Abstract Local field potential (LFP) reflects the response of the neuron clusters in the local area of cerebral cortex under visual stimulation. Extracting response characteristics of LFP accurately is of great importance to the analysis of visual information processing mechanism. Here, HilbertHuang transform which has adaptive characteristics was adopted according to the nonstationary of LFP, and the tuning characteristics of the stimulate raster spatial frequency response in V1 area of the rat based on the intrinsic mode components of LFP was studied, and Multiunit activity(MUA) and Gammaband extracted with wavelet decomposition were compared. Results showed that the second intrinsic mode function of LFP was the strongest on the tuning characteristics of stimulate raster spatial frequency, and the average of tuning index (0.795 1) was greater than MUA (0.631 3) and wavelet decomposition (0.664 6), and its consistency rate with MUA was 68.75%. Therefore, the proposed method in feature extraction of response band has more advantages.
WAN Hong*ZHANG Xiao Na LIU Xin Yu LI Xiao Yan. Research about the Tuning Characteristics of Response Based on the Intrinsic Mode Functions of Local Field Potential[J]. journal1, 2013, 32(3): 292-298.
［1］Mazer JA, Vinje WE, McDermott J, et al. Spatial frequency and orientation tuning dynamics in area V1 ［J］. Neurobiology, 2002, 99(3): 1645-1650.
［2］Belitski A, Panzeri S, Magri C, et al. Sensory information in local field potentials and spikes from visual and auditory cortices: time scales and frequency bands ［J］. Journal Computational Neuroscience, 2010, 29(3):533-545.
［3］Gawne TJ. The local and nonlocal components of the local field potential in awake primate visual cortex ［J］. Journal of Computational Neuroscience, 2010, 29(3):615-623.
［4］Ince RAA, Mazzoni A, Bartels A, et al. A novel test to determine the significance of neural selectivity to single and multiple potentially correlated stimulus features ［J］. Journal of Neuroscience Methods, 2012, 210(1): 49-65.
［5］Belitski A, Gretton A, Magri C. Lowfrequency local field potentials and spikes in primary visual cortex convey independent visual information ［J］. The Journal of Neuroscience, 2008, 28(22):5696 -5709.
［6］Henrie JA, Shapley R. LFP power spectra in V1 cortex: the graded effect of stimulus contrast ［J］. Journal of Neurophysiology, 2005, 94(1): 479-490.
［7］Kayser C, Konig P. Stimulus locking and feature selectivity prevail in complementary frequency ranges of V1 local field potentials ［J］. Neuroscience, 2004, 19(2): 485-489.
［8］Philipp B, Georgios A. Comparing the feature selectivity of the gammaband of the local field potential and the underlying spiking activity in primate visual cortex ［J］. Frontiers in Systems Neuroscience, 2008, 2(2): 1-11.
［9］Magri C, Mazzoni A, Logothetis NK, et al. Optimal band separation of extracellular field potentials ［J］. Tournal of Neuroscience Methods, 2012, 210(1), 66-78.
［10］Huang NE, Shen Z, Long SR, et al. The empirical mode decomposition and the hilbert spectrum for nonlinear and nonstation time series analysis ［J］. Proceedings of the Royal Society of London,1998, 454: 903-995.
［11］Liang HL, Steven LB, Desimone R, et al. Empirical mode decomposition:a method foranalyzing neural data ［J］. Neurocomputing, 2005, 65-66: 801-807.
［12］Sweeney CM, Nasuto SJ. A novel approach to the detection of synchronisation in EEG based on empirical mode decomposition ［J］.Journal of Computational Neuroscience, 2007, 23(1):79-111.
［13］袁玲,杨帮华,马世伟.基于HHT和SVM的运动想象脑电识别［J］. 仪器仪表学报, 2010, 31(3):649-654.
［14］Kajikawa Y, Schroeder CE. How local is the local field potential? ［J］. Neuron, 2011, 72(5): 847-858.
［15］尚志刚, 冯平艳, 刘新玉等. 局部场电位γ频带能量对朝向调谐特性研究［J］. 郑州大学学报(工学版), 2012, 33(6): 28-32.
［16］Molotchnikoff S, Gillet PC. Spatial frequency characteristics of nearby neurons in cat′s visual cortex ［J］. Neuroscience Letters. 2007, 418(3):242-247.
［17］Cristopher M, Tryker MP. Highly selective receptive fields in mouse visual cortex ［J］. The Journal of Neuroscience, 2008, 30(28):7520-7536.
