conventional digital computers designed according to the von Neumann configuration, in which the arithmetic/logic units and memory units are separated, the brain outperforms digital computers due to its dramatically different configuration, in which arithmetic calculation and memory operate simultaneously without the burden of data transmission. Hardware implementation of neuromorphic systems has attracted much interest due to the great potential inherent in machine learning at low power consumption. Conventional systems based on complementary metal-oxide semiconductor devices have been used for the emulation of synaptic behaviors, [3,4] but these transistor devices bear little phenomenological similarity to the biological synapse [5] and the realization of neuromorphic computing systems by traditional transistor devices requires the construction of large-scale parallel logic and switching cells. This is accompanied by high power consumption, complex structural configurations, and intrinsic difficulty in scaling down to meet the needs of future nanoelectronic devices. Solid state devices that can accurately emulate the functions and plasticity of biological synapses will be the most important basic building blocks in brain-inspired computation systems. [6] Electronic devices that can simulate the dynamics of neurotransmission in the human body are of great interest for the development of artificial intelligence in modern information technology. An artificial nociceptor realized by a single metal-oxide nanobelt device with a unique capacitive-coupled threshold switching behavior is demonstrated. Via thermal admittance spectroscopy and temperature-dependent sweeping study, the properties of the nanobelt devices are determined by Schottky emission at low bias and by defect-assisted quantum tunneling at high bias subject to a threshold voltage. The low activation energy associated with dynamic electron trapping gives rise to a voltage-dependent volatile threshold switching behavior. This threshold switching behavior allows the emulation of several characteristic features of a nociceptor, a critical type of sensory neuron in the human body, including "threshold," "relaxation," "no adaptation," "allodynia," and "hyperalgesia" behaviors, essential for the realization of electronic sensory receptors that detect noxious stimuli and signal rapid warning to the central nervous system. One-dimensional metal oxide nanobelt devices of this type yield multifunctional nociceptor performance that is fundamental for applications in artificial intelligence systems, representing a key step in the realization of neural integrated devices via a bottom-up approach.