Electrical synapses provide rapid, bidirectional communication in nervous systems, accomplishing tasks distinct from and complementary to chemical synapses. Here, we demonstrate an artificial electrical synapse based on second-order conductance transition (SOCT) in an Ag-based memristor for the first time. High-resolution transmission electron microscopy indicates that SOCT is mediated by the virtual silver electrode. Besides the conventional chemical synaptic behaviors, the biphasic plasticity of electrical synapses is well emulated by integrating the device with a photosensitive element to form an optical pre-processing unit (OPU), which contributes to the retinal neural circuitry and is adaptive to ambient illumination. By synergizing the OPU and spiking neural network (SNN), adaptive pattern recognition tasks are accomplished under different light and noise settings. This work not only contributes to the further completion of synaptic behaviour for hardware-level neuromorphic computing, but also potentially enables image pre-processing with light adaptation and noise suppression for adaptive visual recognition.

中文翻译：

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视网膜电突触中双相可塑性的光自适应模式预处理仿真

电突触在神经系统中提供快速的双向通讯，完成与化学突触不同的和互补的任务。在这里，我们首次展示了基于二次电导跃迁（SOCT）的基于Ag的忆阻器的人工电突触。高分辨率透射电子显微镜表明SOCT由虚拟银电极介导。除了常规的化学突触行为外，通过将设备与光敏元件集成在一起以形成光学预处理单元（OPU），可以很好地模拟电突触的双相可塑性，该光学预处理单元有助于视网膜神经电路并适应环境照明。通过协同OPU和增强神经网络（SNN），自适应模式识别任务是在不同的灯光和噪音设置下完成的。这项工作不仅有助于进一步完成用于硬件级神经形态计算的突触行为，而且还可以潜在地实现具有光适应性和噪声抑制的图像预处理，以实现适应性视觉识别。