Here, we present fibrous neuromorphic devices (FNDs) that serves as multi-level nerve pathways to implement a biomimetic knee-jerk reflex and cognitive activities. By the tunable charge-carrier polarity of the fibrous electrolyte, FNDs successfully simulate the competition between glutamate and γ-aminobutyric acid (GABA) in a multiplexed transmission process in the human nervous system. To emulate action signals that respond to environmental stimuli in a low-level nerve pathway, a fiber-level neurologically integrated muscular system was constructed by cascading with FNDs and artificial muscle fibers; the system realized unconditioned reflex, even under loads of several Newtons. To emulate the high-level nerve pathway, multiple conductive states of FNDs were used to construct flexible neuromorphic networks; the recognition accuracy for the Fashion MNIST dataset was > 83%, with < 0.1% loss of accuracy even after 100 bending cycles, which represents the most stable recognition result for flexible neuromorphic electronics so far. The presented FNDs provide an excellent basis for the development of human-compatible artificial neurological systems.

在这里，我们提出了作为多级神经通路的纤维神经形态装置 (FND)，以实现仿生膝跳反射和认知活动。通过纤维电解质的可调电荷载流子极性，FNDs成功模拟了谷氨酸和γ-氨基丁酸（GABA）在人类神经系统中的多路传输过程中的竞争。为了模拟在低级神经通路中对环境刺激作出反应的动作信号，通过级联 FND 和人造肌纤维构建了一个纤维级的神经学整合肌肉系统；即使在几个牛顿的负载下，该系统也实现了无条件反射。为了模拟高级神经通路，使用 FND 的多种导电状态来构建灵活的神经形态网络；Fashion MNIST 数据集的识别准确率 > 83%，即使经过 100 次弯曲循环，准确率损失也小于 0.1%，这是迄今为止柔性神经形态电子学最稳定的识别结果。所提出的 FND 为开发与人类兼容的人工神经系统提供了极好的基础。