Document Detail

Cross-frequency decomposition: A novel technique for studying interactions between neuronal oscillations with different frequencies.
MedLine Citation:
PMID:  22217959     Owner:  NLM     Status:  Publisher    
OBJECTIVE: We present a novel method for the extraction of neuronal components showing cross-frequency phase synchronization. METHODS: In general the method can be applied for the detection of phase interactions between components with frequencies f1 and f2, where f2≈rf1 and r is some integer. We refer to the method as cross-frequency decomposition (CFD), which consists of the following steps: (a) extraction of f1-oscillations with the spatio-spectral decomposition algorithm (SSD); (b) frequency modification of the f1-oscillations obtained with SSD; and (c) finding f2-oscillations synchronous with f1-oscillations using least-squares estimation. RESULTS: Our simulations showed that CFD was capable of recovering interacting components even when the signal-to-noise ratio was as low as 0.01. An application of CFD to the real EEG data demonstrated that cross-frequency phase synchronization between alpha and beta oscillations can originate from the same or remote neuronal populations. CONCLUSIONS: CFD allows a compact representation of the sets of interacting components. The application of CFD to EEG data allows differentiating cross-frequency synchronization arising due to genuine neurophysiological interactions from interactions occurring due to quasi-sinusoidal waveform of neuronal oscillations. SIGNIFICANCE: CFD is a method capable of extracting cross-frequency coupled neuronal oscillations even in the presence of strong noise.
Vadim V Nikulin; Guido Nolte; Gabriel Curio
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-1-2
Journal Detail:
Title:  Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology     Volume:  -     ISSN:  1872-8952     ISO Abbreviation:  -     Publication Date:  2012 Jan 
Date Detail:
Created Date:  2012-1-5     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  100883319     Medline TA:  Clin Neurophysiol     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Neurophysics Group, Department of Neurology, Campus Benjamin Franklin, Charité - University Medicine Berlin, D-12200 Berlin, Germany; Bernstein Center for Computational Neuroscience, Berlin, Germany.
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