Abstract: With the explosive growth of information and the limitations of microelectronic processing technology,complementary metal oxide semiconductor(CMOS)devices are difficult to apply to the construction of largescale neuromorphic devices. The use of non-CMOS devices to achieve synaptic plasticity simulation is considered to be an effective way to build artificial neural networks in the post-Moore era. Among many non-CMOS devices,the memristor has the advantages of adjustable conductance and simple structure,and is considered to be the basic element to realize the synaptic function. Particularly,the electrochemical metallization mechanism(ECM)memristors have the advantages of ultra-high-density integration and insensitive to material properties. However,ECM electronic synapses have the problem of poor conductance controllability,which restricts the realization of high-performance neuromorphic devices. Researchers have conducted a lot of research on the conductance controllability of ECM electronic synapses. This review summarizes the optimization methods of conductance controllability of ECM electronic synapse from the perspective of device structure and materials.