Neural microelectrode is the important bridge of information exchange between the human body and machines. By recording and transmitting nerve signals with electrodes, people can control the external machines. At the same time, using electrodes to electrically stimulate nerve tissue, people with long-term brain diseases will be safely and reliably treated. Young’s modulus of the traditional rigid electrode probe is not matched well with that of biological tissue, and tissue immune rejection is easy to generate, resulting in the electrode not being able to achieve long-term safety and reliable working. In recent years, the choice of flexible materials and design of electrode structures can achieve modulus matching between electrode and biological tissue, and tissue damage is decreased. This review discusses nerve microelectrodes based on flexible electrode materials and substrate materials. Simultaneously, different structural designs of neural microelectrodes are reviewed. However, flexible electrode probes are difficult to implant into the brain. Only with the aid of certain auxiliary devices, can the implant be safe and reliable. The implantation method of the nerve microelectrode is also reviewed.
With the development of the Internet of things, artificial intelligence, and wearable devices, massive amounts of data are generated and need to be processed. High standards are required to store and analyze this information. In the face of the explosive growth of information, the memory used in data storage and processing faces great challenges. Among many types of memories, memristors have received extensive attentions due to their low energy consumption, strong tolerance, simple structure, and strong miniaturization. However, they still face many problems, especially in the application of artificial bionic synapses, which call for higher requirements in the mechanical properties of the device. The progress of integrated circuit and micro-processing manufacturing technology has greatly promoted development of the flexible memristor. The use of a flexible memristor to simulate nerve synapses will provide new methods for neural network computing and bionic sensing systems. In this paper, the materials and structure of the flexible memristor are summarized and discussed, and the latest configuration and new materials are described. In addition, this paper will focus on its application in artificial bionic synapses and discuss the challenges and development direction of flexible memristors from this perspective.