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在单个无机突触中模拟短期可塑性和长时程增强。

Short-term plasticity and long-term potentiation mimicked in single inorganic synapses.

机构信息

International Center for Materials Nanoarchitectonics (MANA), National Institute for Materials Science (NIMS), 1-1 Namiki, Tsukuba, Ibaraki 305-0044, Japan.

出版信息

Nat Mater. 2011 Jun 26;10(8):591-5. doi: 10.1038/nmat3054.

DOI:10.1038/nmat3054
PMID:21706012
Abstract

Memory is believed to occur in the human brain as a result of two types of synaptic plasticity: short-term plasticity (STP) and long-term potentiation (LTP; refs 1-4). In neuromorphic engineering, emulation of known neural behaviour has proven to be difficult to implement in software because of the highly complex interconnected nature of thought processes. Here we report the discovery of a Ag(2)S inorganic synapse, which emulates the synaptic functions of both STP and LTP characteristics through the use of input pulse repetition time. The structure known as an atomic switch, operating at critical voltages, stores information as STP with a spontaneous decay of conductance level in response to intermittent input stimuli, whereas frequent stimulation results in a transition to LTP. The Ag(2)S inorganic synapse has interesting characteristics with analogies to an individual biological synapse, and achieves dynamic memorization in a single device without the need of external preprogramming. A psychological model related to the process of memorizing and forgetting is also demonstrated using the inorganic synapses. Our Ag(2)S element indicates a breakthrough in mimicking synaptic behaviour essential for the further creation of artificial neural systems that emulate characteristics of human memory.

摘要

记忆被认为是人类大脑中由于两种类型的突触可塑性而产生的

短期可塑性(STP)和长时程增强(LTP;refs 1-4)。在神经形态工程学中,由于思维过程的高度复杂的相互关联性质,模拟已知的神经行为已被证明难以在软件中实现。在这里,我们报告了一种 Ag(2)S 无机突触的发现,该突触通过使用输入脉冲重复时间来模拟 STP 和 LTP 特性的突触功能。这种被称为原子开关的结构,在临界电压下工作,以 STP 的形式存储信息,其电导水平会自发衰减以响应间歇性输入刺激,而频繁的刺激则会导致向 LTP 的转变。Ag(2)S 无机突触具有与单个生物突触类似的有趣特性,并且在单个设备中实现了动态记忆,而无需外部预编程。还使用无机突触演示了与记忆和遗忘过程相关的心理模型。我们的 Ag(2)S 元件表明,在模拟对进一步创建模拟人类记忆特征的人工神经网络至关重要的突触行为方面取得了突破。

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