The integration and cooperation of nociceptors, neurons and synapses in the biological nervous system empower humans to efficiently perceive and process noxious information for avoiding dangers. Inspired by biological nervous systems, current artificial demonstrations include electrolyte-gate transistors, electrochemical metallization resistive switching devices and halide perovskite-based memristors. However, these devices suffer from integration difficulties and instability issues. Herein, we introduce a complementary metal oxide semiconductor (CMOS)-compatible simple and stable Pt/V₂O₅/Pt sandwich structure and carefully construct and modulate the suboxide V₂O_5−x and Mott VO₂ nanochannels in the layered V₂O₅ matrix to simulate brain-like processing and nervous pain perception functions, respectively. Simulation results demonstrate that the recognition accuracy of handwritten digits reaches 80% after only 5 training epochs and 89% after 52 epochs in a convolutional neural network based on the V₂O_5−x nanochannel synaptic device. The nociceptor with all key characteristics is perfectly imitated based on the VO₂ nanochannel threshold switching device. Especially, an ultralow threshold level of 0.4 V and sub-millisecond incubation time are observed in the nociceptor simulation, which could be needed in special injury situations. The proposed drift and Mott nanochannels in one device hold a tremendous potential as synaptic and nociceptive emulators for artificial intelligence systems.