中国神经再生研究(英文版)

中国神经再生研究(英文版) ›› 2013, Vol. 8 ›› Issue (16): 1500-1513.doi: 10.3969/j.issn.1673-5374.2013.16.007

• 原著:脑损伤修复保护与再生 • 上一篇    下一篇

脑损伤后JNK3基因参与神经细胞凋亡及神经功能恢复

  

  • 收稿日期:2013-03-02 修回日期:2013-05-20 出版日期:2013-06-05 发布日期:2013-06-05

Artifact suppression and analysis of brain activities with electroencephalography signals

Md. Rashed-Al-Mahfuz1, Md. Rabiul Islam1, Keikichi Hirose2, Md. Khademul Islam Molla2, 3   

  1. 1 Department of Computer Science and Engineering, Pabna University of Science and Technology, Pabna, Bangladesh
    2 Department of Information and Communication Engineering, The University of Tokyo, Tokyo, Japan
    3 Department of Computer Science and Engineering, Rajshahi University, Rajshahi, Bangladesh
  • Received:2013-03-02 Revised:2013-05-20 Online:2013-06-05 Published:2013-06-05
  • Contact: Md. Khademul Islam Molla, Ph.D., Professor, Department of Computer Science and Engineering, Rajshahi University, Rajshahi, Bangladesh, molla@ gavo.t.u-tokyo.ac.jp.

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摘要：

越来越多的证据表明,脑损伤后c-Jun氨基末端激酶(c-Jun amino-terminal kinase，JNK)通路的激活参与神经细胞凋亡及神经功能恢复。然而，通过激活JNK家族中哪些基因在发挥作用呢？目前并不十分明确。因此，实验采取原位末端标记法、反转录-聚合酶链反应、神经功能缺损评分方法，探讨脑损伤大鼠JNK1，JNK2，JNK3基因的表达变化，以及与神经元凋亡和神经功能改变的关系。发现大鼠脑组织JNK3表达在脑损伤后1h、6h、1d和7d下降，JNK1和JNK2的表达无明显变化，脑损伤皮质周边区凋亡神经细胞逐渐减少。大鼠神经功能缺损评分在脑损伤后1，3，5，7，14，28 d逐渐降低。说明JNK3在脑损伤后早期表达下调，可能与神经细胞凋亡有关，JNK3的下调可能促进脑损伤后神经功能的恢复。

关键词: 神经再生, 脑损伤, JNK1, JNK2, JNK3, 原位末端标记, 细胞凋亡, 神经功能恢复

Abstract:

Brain-computer interface is a communication system that connects the brain with computer (or other devices) but is not dependent on the normal output of the brain (i.e., peripheral nerve and muscle). Electro-oculogram is a dominant artifact which has a significant negative influence on further analysis of real electroencephalography data. This paper presented a data adaptive technique for artifact suppression and brain wave extraction from electroencephalography signals to detect regional brain activities. Empirical mode decomposition based adaptive thresholding approach was employed here to suppress the electro-oculogram artifact. Fractional Gaussian noise was used to determine the threshold level derived from the analysis data without any training. The purified electroencephalography signal was composed of the brain waves also called rhythmic components which represent the brain activities. The rhythmic components were extracted from each electroencephalography channel using adaptive wiener filter with the original scale. The regional brain activities were mapped on the basis of the spatial distribution of rhythmic components, and the results showed that different regions of the brain are activated in response to different stimuli. This research analyzed the activities of a single rhythmic component, alpha with respect to different motor imaginations. The experimental results showed that the proposed method is very efficient in artifact suppression and identifying individual motor imagery based on the activities of alpha component.

Key words: neural regeneration, brain activity, brain waves, data adaptive filtering, electroencephalography, electro-oculogram artifact, topographic mapping, Wiener filtering, neuroregeneration