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神经系统以时空编码形式刻画外部刺激信息, 针刺作为对穴位的机械作用可以等效为对神经系统的一种外部刺激. 为了揭示神经系统如何表达和传递针刺作用, 本文设计了不同频率的针刺动物实验, 即在针刺大鼠足三里穴位时获取脊髓背根神经节电信号. 首先, 经过数据预处理获得单神经元动作电位序列并转化为点过程序列. 其次, 应用广义线性模型(GLM)编码针刺作用, 产生模拟的神经放电序列. 另外, 在模型基础上应用贝叶斯解码, 根据神经放电序列重构针刺随时间变化的位移波形. 最后, 基于时间重标度理论应用分位数分位数(Q-Q)图方法检验编码模型与点过程数据的一致性. 结果表明, GLM能够模拟针刺神经编码, 并正确解码针刺信息. 本文为针刺研究提供了新的视角, 对于构建神经系统与机器接口以改善针刺的临床研究具有潜在意义.Neural system can characterize the information evoked in external stimulations by spatiotemporal encoding. Acupunctureas, as a mechanical actionis equivalent to an external stimulus to the neural system. In order to decipher how neural systems represent and transmit acupuncture information, experiments are designed such that different frequencies of manual acupuncture (MA) manipulations can be given to ‘Zusanli’ point of an experimental rat, and the induced electrical signals in spinal dorsal root ganglion are detected and recorded. First, the spike trains are obtained by data preprocessing and transformed into point process trains. Then a generalized linear model is introduced to encode the acupuncture information and produce the simulated neural spike train. In addition, a Bayesian decoding algorithm is used to reconstruct the displacement oscillograms of the acupuncture needle from the neural point process spike train. Finally, the quantile-quantile (Q-Q) plot based on the time-rescaling theorem is used to evaluate the agreement between the encoding model and the point process data. Results prove to be valid based on statistical analysis. These studies have offered new insights into neural processing underlying acupuncture and have implementations for constructing the interface between neural systems and machines and improving the clinical study.
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Keywords:
- acupuncture /
- point process /
- generalized linear model /
- neural decoding
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[1] Andersson S, Lundeberg T 1995 Med. Hypotheses 45 271
[2] VanderPloeg K, Yi X 2009 J. Acupunct. Meridian Stud. 2 26
[3] Leake R, Broderick J E 1999 Integr. Med. 1 107
[4] Foster J M, Sweeney B P 1987 Br. J. Hosp. Med. 38 308
[5] Cho Z H, Chung S C, Jones J P, Park J B, Park H J, Lee H J, Wong E K, Min B I 1998 Proc. Natl. Acad. Sci. USA 95 2670
[6] Zhang Y, Qin W, Liu P, Tian J, Liang J M, Karen V D, Liu Y J 2009 Neurosci. Lett. 449 6
[7] Zhang W T, Jin Z, Cui G H 2003 Brain Res. 982 168
[8] Wang T T, Yuan Y, Kang Y, Yuan W L, Zhang H T, Wu L Y, Feng Z T 2005 Neurosci. Lett. 382 236
[9] Han J S 2003 Trends Neurosci. 26 17
[10] Backer M, Hammes M G, Valet M, Deppe M, Conrad B, Tolle T R, Dobos G 2002 Neurosci. Lett. 333 203
[11] Cui Y M, Qi L J 1998 International Journal of Clinical Acupuncture 9 317
[12] Cai W Y 1992 American Journal of Chinese Medicine 20 331
[13] Han C X, Wang J, Che Y Q, Deng B, Guo Y, Guo Y M, Liu Y Y 2010 Acta Phys. Sin. 59 5880 (in Chinese) [韩春晓, 王江, 车艳秋, 邓斌, 郭义, 郭永明, 刘阳阳 2010 59 5880]
