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采用局部场电位小波包熵分析空间频率特性 被引量:2

Analyzing spatial frequency characteristic by using wavelet packet entropy of local field potential
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摘要 空间频率是视觉刺激的基本特征之一,为了研究视觉皮层神经元对刺激空间频率的响应特性,提出了一种基于局部场电位小波包熵的分析方法。通过以Long Evans大鼠为模式动物进行电生理实验,分别采用神经元放电统计分析和局部场电位小波包熵分析,发现不同空间频率刺激下,小波包熵调谐曲线与全局神经元放电调谐曲线具有一致性,证明了局部场电位小波包熵可用于表征视皮层神经元对刺激空间频率的选择性。结果还表明采用基于局部场电位小波包熵分析时,各通道结果具有更好的一致性。 Spatial frequency is one of the basic properties in visual stimuli, to study the response of neurons in visual cortex to the spatial frequency of stimuli, a method based on wavelet packet entropy of local field potential is proposed. By doing experi-ments on Long Evans rats, both statistical analysis based on spike per second and analysis based on wavelet packet entropy of LFP are used, the result is that under stimulus of different spatial frequencies, tuning curves of wavelet packet entropy is consis-tent with tuning curves of spikes in whole, which indicates that the wavelet packet entropy of LFP can be used to measure the spatial frequency selectivity of neurons in visual cortex. The results also suggest better consistency when using wavelet packet entropy of LFP.
作者 师黎 朱俊强
出处 《计算机工程与应用》 CSCD 2013年第17期217-220,257,共5页 Computer Engineering and Applications
基金 国家自然科学基金(No.60971110)
关键词 局部场电位 空间频率 小波包熵 调谐特性 local field potential spatial frequency wavelet packet entropy tuning curve
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  • 1Hamois C,Bodis-Wollner I,Onofrj M.The effect of contrast and spatial frequency on the visual evoked potential of the hooded rat[J].Experimental Brain Research,1984,57:l-8.
  • 2Friend S M,Baker Jr C L.Spatio-temporal frequency separa- bility in area 18 neurons of the cat[J].Vision Res, 1993,33: 1765-1771.
  • 3雷静江,李朝义.猫视皮层神经元时间特性与空间特性的关系[J].科学通报,1996,41(10):931-934. 被引量:2
  • 4Molotchnikoff S, Gillet P C.Spatial frequency characteristics of nearby neurons in cat's visual cortex[J].Neuroscience Letters, 2007,418 : 242-247.
  • 5Issa N P,Trepel C, Stryker M P.Spatial frequency maps in cat visual cortex[J].The Journal of Neuroscience, 2002, 20 (22) :8504-8514. 4 : 497-503.
  • 6Foster K H,Gaska J P.Spatial and temporal frequency selec- tivity of neurons in visual cortex areas V1 and V2 of the macaque monkey[J].Physiol, 1985,365:331-363.
  • 7Sirovich L, Uglesich R.The organization of orientation and spatial frequency in primary visual cortex[J].PNAS, 2004, 101 : 16941-16946.
  • 8Etzold A, Eurich C W.Tuning properties of noisy cells with application to orientation selectivity in rat visual cortex[J]. Neurocomputing, 2003,52/5.
  • 9Niell C M, Stryker M P.Highly selective receptive fields in mouse visual cortex[J].The Journal of Neuroscience, 2008,30(28) : 7520-7536.
  • 10Zhu Wei, Xing Dajun.Correlation between spatial frequency and orientation selectivity in V1 cortex: implications of a network model[J].Vision Research,2010,50:2261-2273.

二级参考文献53

  • 1沈花,李交杰,胡萌,唐孝威,李光.基于单导EEG的高空缺氧所致疲劳的实时检测技术研究[J].传感技术学报,2006,19(4):1042-1044. 被引量:2
  • 2[1]Rezek IA, Roberts SJ. Stochastic Complexity Measures for Physiological Signal Analysis[J]. IEEE Trans Biomed Engin, 1998,45(9): 1186-1191.
  • 3[2]Lee YJ, Zhu YS, Xu YH, et al. Detection of non-linearity in the EEG of schizophrenic patients[J]. Clin Neurophysiol, 2001,112(7): 1288-1294.
  • 4[3]Krystal AD, Zaidman C, Greenside HS, et al. The largest Lyapunov exponent of the EEG during ECT seizures as a measure of ECT seizure adequacy[J]. Electroencepholography and Clinical Neurophysiology, 1997,103(6):599-606.
  • 5[4]Shaw FZ, Chen RF, Tsao HW, et al. Algorithmic complexity as an index of cortical function in awake and pentobarbital-anesthetized rats[J]. J Neurosci Meth, 1999,93(2): 101-110.
  • 6[5]Pincus S. Approximate entropy (ApEn) as a complexity measure[J]. Chaos, 1995,5(1):110.
  • 7[6]Pincus SM, Goldberger AL. Physiological time-series analysis: what does regularity quantify?[J] American Journal of Physiology, 1994,266(4 Pt 2):H1643.
  • 8[7]Inouye T, Shinosaki K, Sakamoto H, et al. Quantification of EEG irregularity by use of the entropy of the power spectrum[J]. Electroencephalography and Clinical Neurophysiology, 1991,79(3):204-210.
  • 9[8]Muthuswamy J, Thakor NV. Spectral analysis methods for neurological signals[J]. J Neurosci Meth, 1998,83(1):1-14.
  • 10[9]Unser M, Aldroubi A. A review of wavelet in biomedical applications[J]. Proc IEEE, 1996,84:626-638.

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