This work combines a matrix of electrical pathways connected by memristors that emulate the wiring transmission and plasticity extant within the brain’s neural networks. Importantly, this memristor matrix is coupled to a light-mediated modulatory system that, akin to volume transmission, induces widespread but specific influences upon assemblies of connections across the network. The emulated brain neuromodulation and resultant associative learning demonstrate significant improvements in size, weight, and power (SWaP) efficiencies and enhanced powers of learning and memory.

中文翻译：

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神经形态纳米复合材料的异刺激化学调节，用于时间、功率和数据高效的机器学习

这项工作结合了由忆阻器连接的电通路矩阵，模拟大脑神经网络内存在的线路传输和可塑性。重要的是，该忆阻器矩阵与光介导的调制系统耦合，该系统类似于体积传输，对整个网络的连接组件产生广泛但特定的影响。模拟的大脑神经调节和由此产生的联想学习证明了尺寸、重量和功率 (SWaP) 效率的显着改善以及学习和记忆能力的增强。