The integration and cooperation of mechanoreceptors, neurons and synapses in somatosensory systems enable humans to efficiently sense and process tactile information. Inspired by biological somatosensory systems, we report an optoelectronic spiking afferent nerve with neural coding, perceptual learning and memorizing capabilities to mimic tactile sensing and processing. Our system senses pressure by MXene-based sensors, converts pressure information to light pulses by coupling light-emitting diodes to analog-to-digital circuits, then integrates light pulses using a synaptic photomemristor. With neural coding, our spiking nerve is capable of not only detecting simultaneous pressure inputs, but also recognizing Morse code, braille, and object movement. Furthermore, with dimensionality-reduced feature extraction and learning, our system can recognize and memorize handwritten alphabets and words, providing a promising approach towards e-skin, neurorobotics and human-machine interaction technologies.

体感系统中机械感受器、神经元和突触的整合与协作使人类能够有效地感知和处理触觉信息。受生物体感系统的启发，我们报告了一种光电尖峰传入神经，具有神经编码、感知学习和记忆能力，可以模仿触觉感知和处理。我们的系统通过基于 MXene 的传感器感应压力，通过将发光二极管耦合到模数电路将压力信息转换为光脉冲，然后使用突触光忆阻器集成光脉冲。通过神经编码，我们的尖峰神经不仅能够检测同时的压力输入，还能识别莫尔斯电码、盲文和物体运动。此外，通过降维特征提取和学习，我们的系统可以识别和记忆手写字母和单词，为电子皮肤、神经机器人和人机交互技术提供了一种有前景的方法。