Nowadays, the huge power consumption and the inability of the conventional circuits to deal with real-time classification tasks have necessitated the devising of new electronic devices with inherent neuromorphic functionalities. Resistive switching memories arise as an ideal candidate due to their low footprint and small leakage current dissipation, while their intrinsic randomness is smoothly leveraged for implementing neuromorphic functionalities. In this review, valence change memories or conductive bridge memories for emulating neuromorphic characteristics are demonstrated. Moreover, the impact of the device structure and the incorporation of Pt nanoparticles is thoroughly investigated. Interestingly, our devices possess the ability to emulate various artificial synaptic functionalities, including paired-pulsed facilitation and paired-pulse depression, long-term plasticity and four different types of spike-dependent plasticity. Our approach provides valuable insights from a material design point of view towards the development of multifunctional synaptic elements that operate with low power consumption and exhibit biological-like behavior.