Detection of neural correlates of self-paced motor activity using empirical mode decomposition phase locking analysis

Sweeney-Reed, C. M. and Nasuto, S. J. ORCID: https://orcid.org/0000-0001-9414-9049 (2009) Detection of neural correlates of self-paced motor activity using empirical mode decomposition phase locking analysis. Journal of Neuroscience Methods, 184 (1). pp. 54-70. ISSN 0165-0270 doi: 10.1016/j.jneumeth.2009.07.023

Abstract/Summary

Transient episodes of synchronisation of neuronal activity in particular frequency ranges are thought to underlie cognition. Empirical mode decomposition phase locking (EMDPL) analysis is a method for determining the frequency and timing of phase synchrony that is adaptive to intrinsic oscillations within data, alleviating the need for arbitrary bandpass filter cut-off selection. It is extended here to address the choice of reference electrode and removal of spurious synchrony resulting from volume conduction. Spline Laplacian transformation and independent component analysis (ICA) are performed as pre-processing steps, and preservation of phase synchrony between synthetic signals. combined using a simple forward model, is demonstrated. The method is contrasted with use of bandpass filtering following the same preprocessing steps, and filter cut-offs are shown to influence synchrony detection markedly. Furthermore, an approach to the assessment of multiple EEG trials using the method is introduced, and the assessment of statistical significance of phase locking episodes is extended to render it adaptive to local phase synchrony levels. EMDPL is validated in the analysis of real EEG data, during finger tapping. The time course of event-related (de)synchronisation (ERD/ERS) is shown to differ from that of longer range phase locking episodes, implying different roles for these different types of synchronisation. It is suggested that the increase in phase locking which occurs just prior to movement, coinciding with a reduction in power (or ERD) may result from selection of the neural assembly relevant to the particular movement. (C) 2009 Elsevier B.V. All rights reserved.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/15393
Item Type	Article
Refereed	Yes
Divisions	Life Sciences > School of Biological Sciences > Department of Bio-Engineering
Uncontrolled Keywords	EEG, Time-frequency, Phase synchrony, Empirical mode decomposition, Finger tap, INDEPENDENT COMPONENT ANALYSIS, MILD COGNITIVE IMPAIRMENT, HUMAN, SUPPLEMENTARY MOTOR, ELECTROMYOGRAPHIC SIGNALS, INCREASED, SYNCHRONIZATION, FUNCTIONAL CONNECTIVITY, EEG SYNCHRONIZATION, ALZHEIMERS-DISEASE, SENSORIMOTOR AREAS, HILBERT SPECTRUM
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