As scientists discovered that raw neurological signals could translate into bioelectric information, brain–machine interfaces (BMI) for experimental and clinical studies have experienced massive growth. Developing suitable materials for bioelectronic devices to be used for real-time recording and data digitalizing has three important necessitates which should be covered. Biocompatibility, electrical conductivity, and having mechanical properties similar to soft brain tissue to decrease mechanical mismatch should be adopted for all materials. In this review, inorganic nanoparticles and intrinsically conducting polymers are discussed to impart electrical conductivity to systems, where soft materials such as hydrogels can offer reliable mechanical properties and a biocompatible substrate. Interpenetrating hydrogel networks offer more mechanical stability and provide a path for incorporating polymers with desired properties into one strong network. Promising fabrication methods, like electrospinning and additive manufacturing, allow scientists to customize designs for each application and reach the maximum potential for the system. In the near future, it is desired to fabricate biohybrid conducting polymer-based interfaces loaded with cells, giving the opportunity for simultaneous stimulation and regeneration. Developing multi-modal BMIs, Using artificial intelligence and machine learning to design advanced materials are among the future goals for this field.

中文翻译：

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用于脑机接口的导电聚合物基纳米结构材料

随着科学家发现原始神经信号可以转化为生物电信息，用于实验和临床研究的脑机接口（BMI）经历了巨大的增长。开发适合生物电子设备用于实时记录和数据数字化的材料具有三个重要的必要条件。所有材料均应采用生物相容性、导电性以及具有与软脑组织相似的机械性能以减少机械失配。在这篇综述中，讨论了无机纳米粒子和本征导电聚合物，以赋予系统导电性，其中水凝胶等软材料可以提供可靠的机械性能和生物相容性基材。互穿水凝胶网络提供了更高的机械稳定性，并提供了一种将具有所需性能的聚合物结合到一个强大的网络中的途径。静电纺丝和增材制造等有前途的制造方法使科学家能够为每种应用定制设计并发挥系统的最大潜力。在不久的将来，人们希望制造出负载细胞的生物混合导电聚合物界面，从而为同时刺激和再生提供机会。开发多模式BMI、利用人工智能和机器学习设计先进材料是该领域的未来目标。