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Revealing the dynamic causal interdependence between neural and muscular signals in Parkinsonian tremor
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Wang, S., Chen, Y., Ding, M., Feng, Jianfeng, Stein, J. F., Aziz, T. Z. and Liu, X. (2007) Revealing the dynamic causal interdependence between neural and muscular signals in Parkinsonian tremor. Journal of the Franklin Institute, Vol.344 (No.3-4). pp. 180-195. doi:10.1016/j.jfranklin.2006.06.003 ISSN 0016-0032.
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Official URL: http://dx.doi.org/10.1016/j.jfranklin.2006.06.003
Abstract
Functional correlation between oscillatory neural and muscular signals during tremor can be revealed by coherence estimation. The coherence value in a defined frequency range reveals the interaction strength between the two signals. However, coherence estimation does not provide directional information, preventing the further dissection of the relationship between the two interacting signals. We have therefore investigated causal correlations between the subthalamic nucleus (STN) and muscle in Parkinsonian tremor using adaptive Granger autoregressive (AR) modeling. During resting tremor we analyzed the inter-dependence of local field potentials (LFPs) recorded from the STN and surface electromyograms (EMGs) recorded from the contralateral forearm muscles using an adaptive Granger causality based on AR modeling with a running window to reveal the time-dependent causal influences between the LFP and EMG signals in comparison with coherence estimation. Our results showed that during persistent tremor, there was a directional causality predominantly from EMGs to LFPs corresponding to the significant coherence between LFPs and EMGs at the tremor frequency; and over episodes of transient resting tremor, the inter-dependence between EMGs and LFPs was bi-directional and alternatively varied with time. Further time-frequency analysis showed a significant suppression in the beta band (10-30 Hz) power of the STN LFPs preceded the onset of resting tremor which was presented as the increases in the power at the tremor frequency (3.0-4.5 Hz) in both STN LFPs and surface EMGs. We conclude that the functional correlation between the STN and muscle is dynamic, bi-directional, and dependent on the tremor status. The Granger causality and time-frequency analysis are effective to characterize the dynamic correlation of the transient or intermittent events between simultaneously recorded neural and muscular signals at the same and across different frequencies. (c) 2006 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
Item Type: | Journal Article | ||||
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Subjects: | T Technology > TL Motor vehicles. Aeronautics. Astronautics T Technology > TA Engineering (General). Civil engineering (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering Q Science > QA Mathematics |
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Centre for Scientific Computing Faculty of Science, Engineering and Medicine > Science > Computer Science |
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Journal or Publication Title: | Journal of the Franklin Institute | ||||
Publisher: | Elsevier Science Ltd. | ||||
ISSN: | 0016-0032 | ||||
Official Date: | May 2007 | ||||
Dates: |
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Volume: | Vol.344 | ||||
Number: | No.3-4 | ||||
Number of Pages: | 16 | ||||
Page Range: | pp. 180-195 | ||||
DOI: | 10.1016/j.jfranklin.2006.06.003 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Restricted or Subscription Access | ||||
Title of Event: | 3rd IEE International Seminar on Medical Applications of Signal Processing | ||||
Type of Event: | Other | ||||
Location of Event: | London, England | ||||
Date(s) of Event: | November 03-04, 2005 |
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