Pulse lead/lag timing detection for adaptive feedback and control based on optical spike-timing-dependent plasticity

被引:54
作者
Fok, Mable P. [1 ]
Tian, Yue [1 ]
Rosenbluth, David [2 ]
Prucnal, Paul R. [1 ]
机构
[1] Princeton Univ, Dept Elect Engn, Lightwave Commun Res Lab, Princeton, NJ 08544 USA
[2] Lockheed Martin Adv Technol Lab, Cherry Hill, NJ 08002 USA
关键词
SYNAPTIC MODIFICATION; LEARNING RULE; CIRCUITS; NEURON; MODEL;
D O I
10.1364/OL.38.000419
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Biological neurons perform information processing using a model called pulse processing, which is both computationally efficient and scalable, adopting the best features of both analog and digital computing. Implementing pulse processing with photonics can result in bandwidths that are billions of times faster than biological neurons and substantially faster than electronics. Neurons have the ability to learn and adapt their processing based on experience through a change in the strength of synaptic connections in response to spiking activity. This mechanism is called spike-timing-dependent plasticity (STDP). Functionally, STDP constitutes a mechanism in which strengths of connections between neurons are based on the timing and order between presynaptic spikes and postsynaptic spikes, essentially forming a pulse lead/lag timing detector that is useful in feedback control and adaptation. Here we report for the first time the demonstration of optical STDP that is useful in pulse lead/lag timing detection and apply it to automatic gain control of a photonic pulse processor. (c) 2013 Optical Society of America
引用
收藏
页码:419 / 421
页数:3
相关论文
共 22 条
  • [1] Functional significance of long-term potentiation for sequence learning and prediction
    Abbott, LF
    Blum, KI
    [J]. CEREBRAL CORTEX, 1996, 6 (03) : 406 - 416
  • [2] Synaptic modification by correlated activity: Hebb's postulate revisited
    Bi, GQ
    Poo, MM
    [J]. ANNUAL REVIEW OF NEUROSCIENCE, 2001, 24 : 139 - 166
  • [3] A model of spatial map formation in the hippocampus of the rat
    Blum, KI
    Abbott, LF
    [J]. NEURAL COMPUTATION, 1996, 8 (01) : 85 - 93
  • [4] Buesing L., 2007, ADV NEURAL INFORM PR, V20, P193
  • [5] Spike timing-dependent plasticity: A Hebbian learning rule
    Caporale, Natalia
    Dan, Yang
    [J]. ANNUAL REVIEW OF NEUROSCIENCE, 2008, 31 : 25 - 46
  • [6] Spike-timing-dependent plasticity and relevant mutual information maximization
    Chechik, G
    [J]. NEURAL COMPUTATION, 2003, 15 (07) : 1481 - 1510
  • [7] Signal feature recognition based on lightwave neuromorphic signal processing
    Fok, Mable P.
    Deming, Hannah
    Nahmias, Mitchell
    Rafidi, Nicole
    Rosenbluth, David
    Tait, Alexander
    Tian, Yue
    Prucnal, Paul R.
    [J]. OPTICS LETTERS, 2011, 36 (01) : 19 - 21
  • [8] Lightwave Neuromorphic Signal Processing
    Fok, Mable P.
    Rosenbluth, David
    Kravtsov, Konstantin
    Prucnal, Paul R.
    [J]. IEEE SIGNAL PROCESSING MAGAZINE, 2010, 27 (06) : 160 - 158
  • [9] Spike-timing-dependent synaptic modification induced by natural spike trains
    Froemke, RC
    Dan, Y
    [J]. NATURE, 2002, 416 (6879) : 433 - 438
  • [10] A neuronal learning rule for sub-millisecond temporal coding
    Gerstner, W
    Kempter, R
    vanHemmen, JL
    Wagner, H
    [J]. NATURE, 1996, 383 (6595) : 76 - 78