level stretchability with an interconnected, highly permeable 3D topography that mimics the native extracellular matrix (ECM), these biomimetic scaffolds successfully overcome the metabolic limitations of dense elastomeric films. Finally, we discuss current challenges and future perspectives, ranging from scalable high-density manufacturing and active biochemical modulation to fully untethered integration, charting a comprehensive roadmap for next-generation, chronically stable neural interfaces.
Authors
- Yidan Gao (ORCID: https://orcid.org/0000-0002-7519-7229)
- Jiujiang Ji (ORCID: https://orcid.org/0000-0003-1438-5223)
- Mei Tian (ORCID: https://orcid.org/0009-0003-3603-1992)
- Juan Liu
- Yen Wei
Institutions
- Chung Yuan Christian University (TW)
- Beijing University of Chinese Medicine (CN)
- Fudan University (CN)
- North Minzu University (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- Polymers
- Published
- 2026-10-19
- DOI
- https://doi.org/10.3390/polym18202569
- Primary Topic
- Neuroscience and Neural Engineering
- Type
- article
- Field-Weighted Citation Impact
- 0.00