• DocumentCode
    2136524
  • Title

    Experimental Study on Neuronal Spike Sorting Methods

  • Author

    Dai, Jianhua ; Liu, Xiaochun ; Yi, Yu ; Zhang, Huaijian ; Wang, Jingjing ; Zhang, Shaomin ; Zheng, Xiaoxiang

  • Volume
    2
  • fYear
    2008
  • fDate
    13-15 Dec. 2008
  • Firstpage
    230
  • Lastpage
    233
  • Abstract
    When recording extracellular neural activity, it is often necessary to distinguish action potentials arising from distinct cells near the electrode tip, a process commonly referred to as spike sorting or action potential sorting. Sorting of neuronal spikes plays a very important role in coding of neural information, which is a prerequisite for studying the brain function. In this paper, five major action potential classification methods including Template Matching, Wavelet Transform, Principal Component Analysis, Back-Propagation (BP) Neural Network, Two-stage Radius Basis Function Network are studied. Under the conditions of different levels of background noise, the performances of these methods are tested. This work may be helpful to choose classification method.
  • Keywords
    backpropagation; principal component analysis; radial basis function networks; wavelet transforms; action potential sorting; back-propagation neural network; extracellular neural activity; neuronal spike sorting methods; principal component analysis; template matching; two-stage radius basis function network; wavelet transform; Background noise; Biological neural networks; Electrodes; Extracellular; Performance evaluation; Principal component analysis; Sorting; Testing; Wavelet analysis; Wavelet transforms; Artificial neural network; Spke sorting; Template matching; Wavelet transform;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Future Generation Communication and Networking, 2008. FGCN '08. Second International Conference on
  • Conference_Location
    Hainan Island
  • Print_ISBN
    978-0-7695-3431-2
  • Type

    conf

  • DOI
    10.1109/FGCN.2008.182
  • Filename
    4734212