Department of Chemistry and Biochemistry, University of California Los Angeles, Los Angeles, California, United States of America.
PLoS One. 2012;7(8):e42772. doi: 10.1371/journal.pone.0042772. Epub 2012 Aug 6.
Efforts to emulate the formidable information processing capabilities of the brain through neuromorphic engineering have been bolstered by recent progress in the fabrication of nonlinear, nanoscale circuit elements that exhibit synapse-like operational characteristics. However, conventional fabrication techniques are unable to efficiently generate structures with the highly complex interconnectivity found in biological neuronal networks. Here we demonstrate the physical realization of a self-assembled neuromorphic device which implements basic concepts of systems neuroscience through a hardware-based platform comprised of over a billion interconnected atomic-switch inorganic synapses embedded in a complex network of silver nanowires. Observations of network activation and passive harmonic generation demonstrate a collective response to input stimulus in agreement with recent theoretical predictions. Further, emergent behaviors unique to the complex network of atomic switches and akin to brain function are observed, namely spatially distributed memory, recurrent dynamics and the activation of feedforward subnetworks. These devices display the functional characteristics required for implementing unconventional, biologically and neurally inspired computational methodologies in a synthetic experimental system.
通过神经形态工程来模拟大脑强大的信息处理能力的努力得到了最近在制造具有类突触操作特性的非线性、纳米级电路元件方面的进展的支持。然而，传统的制造技术无法有效地生成具有生物神经元网络中发现的高度复杂的相互连接性的结构。在这里，我们展示了一种自组装神经形态器件的物理实现，该器件通过由嵌入在复杂银纳米线网络中的超过 10 亿个相互连接的原子开关无机突触组成的基于硬件的平台，实现了系统神经科学的基本概念。对网络激活和被动谐波产生的观察结果表明，集体对输入刺激的反应与最近的理论预测一致。此外，还观察到了仅在原子开关的复杂网络中出现的独特的涌现行为，类似于大脑功能，即空间分布式记忆、递归动力学和前馈子网的激活。这些器件显示了在合成实验系统中实现非常规的、受生物和神经启发的计算方法所需的功能特性。
