Spike-Timing Dependent Plasticity in Unipolar Silicon Oxide RRAM Devices

被引:22
|
作者
Zarudnyi, Konstantin [1 ]
Mehonic, Adnan [1 ]
Montesi, Luca [1 ]
Buckwell, Mark [1 ]
Hudziak, Stephen [1 ]
Kenyon, Anthony J. [1 ]
机构
[1] UCL, Dept Elect & Elect Engn, London, England
基金
英国工程与自然科学研究理事会;
关键词
resistive switching; resistance switching; STDP; RRAM; machine learning; neuromorphic systems; NEURAL-NETWORKS; SYSTEMS; VLSI; SYNAPSES; NEURONS;
D O I
10.3389/fnins.2018.00057
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Resistance switching, or Resistive RAM (RRAM) devices show considerable potential for application in hardware spiking neural networks (neuro-inspired computing) bymimicking some of the behavior of biological synapses, and hence enabling non-von Neumann computer architectures. Spike-timing dependent plasticity (STDP) is one such behavior, and one example of several classes of plasticity that are being examined with the aim of finding suitable algorithms for application in many computing tasks such as coincidence detection, classification and image recognition. In previous work we have demonstrated that the neuromorphic capabilities of silicon-rich silicon oxide (SiOx) resistance switching devices extend beyond plasticity to include thresholding, spiking, and integration. We previously demonstrated such behaviors in devices operated in the unipolar mode, opening up the question of whether we could add plasticity to the list of features exhibited by our devices. Here we demonstrate clear STDP in unipolar devices. Significantly, we show that the response of our devices is broadly similar to that of biological synapses. This work further reinforces the potential of simple two-terminal RRAM devices to mimic neuronal functionality in hardware spiking neural networks.
引用
收藏
页数:8
相关论文
共 50 条
  • [1] Efficient Design of Triplet Based Spike-Timing Dependent Plasticity
    Azghadi, Mostafa Rahimi
    Al-Sarawi, Said
    Iannella, Nicolangelo
    Abbott, Derek
    2012 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2012,
  • [2] Design and Implementation of BCM Rule Based on Spike-Timing Dependent Plasticity
    Azghadi, Mostafa Rahimi
    Al-Sarawi, Said
    Iannella, Nicolangelo
    Abbott, Derek
    2012 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2012,
  • [3] Spike-timing dependent plasticity and the cognitive map
    Bush, Daniel
    Philippides, Andrew
    Husbands, Phil
    O'Shea, Michael
    FRONTIERS IN COMPUTATIONAL NEUROSCIENCE, 2010, 4
  • [4] CMOL implementation of spiking neurons and spike-timing dependent plasticity
    Afifi, Ahmad
    Ayatollahi, Ahmad
    Raissi, Farshid
    INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS, 2011, 39 (04) : 357 - 372
  • [5] ASYMMETRIC SPIKE-TIMING DEPENDENT PLASTICITY OF STRIATAL NITRIC OXIDE-SYNTHASE INTERNEURONS
    Fino, E.
    Paille, V.
    Deniau, J. -M.
    Venance, L.
    NEUROSCIENCE, 2009, 160 (04) : 744 - 754
  • [6] Rate coding of spike-timing dependent plasticity: Activity-variation-timing dependent plasticity (AVTDP)
    Lee, Kyoobin
    Kwon, Dong-Soo
    NEUROCOMPUTING, 2009, 72 (4-6) : 1361 - 1368
  • [7] Biophysical and phenomenological models of multiple spike interactions in spike-timing dependent plasticity
    Badoual, Mathilde
    Zou, Quan
    Davison, Andrew P.
    Rudolph, Michael
    Bal, Thierry
    Fregnac, Yves
    Destexhe, Alain
    INTERNATIONAL JOURNAL OF NEURAL SYSTEMS, 2006, 16 (02) : 79 - 97
  • [8] Synchronous Spike Propagation in Izhikevich Neuron System with Spike-Timing Dependent Plasticity
    Nobukawa, Sou
    Nishimura, Haruhiko
    2012 PROCEEDINGS OF SICE ANNUAL CONFERENCE (SICE), 2012, : 453 - 458
  • [9] Demonstration of Spike Timing Dependent Plasticity in CBRAM Devices with Silicon Neurons
    Mahalanabis, D.
    Sivaraj, M.
    Chen, W.
    Shah, S.
    Barnaby, H. J.
    Kozicki, M. N.
    Christen, J. Blain
    Vrudhula, S.
    2016 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS), 2016, : 2314 - 2317
  • [10] Spike-Timing Dependent Plasticity Effect on the Temporal Patterning of Neural Synchronization
    Zirkle, Joel
    Rubchinsky, Leonid L.
    FRONTIERS IN COMPUTATIONAL NEUROSCIENCE, 2020, 14 (14)