To address the limitations of current artificial neurons in neuromorphic hardware implementation, NbOx-based bifunctional memristors are fabricated to construct oscillatory units and advanced neuronal modules. Depending on the voltage biasing conditions, the NbOx-based memristor can operate as either a threshold switching memristor (TSM) or a dynamic memristor (DyM). TSMs are employed to build oscillatory units and further reconfigured into a weighted multi-terminal neuronal module, enabling real-time spatiotemporal summation of input spikes based on the leaky integrate-and-fire model. This module demonstrated the capability to perform spike summation and multi-weight synergy. Leveraging the gradual resistance change characteristic of DyM, a sequential encoder is implemented, allowing the system to recognize and respond to the temporal order of spiking signals. Additionally, DyM is integrated into the oscillatory unit to construct intensification and attenuation neurons, enabling short-term spiking frequency adaptation. The versatile spiking performance of our NbOx bifunctional memristor provides a strategic foundation for developing artificial neurons for next-generation bio-inspired spiking neural networks.
