Detecting time-dependent coherence between non-stationary electrophysiological signals - A combined statistical and time-frequency approach
Zhan, Yang, Halliday, David, Jiang, Ping, Liu, Xuguang and Feng, Jianfeng. (2006) Detecting time-dependent coherence between non-stationary electrophysiological signals - A combined statistical and time-frequency approach. Journal of Neuroscience Methods, Vol.156 (No.1-2). pp. 322-332. ISSN 0165-0270Full text not available from this repository.
Official URL: http://dx.doi.org/10.1016/j.jneumeth.2006.02.013
Various time-frequency methods have been used to study time-varying properties of non-stationary neurophysiological signals. In the present study, a time-frequency coherence estimate using continuous wavelet transform (CWT) together with its confidence intervals are proposed to evaluate the correlation between two non-stationary processes. The approach is based on averaging over repeat trials. A systematic comparison between approaches using CWT and short-time Fourier transform (STFT) is carried out. Simulated data are generated to test the performance of these methods when estimating time-frequency based coherence. In contrast to some recent studies, we find that CWT based coherence estimates do not supersede STFT based estimates. We suggest that a combination of STFT and CWT would be most suitable for analysing non-stationary neural data. Tests are presented to investigate the time and frequency discrimination capabilities of the two approaches. The methods are applied to two experimental data sets: electroencephalogram (EEG) and surface electromyogram (EMG) during wrist movements in a healthy subject, and local field potential (LFP) and surface EMG recordings during resting tremor in a Parkinsonian patient. Supporting software is available at http://www.dcs.warwick.ac.ukffeng/software/COD and http://www.neurospec.org. (c) 2006 Elsevier B.V. All rights reserved.
|Item Type:||Journal Article|
|Subjects:||Q Science > QD Chemistry
R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
|Divisions:||Faculty of Science > Computer Science
Faculty of Science > Centre for Scientific Computing
|Journal or Publication Title:||Journal of Neuroscience Methods|
|Official Date:||30 September 2006|
|Number of Pages:||11|
|Page Range:||pp. 322-332|
|Access rights to Published version:||Restricted or Subscription Access|
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