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  Nonlinear interaction decomposition (NID): A method for separation of cross-frequency coupled sources in human brain

Jamshidi Idaji, M., Müller, K.-R., Nolte, G., Maess, B., Villringer, A., & Nikulin, V. V. (2020). Nonlinear interaction decomposition (NID): A method for separation of cross-frequency coupled sources in human brain. NeuroImage, 211: 116599. doi:10.1016/j.neuroimage.2020.116599.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0006-10C6-8 Version Permalink: http://hdl.handle.net/21.11116/0000-0006-FFB8-C
Genre: Journal Article

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 Creators:
Jamshidi Idaji, Mina1, 2, 3, Author              
Müller, Klaus-Robert2, 4, 5, Author
Nolte, Guido6, Author
Maess, Burkhard7, Author              
Villringer, Arno1, 8, Author              
Nikulin, Vadim V.1, 9, 10, Author              
Affiliations:
1Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634549              
2Machine Learning Group, Faculty of Electrical Engineering and Computer Science, TU Berlin, Germany, ou_persistent22              
3International Max Planck Research School on Neuroscience of Communication, Leipzig, Germany, ou_persistent22              
4Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea, ou_persistent22              
5Max Planck Institute for Informatics, Saarbrücken, Germany, ou_persistent22              
6Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Germany, ou_persistent22              
7Methods and Development Group Brain Networks, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_2205650              
8Clinic for Cognitive Neurology, University of Leipzig, Germany, ou_persistent22              
9Centre for Cognition and Decision Making, National Research University Higher School of Economics, Moscow, Russia, ou_persistent22              
10Department of Neurology, Charité University Medicine Berlin, Germany, ou_persistent22              

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Free keywords: Nonlinear interaction decomposition; NID; Cross-frequency coupling; MEG EEG; Nonlinear neuronal interactions; Independent component analysis; ICA
 Abstract: Cross-frequency coupling (CFC) between neuronal oscillations reflects an integration of spatially and spectrally distributed information in the brain. Here, we propose a novel framework for detecting such interactions in Magneto- and Electroencephalography (MEG/EEG), which we refer to as Nonlinear Interaction Decomposition (NID). In contrast to all previous methods for separation of cross-frequency (CF) sources in the brain, we propose that the extraction of nonlinearly interacting oscillations can be based on the statistical properties of their linear mixtures. The main idea of NID is that nonlinearly coupled brain oscillations can be mixed in such a way that the resulting linear mixture has a non-Gaussian distribution. We evaluate this argument analytically for amplitude-modulated narrow-band oscillations which are either phase-phase or amplitude-amplitude CF coupled. We validated NID extensively with simulated EEG obtained with realistic head modelling. The method extracted nonlinearly interacting components reliably even at SNRs as small as dB. Additionally, we applied NID to the resting-state EEG of 81 subjects to characterize CF phase-phase coupling between alpha and beta oscillations. The extracted sources were located in temporal, parietal and frontal areas, demonstrating the existence of diverse local and distant nonlinear interactions in resting-state EEG data. All codes are available publicly via GitHub.

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Language(s): eng - English
 Dates: 2020-01-162019-11-252020-01-312020-02-052020-05-01
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1016/j.neuroimage.2020.116599
Other: epub 2020
PMID: 32035185
 Degree: -

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Title: NeuroImage
Source Genre: Journal
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Publ. Info: Orlando, FL : Academic Press
Pages: - Volume / Issue: 211 Sequence Number: 116599 Start / End Page: - Identifier: ISSN: 1053-8119
CoNE: https://pure.mpg.de/cone/journals/resource/954922650166