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

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Jamshidi Idaji,  Mina
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
International Max Planck School NeuroCom;
Machine Learning Group, Technical University of Berlin, Berlin, Germany;

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Maess,  Burkhard
Methods and Development Unit - MEG and Cortical Networks, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Villringer,  Arno
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Nikulin,  Vadim V.
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Center for Cognitive and Decision Making, Institute for Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia;
Neurophysics Group, Department of Neurology, Charite-Universitaetsmedizin Berlin, Berlin, Germany;

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JamshidiIdaji_2019.pdf
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Citation

Jamshidi Idaji, M., Mueller, K.-R., Nolte, G., Maess, B., Villringer, A., & Nikulin, V. V. (2019). Nonlinear interaction decomposition (NID): A method for separation of cross-frequency coupled sources in human brain. bioRxiv. doi:10.1101/680397.


Cite as: http://hdl.handle.net/21.11116/0000-0004-C272-0
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