[14] Takeshige C, Oka K, Mizuno T, Hisamitsu T, Luo C P, Kobori M, Mera H, Fang T Q 1993 Brain Res. Bull. 30 53
[15] Squire L, Berg D, Bloem F, Lac S D, Ghosh A, Spitzer N 2009 Sensory system and motor system (Beijing: Science Press)
[16] Wang J, Sun L, Fei X, Zhu B 2007 Chaos Solitons Fract. 33 901
[17] Men C, Wang J, Qin Y M, Deng B, Wei X L 2011 Computer Methods and Programs in Biomedicine 104 498
[18] Men C, Wang J, Deng B, Wei X L, Che Y Q, Han C X 2012 Neurocomputing 79 12
[19] Men C, Wang J, Qin Y M, Tsang K M, Deng B 2011 Applied Mathematical Modelling 36 4742
[20] Luo X L, Wang J, Han C X, Deng B, Wei X L, Bian H R 2012 Chin. Phys. B 21 028701
[21] Bian H R, Wang J, Han C X, Deng B, Wei X L, Che Y Q 2011 Acta Phys. Sin. 60 118701 (in Chinese) [边洪瑞, 王江, 韩春晓, 邓斌, 魏熙乐, 车艳秋 2011 60 118701]
[22] Yi G S, Wang J, Deng B, Wei X L, Han C X 2012 Chin. Phys. B 028703
[23] Yang Z Q, Lu Q S 2006 Chin. Phys. 15 578
[24] Lu Q S, Wang H X, Wang Q Y 2005 Chin. Phys. 14 2189
[25] Duan Y B, Hu S J, Xie Y, Xu J X, Kang Y M 2004 Chin. Phys. 13 1396
[26] He G G, Zhu P, Chen H P, Xie X P 2010 Acta Phys. Sin. 59 5307 (in Chinese) [何国光, 朱萍, 陈宏平, 谢小平 2010 59 5307]
[27] Zhang H, Fang L P, Tong Q Y 2007 Acta Phys. Sin. 56 7339 [张宏, 方路平, 童勤业 2007 56 7339]
[28] Yu W Q, Xu D, Liu F, Wang W, Li J 2009 Chin. Phys. B 18 5560
[29] Zhan Y, Zhang S H, Zhao T J, An H L, Zhang Z D, Han Y R, Liu H, Zhang Y H 2008 Chin. Phys. B 17 2297
[30] Koyama S, Eden U T, Brown E N, Kass R E 2010 Annals of the Institute of Statistical Mathematics 62 37
[31] Rieke F, Warland D, de Ruyter van Steveninck R, Bialek W 1997 Spikes: Exploring the neural code (Cambridge: The MIT Press)
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[33] Liu T Y, Yang H Y, Ku A L, Gao M 2010 Acupuncture Research 35 61 (in Chinese) [刘堂义, 杨华元, 蒯乐, 高明 2010 针刺研究 35 61]
[34] Quiroga R Q, Nadasdy Z, Ben-Shaul Y 2004 Neural Comput. 16 1661
[35] Truccolo W, Eden U T, Fellows M R, Donoghue J P, Brown E N 2005 Journal of Neurophysiology 93 1074
[36] Smith A C, Brown E N 2003 Neural Computation 15 965
[37] Keat J, Reinagel P, Reid R C, Meister M 2001 Neuron 30 803
[38] Pillow J, Shlens J, Paninski L, Sher A, Litke A, Chichilnisky E, Simoncelli E 2008 Nature 454 995
[39] Brown E N, Barbieri R, Ventura V, Kass R E, Frank L M 2002 Neural Computation 14 325
[40] Akaike H 1994 Proceedings of the first US/Japan conference on the frontiers of statistical modeling: an informational approach Dordrecht, Kluwer, January 31, 1994 p33
[41] Brown E N, Frank L M, Tang D, Quirk M C, Wilson M A 1998 J. Neurosci. 18 7411
[42] Tanner M A 1996 Tools for Statistical Inference: Methods for the Exploration of Posterior Distributions and Likelihood Functions (New York: Springer-Verlag)
[43] Kitagawa G, Gersh W 1996 Smoothness priors analysis of time series (New York: Springer)
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