• 1. Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China;
  • 2. Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China;
  • 3. University of Chinese Academy of Sciences, Beijing 100049, China;
WANGShouyan, Email: swang@sibet.ac.cn
Export PDF Favorites Scan Get Citation

The dysfunction of subthalamic nucleus is the main cause of Parkinson’s disease. Local field potentials in human subthalamic nucleus contain rich physiological information. The present study aimed to quantify the oscillatory and dynamic characteristics of local field potentials of subthalamic nucleus, and their modulation by the medication therapy for Parkinson’s disease. The subthalamic nucleus local field potentials were recorded from patients with Parkinson’s disease at the states of on and off medication. The oscillatory features were characterised with the power spectral analysis. Furthermore, the dynamic features were characterised with time-frequency analysis and the coefficient of variation measure of the time-variant power at each frequency. There was a dominant peak at low beta band with medication off. The medication significantly suppressed the low beta component and increased the theta component. The amplitude fluctuation of neural oscillations was measured by the coefficient of variation. The coefficient of variation in 4-7 Hz and 60-66 Hz was increased by medication. These effects proved that medication had significant modulation to subthalamic nucleus neural oscillatory synchronization and dynamic features. The subthalamic nucleus neural activities tend towards stable state under medication. The findings would provide quantitative biomarkers for studying the mechanisms of Parkinson’s disease and clinical treatments of medication or deep brain stimulation.

Citation: WANGYanan, GENGXinyi, HUANGYongzhi, WANGShouyan. Influence of Medication on the Oscillatory and Dynamic Characteristics of Subthalamic Local Field Potentials in Patients with Parkinson’s Disease. Journal of Biomedical Engineering, 2016, 33(1): 49-55. doi: 10.7507/1001-5515.20160010 Copy

  • Previous Article

    Classification and Correlative Technology Development of Wearable Devices
  • Next Article

    Brain Efficient Connectivity Analysis of Attention Based on the Granger Causality Method