Berdan Radu, Vasilaki Eleni, Khiat Ali, Indiveri Giacomo, Serb Alexandru, Prodromakis Themistoklis
Department of Electrical and Electronic Engineering, Imperial College London, London, SW7 2AZ, UK.
Department of Computer Science, University of Sheffield, Sheffield, UK.
Sci Rep. 2016 Jan 4;6:18639. doi: 10.1038/srep18639.
Neuromorphic architectures offer great promise for achieving computation capacities beyond conventional Von Neumann machines. The essential elements for achieving this vision are highly scalable synaptic mimics that do not undermine biological fidelity. Here we demonstrate that single solid-state TiO2 memristors can exhibit non-associative plasticity phenomena observed in biological synapses, supported by their metastable memory state transition properties. We show that, contrary to conventional uses of solid-state memory, the existence of rate-limiting volatility is a key feature for capturing short-term synaptic dynamics. We also show how the temporal dynamics of our prototypes can be exploited to implement spatio-temporal computation, demonstrating the memristors full potential for building biophysically realistic neural processing systems.
神经形态架构在实现超越传统冯·诺依曼机器的计算能力方面具有巨大潜力。实现这一愿景的关键要素是高度可扩展的突触模拟器,且不损害生物逼真度。在此,我们证明单个固态二氧化钛忆阻器可展现出在生物突触中观察到的非关联可塑性现象,这得益于其亚稳态记忆状态转变特性。我们表明,与固态存储器的传统用途相反,限速波动性的存在是捕捉短期突触动态的关键特征。我们还展示了如何利用我们原型的时间动态来实现时空计算,证明了忆阻器在构建生物物理逼真的神经处理系统方面的全部潜力。