Chinese Science Bulletin

, Volume 57, Issue 16, pp 2036–2045 | Cite as

Development of an invasive brain-machine interface with a monkey model

  • QiaoSheng Zhang
  • ShaoMin Zhang
  • YaoYao Hao
  • HuaiJian Zhang
  • JunMing Zhu
  • Ting Zhao
  • JianMin Zhang
  • YiWen Wang
  • XiaoXiang Zheng
  • WeiDong ChenEmail author
Open Access
Article Cybernetics


Brain-machine interfaces (BMIs) translate neural activities of the brain into specific instructions that can be carried out by external devices. BMIs have the potential to restore or augment motor functions of paralyzed patients suffering from spinal cord damage. The neural activities have been used to predict the 2D or 3D movement trajectory of monkey’s arm or hand in many studies. However, there are few studies on decoding the wrist movement from neural activities in center-out paradigm. The present study developed an invasive BMI system with a monkey model using a 10×10-microelectrode array in the primary motor cortex. The monkey was trained to perform a two-dimensional forelimb wrist movement paradigm where neural activities and movement signals were simultaneous recorded. Results showed that neuronal firing rates highly correlated with forelimb wrist movement; > 70% (105/149) neurons exhibited specific firing changes during movement and > 36% (54/149) neurons were used to discriminate directional pairs. The neuronal firing rates were also used to predict the wrist moving directions and continuous trajectories of the forelimb wrist. The four directions could be classified with 96% accuracy using a support vector machine, and the correlation coefficients of trajectory prediction using a general regression neural network were above 0.8 for both horizontal and vertical directions. Results showed that this BMI system could predict monkey wrist movements in high accuracy through the use of neuronal firing information.


brain-machine interface primary motor cortex center-out paradigm neural decoding support vector machine general regression neural network 


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Copyright information

© The Author(s) 2012

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 2.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Authors and Affiliations

  • QiaoSheng Zhang
    • 1
    • 3
    • 4
  • ShaoMin Zhang
    • 1
    • 3
    • 4
  • YaoYao Hao
    • 1
    • 3
    • 4
  • HuaiJian Zhang
    • 1
    • 3
    • 4
  • JunMing Zhu
    • 1
    • 5
  • Ting Zhao
    • 1
  • JianMin Zhang
    • 5
  • YiWen Wang
    • 1
  • XiaoXiang Zheng
    • 1
    • 3
    • 4
  • WeiDong Chen
    • 1
    • 2
    Email author
  1. 1.Qiushi Academy for Advanced StudiesZhejiang UniversityHangzhouChina
  2. 2.College of Computer Science and TechnologyZhejiang UniversityHangzhouChina
  3. 3.Department of Biomedical EngineeringZhejiang UniversityHangzhouChina
  4. 4.Key Laboratory of Biomedical Engineering of Ministry of EducationZhejiang UniversityHangzhouChina
  5. 5.Department of Neurosurgery, Second Affiliated Hospital School of MedicineZhejiang UniversityHangzhouChina

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