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Curr Opin Neurobiol. 2015 Apr;31:51-61. doi: 10.1016/j.conb.2014.08.002. Epub 2014 Sep 15.

Untangling cross-frequency coupling in neuroscience.

Author information

1
Max-Planck Institute for Brain Research, Frankfurt am Main 60528, Germany; École Normale Supérieure de Lyon (UMPA), Lyon 69364, France.
2
Max-Planck Institute for Brain Research, Frankfurt am Main 60528, Germany; Frankfurt Institute for Advanced Studies, Frankfurt am Main 60438, Germany; Ernst Strüngmann Institute, Frankfurt am Main 60528, Germany; Institute of Public Law, Tartu University, Tallinn 10119, Estonia; Institute of Computer Science, University of Tartu, Tartu 50409, Estonia.
3
Max-Planck Institute for Brain Research, Frankfurt am Main 60528, Germany; Frankfurt Institute for Advanced Studies, Frankfurt am Main 60438, Germany; Max-Planck Institute for Dynamics and Self-Organization, Göttingen 37077, Germany.
4
MEG Unit, Brain Imaging Center, Goethe University, Frankfurt am Main 60528, Germany.
5
Max-Planck Institute for Brain Research, Frankfurt am Main 60528, Germany; Frankfurt Institute for Advanced Studies, Frankfurt am Main 60438, Germany; Ernst Strüngmann Institute, Frankfurt am Main 60528, Germany; Brain Institute, Federal University of Rio Grande do Norte, Natal 59056, Brazil.
6
Institute of Cognitive Science, University of Osnabrueck, 49069, Germany.
7
Max-Planck Institute for Brain Research, Frankfurt am Main 60528, Germany; Frankfurt Institute for Advanced Studies, Frankfurt am Main 60438, Germany; Ernst Strüngmann Institute, Frankfurt am Main 60528, Germany.
8
Max-Planck Institute for Brain Research, Frankfurt am Main 60528, Germany; Frankfurt Institute for Advanced Studies, Frankfurt am Main 60438, Germany; Ernst Strüngmann Institute, Frankfurt am Main 60528, Germany; MEG Unit, Brain Imaging Center, Goethe University, Frankfurt am Main 60528, Germany; Institute of Computer Science, University of Tartu, Tartu 50409, Estonia. Electronic address: raulvicente@gmail.com.

Abstract

Cross-frequency coupling (CFC) has been proposed to coordinate neural dynamics across spatial and temporal scales. Despite its potential relevance for understanding healthy and pathological brain function, the standard CFC analysis and physiological interpretation come with fundamental problems. For example, apparent CFC can appear because of spectral correlations due to common non-stationarities that may arise in the total absence of interactions between neural frequency components. To provide a road map towards an improved mechanistic understanding of CFC, we organize the available and potential novel statistical/modeling approaches according to their biophysical interpretability. While we do not provide solutions for all the problems described, we provide a list of practical recommendations to avoid common errors and to enhance the interpretability of CFC analysis.

PMID:
25212583
DOI:
10.1016/j.conb.2014.08.002
[Indexed for MEDLINE]

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