Please wait a minute...
浙江大学学报(工学版)
J4  2012, Vol. 46 Issue (2): 351-358    DOI: 10.3785/j.issn.1008-973X.2012.02.027
    
Selection of filtering frequencies for neuronal spike signals
FENG Zhou-yan, WANG Jing, WANG Yang, ZHENG Xiao-jing
College of Biomedical Engineering and Instrumentation Science, Key Laboratory of Biomedical Engineering of
Ministry of Education, Zhejiang University, Hangzhou 310027, China
Download:   PDF(0KB) HTML
Export: BibTeX | EndNote (RIS)      

Abstract  

In order to determine the proper filtering frequency ranges for accurately recording and analyzing the extracellular neuron unit action potential (i.e., spike), changes in spike waveform distortion, signal-to-noise ratio (SNR), and accuracy of spike classification under different lower and higher cutoff frequencies were investigated. The spike signals were recorded from rat hippocampal regions by microelectrode arrays. The results show that with lower cut-off frequency≤100 Hz and higher cutoff frequency≥5 kHz, the spike waveform distortions caused by filtering are small. The optimized higher cut-off frequency ranges for spike detection and spike classification are both at 3~5 kHz. However, the optimized lower cutoff frequency for spike detection is 500 ~ 600 Hz, whereas for spike classification the frequency is about 200 Hz. The reason is that the accuracy of spike classifications depends on both the SNR and the waveform distortion.

Published: 20 March 2012
CLC:  TP 274  
  R 318  
Service
E-mail this article
Add to my bookshelf
Add to citation manager
E-mail Alert
RSS
Articles by authors
Cite this article:

FENG Zhou-yan, WANG Jing, WANG Yang, ZHENG Xiao-jing. Selection of filtering frequencies for neuronal spike signals. J4, 2012, 46(2): 351-358.

URL:

http://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2012.02.027     OR     http://www.zjujournals.com/eng/Y2012/V46/I2/351


神经元锋电位信号滤波频率的选择

为了在记录和分析细胞外神经元单元动作电位（即锋电位）时能够正确选择滤波频率范围，分析了不同下限和上限截止频率时锋电位的波形失真、信噪比以及分类正确率的变化过程. 锋电位信号是利用微电极阵列采集的大鼠海马区神经元信号. 结果表明，下限截止频率小于100 Hz且上限截止频率大于5 000 Hz时，滤波造成的锋电位波形失真较小. 对于锋电位的检出和分类这2种数据处理，它们的上限截止频率最佳范围一致，为3～5 kHz. 但是，对于下限截止频率，锋电位检出的最佳频率为500～600 Hz，而锋电位分类的最佳频率却在200 Hz左右，这是由于锋电位分类的正确率与信噪比和波形的失真都相关.

［1］ HOCHBERG L R, SERRUYA M D, FRIEHS G M, et al. Neuronal ensemble control of prosthetic devices by a human with tetraplegia ［J］. Nature, 2006, 442(7099): 164-171.
［2］ KLAUSBERGER T, MAGILL PJ, MARTON LF, et al. Brainstate and celltypespecific firing of hippocampal interneurons in vivo ［J］. Nature, 2003, 421(6925): 844-848.
［3］ RASCH MJ, GRETTON A, MURAYAMA Y, et al. Inferring spike trains from local field potentials ［J］. Journal of Neurophysiology, 2008, 99 (3): 1461-1476.
［4］ TAKEKAWA T, ISOMURA Y, FUKAI T. Accurate spike sorting for multiunit recordings ［J］. European Journal of Neuroscience, 2010, 31(2): 263-272.
［5］ KANEKO H, SUZUKI SS, OKADA J, et al. Multineuronal spike classification based on multisite electrode recording, wholewaveform analysis, and hierarchical clustering ［J］. IEEE Transactions on Biomedical Engineering, 1999, 46(3): 280-90.
［6］ QUIROGA R. QUIAN. What is the real shape of extracellular spikes ［J］. Journal of Neuroscience Methods, 2009, 177(1): 194-198.
［7］ HENZE DA, BORHEGYI Z, CSICSVARI J, et al. Intracellular features predicted by extracellular recordings in the hippocampus in vivo ［J］. Journal of Neurophysiology, 2000, 84(1): 390-400.
［8］ LEE CW, DANG H, NENADIC Z. An Efficient Algorithm for Current Source Localization with Tetrodes ［C］∥ Proceedings of the 29th Annual International Conference of the IEEE EMBS Cité Internationale. Lyon, France：［s.n.］, 2007: 1282-1285.
［9］ LEWICKI MS. A review of methods for spike sorting: the detection and classification of neural action potentials ［J］. Network, 1998, 9(4): 53-78.
［10］ 王静,封洲燕.多通道神经元锋电位检测和分类的新方法［J］.生物化学与生物物理进展,2009, 36 (5): 641-647.
WANG Jing, FENG Zhouyan. A novel method for multichannel neuronal spike detection and classification ［J］. Progress in Biochemistry and Biophysics, 2009, 36 (5): 641-647.
［11］ JOSHUA M, ELIAS S, LEVINE O, et al. Quantifying the isolation quality of extracellularly recorded action potentials ［J］. Journal of Neuroscience Methods, 2007, 163(2): 267-82.
［12］ BARTHO P, HIRASE H, MONCONDUIT L, et al. Characterization of neocortical principal cells and interneurons by network interactions and extracellular features ［J］. Journal of Neurophysiology, 2004, 92(1): 600-608.
［13］ GOLD C, HENZE DA, KOCH C. Using extracellular action potential recordings to constrain compartmental models ［J］. Journal of Computational Neuroscience, 2007, 23(1): 39-58.
［14］ WILTSCHKO A B, GAGE G J, BERKE J D. Wavelet filtering before spike detection preserves waveform shape and enhances singleunit discrimination ［J］. Journal of Neuroscience Methods, 2008, 173(1): 34-40.
［15］ BRETSCHNEIDER F, de WEILLE J R. Introduction to electrophysiological methods and instrumentation ［M］. London: Academic Press. 2006: 47-55.
［16］ MUSIAL P G, BAKER S N, GERSTEIN G L, et al. Signaltonoise ratio improvement in multiple electrode recording ［J］. Journal of Neuroscience Methods, 2002, 115(1): 29-43.
［17］ CHANDRA R, OPTICAN L M. Detection, classification, and superposition resolution of action potentials in multiunit singlechannel recordings by an online realtime neural network ［J］. IEEE Transactions on Biomedical Engineering, 1997, 44 (5): 403-412.
［18］ THAKUR P H, LU H, HSIAO S S, et al. Automated optimal detection and classification of neural action potentials in extracellular recordings ［J］. Journal of Neuroscience Methods, 2007, 162 (1/2): 364-376.
No related articles found!