Mechanical mismatch between conventional rigid electrodes and neural tissues substantially constrains the long-term stability, biocompatibility, and practical usability of Brain–computer interfaces (BCIs). Flexible materials have therefore emerged as a promising class of alternatives. This study aimed to quantitatively assess flexible material strategies on BCI performance and to establish an evidence chain linking material properties to signal quality. Following the PRISMA guidelines, we systematically searched five databases and included six animal studies, applying a random-effects model to pool effect sizes and conducting subgroup analyses to explore heterogeneity. The results showed that flexible materials significantly reduced electrode-tissue interface impedance and inflammation risk ratio, while improving the SNR. However, hydrogel-based materials demonstrated optimal biocompatibility but lower conductivity, whereas PEDOT:PSS composites offered superior electrical performance but were prone to long-term degradation. For chronic implantable BCIs, ideal performance is achieved either by selecting materials with a Young’s modulus ≤ 1–10 MPa. Tuning stiffness to the brain-matched regime (102 −103 kPa) represents a critical compromise between biocompatibility and manufacturability, whereas pursuing ultra-soft materials (<10 kPa) yield marginal gains disproportionate to the additional fabrication complexity. Future development should therefore emphasize bioadaptive, feedback-driven architectures and multi-scale microporous hydrogel systems to accelerate clinical translation.
Peixin et al. (Wed,) studied this question.