Bio-inspired optoelectronic synapse with nociceptive behavior for neuromorphic computing

The development of energy-efficient and multimodal neuromorphic devices is critical importance for advancing next-generation bioinspired perception systems. However, achieving multimodal synaptic plasticity, biomimetic nociceptive functions, and efficient neuromorphic computing within a single monolithic device remains a significant challenge, particularly under low-power optoelectronic co-modulation. Herein, we present an optoelectronic memristive synapse based on a solution-processed PEDOT:PSS/IGZO heterojunction that simultaneously emulates biological synaptic plasticity and nociceptive behavior. The device successfully reproduces representative synaptic functions, including paired-pulse facilitation (PPF), long-term potentiation (LTP), and long-term depression (LTD), under both electrical and optical stimulation. Upon pulsed ultraviolet illumination, the device exhibits distinct excitatory postsynaptic currents (EPSCs) are generated, accompanied by a dynamic transition from short-term memory (STM) to long-term memory (LTM), effectively mimicking the biological learning-forgetting-relearning process. Furthermore, the device faithfully replicates key nociceptive characteristics, including threshold response, relaxation, noxious adaptation, and hyperalgesia. When implemented in a convolutional neural network (CNN), the memristor-based system achieves recognition accuracies of 97.72% and 82.49% on the MNIST and Fashion-MNIST datasets, respectively. This work provides a promising strategy for the development of multifunctional artificial nociceptors with multimodal sensing capabilities and offers a viable pathway toward energy-efficient neuromorphic computing systems.