Cross Frequency Coupling Characteristic Analysis in Subthalamic Local Field Potentials of Parkinson's Disease_Journal of Biomedical Engineering

Authors：

WANGZongbao ^1,2,3 , HUANGYongzhi ^1,3 , ZHANGXinjing ^1,3 , GENGXinyi ¹ , CHENXiao ¹ ,  WANGShouyan ¹

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;

Corresponding author：

WANGShouyan, Email: swang@sibet.ac.cn

Keywords：

Parkinsonism tremor; local field potential; harmonics; Granger causality; bispectra

DOI：

10.7507/1001-5515.20150156

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Pathological neural activity in subthalamic nucleus (STN) is closely related to the symptoms of Parkinson's disease. Local field potentials (LFPs) recordings from subthalamic nucleus show that power spectral peaks exist at tremor, double tremor and tripble tremor frequencies, respectively. The interaction between these components in the multi-frequency tremor may be related to the generation of tremor. To study the linear and nonlinear relationship between those components, we analyzed STN LFPs from 9 Parkinson's disease patients using time frequency, cross correlation, Granger casuality and bi-spectral analysis. Results of the time-frequency analysis and cross-frequency correlation analysis demonstrated that the power density of those components significantly decreased as the alleviation of tremor and cross-correlation (0.18~0.50) exists during tremor period. Granger causality of the time-variant amplitude showed stronger contribution from tremor to double tremor components, and contributions from both tremor and double tremor components to triple tremor component. Quadratic phase couplings among these three components were detected by the bispectral approaches. The linear and nonlinear relationships existed among the multi-components and certainly confirmed that the dependence cross those frequencies and neurological mechanism of tremor involved complicate neural processes.

Citation： WANGZongbao, HUANGYongzhi, ZHANGXinjing, GENGXinyi, CHENXiao, WANGShouyan. Cross Frequency Coupling Characteristic Analysis in Subthalamic Local Field Potentials of Parkinson's Disease. Journal of Biomedical Engineering, 2015, 32(4): 874-880. doi: 10.7507/1001-5515.20150156 Copy

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1. HAMMOND U,BERGMAN H,BROWN P.Patholgical synchronization in Parkinson's disease networks,models and treatments[J].Trends in Neuroscience,2007,30(7):357-364.
2. WEINBERGER M,MAHANT N,HUTCHISON W D,et al.Beta oscillatory activity in the subthalamic nucleus and its relation to dopaminergic response in Parkinson's disease[J].J Neurophysiol,2006,96(6):3248-3256.
3. LIMOUSIN P,KRACK P,POLLAK P,et al.Electrical stimulation of the subthalamic nucleus in advanced Parkinson's disease[J].N Engl J Med,1998,339(16):1105-1111.
4. LITTLE S,BROWN P.What brain signals are suitable for feedback control of deep brain stimulation in Parkinson's disease[J].Annals of New York Science of Academy,2012,1265(1):9-2E4.
5. WANG S,STEIN J,AZIZ T,et al.Revealing the dynamics causal interdependence between neural and muscular signals in Parkinsion tremor[J].Journal of Franklin Institute,2007,344(3-4):180-195.
6. POLLOK B,GROSS J,DIRKS M,et al.L.the cerebral oscillatory network of voluntary tremor[J].Journal of Physiology-London,2003,554(3):871-878.
7. WANG S Y,LIU X,YIANNI J,et al.Optimising coherence estimation to assess the functional correlation of tremor-related activity between the subthalamic nucleus and the forearm muscles[J].J Neurosci Methods,2004,136(2):197-205.
8. EUSEBIO A, THEVATHASAN W, GAYNOR L D, et al. Deep brain stimulation can suppress pathological synchronisation in parkinsonian patients[J]. J Neurol Neurosurg Psychiatry, 2011, 82(5):569-573.
9. COHEN L. Time frequency analysis[M]. Prentice Hall PTR,1995:93-110.
10. 焦青,钟元,郭永新,等.基于Granger因果性的功能磁共振成像对内侧颞叶癫痫活动的研究[J].中国生物医学工程学报,2009,289(1):7-16.
11. NING T, BRONZINO J. Quadratic phase coupling as a quantitative measure for the developing hippocampal formation[J]. Ann Biomed Eng, 1998, 26(4):688-693.
12. MARCEGLIA S, BIANCHI A M, BASELLI G, et al. Interaction between rhythms in the human basal ganglia:application of bispectral analysis to local field potentials[J]. IEEE Trans Neural Syst Rehabil Eng, 2007, 15(4):483-492.
13. NIKIAS C L, RAGHUVEER M R. Bispectrum estimation:a digital signal processing framework[J]. Proceedings of the IEEE, 1987, 75(7):869-891.
14. SIU K, AHN J, JU K, et al. Statistical approach to quantify the presence of phase coupling using the bispectrum[J]. IEEE Trans Biomed Eng, 2008, 55(5):1512-1520.
15. SCHREIBER T, SCHMITZ A. Surrogate time series[J]. Physica D, 2000, 142(3-4):346-382.

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