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J4  2013, Vol. 47 Issue (5): 901-905    DOI: 10.3785/j.issn.1008-973X.2013.05.024
Decoding of rat’s primary motor cortex by partial least square
ZHU Fan1 , LI Yue1,2, JIANG Kai1, YE Shu-ming1, ZHENG Xiao-xiang2
1. Key Laboratory of Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou 310027,
China|2. Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou 310027, China;
3.Information Engineering College, Zhejiang Agriculture and Forestry University, Hangzhou 311300,China 
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In order to analytizing neurons release pattern of the primary motor cortex of rats accurately and predicting corresponding body movement, the activities of the neurons ensemble spike activities in rats primary motor cortex and the forelimb pressure were recorded simultaneously in the experiment. K-means and principal component analysis were used to classification of neurons, then the partial least squares was used to analyze the relations between the neurons activities of the primary motor cortex of the rat and the forelimb motion parameters, and the results were compared with Wiener filter and Kalman filter. The experimental results indicate that the activities of neurons ensembles began a trend of increase 0.6 second before lever pressing, Which hints the neurons distributed activities of the primary motor cortex in rats can be used to analysis and prediction its forelimb movement and the correlation coefficient between the predicted value and real pressure value is more than 085 using the partial least squares, with a better decoding results than those using the Wiener filtering and Kalman filtering.

Published: 01 May 2013
CLC:  TP 391  
Cite this article:

ZHU Fan , LI Yue, JIANG Kai, YE Shu-ming, ZHENG Xiao-xiang. Decoding of rat’s primary motor cortex by partial least square. J4, 2013, 47(5): 901-905.

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为了准确解析大鼠初级运动皮层神经元发放模式并预测相应的肢体动作,实验同时记录大鼠初级运动皮层神经元峰电位发放和大鼠前肢压力,利用K均值法和主成分分析法对神经元进行分类,采用偏最小二乘分析大鼠初级运动皮层神经元活动与前肢运动参数之间的关系,并对该解码结果与维纳滤波和卡尔曼滤波算法的解码结果进行比较.实验结果表明:神经元的发放活动在压杆前0.6 s开始有增加的趋势,提示大鼠的初级运动皮层神经元分布式活动可用于大鼠前肢运动的解析和预测,且偏最小二乘解码得到的预测值与真实压杆值的相关系数在085以上,均高于维纳滤波和卡尔曼滤波的解码结果.

[1] WOLPAW J R, BIRBAUMER N, MCFARLAND D J, et al. Brain–computer interfaces for communication and control [J]. Clinical Neurophysiology, 2002,113(6): 767-791.
[2] NICOLELIS M A  L, GHAZANFAR A, FAGGIN B M, et al. Reconstructing the engram: simultanrous, multisite, many single neuron recordings[J]. Neuron, 1997, 18(4):529-537.
[3] HATSOPOULOS N G, XU Q Q, AMIT Y. Encoding of movement frag- ments in the motor cortex [J]. Journal of Neuroscience, 2007,27(19):5105-5114.
[4] 代建华, 章怀坚, 张韶岷, 等. 大鼠运动皮层神经元集群锋电位时空模式解析[J]. 中国科学: C 辑,2009,39(8): 736-745.
DAI Jian-hua, ZHANG Huai-jian, ZHANG Shao-min, et al. Neurons cluster spike potential of rat motor cortex in time and space analytic model [J]. Science in China series C:Life science, 2009,39(8): 736-745.
[5] CHAPIN J K, MOXON K A, MARKOWITZ R S, et al. Real-time control of a robot arm using simul- taneously recorded neurons in the motor cortex [J]. Nature Neuroscience, 1999, 2(7): 664-670.
[6] HARRIS K D. , HENZE D A. , CSICSVARI J, et al. Accuracy of tetrode spike separation as determined by simultaneous intracellular and extracellular measure- ments [J].Journal of Neurophysiology, 2000,84(1):401-414.
[7] MATTHEW S  M, WARREN H M, MIGUEL A L N. Interval timing and encoding of signal duration by ensembles of cortical and striatal neurons [J]. Behavioral Neuroscience, 2003, 117(4): 760-772.
[8] TAYLOR D M, TILLERY S I, SCH- WARTZ A B. Direct cortical control of 3D neuroprosthetic devices [J].Science, 2002,296(5574) 1829-1832.
[9] WU WEI, BLACK MICHAEL J, MEMBER, et al. Modeling and decoding motor cortical activity using a switching kalman filter [J]. IEEE Transactions on Biomedical Engineering,2004, 51(6): 933-942.
[10] ZHANG H J, DAI, J H, ZHANG S M, et al. Neuronal ensemble decoding of rats motor cortex by Kalman filter and optimal linear estimation [C]∥ International Congress on Image and Signal Processing. Tianjin: IEEE,2009:15.
[11] CHAO Z C, NAGASAKA Y, FUJI N. Long-term asynchronous decoding of arm motion using electrocorticographic signals in monkeys [J]. Frontiers in Neuroengineering, 2010, 3(3): 1-10.
[12] FUAYAMA O, Morishita Y, et al. Estimation of walking speed for controlling vehicle using neural signals from primary motor cortex of rat [C] ∥ The 2nd International IEEE EMBS Conference on Neural Engineering. Arlington: Institute of Electrical and Electronics Engineers Computer Society,2005:442-445.
[13] 朱 凡,蒋 凯,吕荣坤,等. 小量程大行程压杆检测系统及在脑-机接口的应用[J]. 浙江大学学报:工学版,2011,45(9):1693-1696.
ZHU fan, JIANG Kai, LV Rong-kun,et al. Small-range big-trip pressure lever detection system and its application in brain-computer interface [J]. Journal of Zhejiang University: Engineering Science, 2011,45(9):1693-1696.
[14] 张韶岷,陈卫东,孙超,等. 动物脑电-行为同步记录及分析系统[J].浙江大学学报:工学版,2009,43(11):2028-2033.
ZHANG Shao-min, CHEN Wei-dong,SUN Chao,et al. Synchronous recording and analyzing system for animals neuronal activity and behavior[J]. Journal of Zhejiang University: Engineering Science, 2009,43(11):2028-2033.
[15] WOLD S, SJOSTROM M, ERIKSSON L. PLS-regression: a basic tool of chemometrics [J]. Chemometrics and Intelligent Laboratory Systems, 2001, 58(2): 109-130.
[16] 蒋红卫, 夏结来. 偏最小二乘回归及其应用[J]. 第四军医大学学报, 2003, 24(3): 280-283.
JIANG Hong-wei, XIA Jie-lai. Partial least square and its application [J]. Journals of the Fourth Military Medical University, 2003, 24(3): 280-283.

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