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Cited by 608

The DOI matches its Crossref record; 52 of the 52 references it cites were found in a registry or an index.

Untangling cross-frequency coupling in neuroscience

Open access
Aru, Juhan, Aru, Jaan, Priesemann, Viola, Wibral, Michael, Lana, Luiz, Pipa, Gordon, Singer, Wolf, Vicente, Raul·2015·Current Opinion in Neurobiology
DOI 10.1016/j.conb.2014.08.002
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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. Highlights Fundamental caveats and confounds in the methodology of assessing CFC are discussed. Significant CFC can be observed without any underlying physiological coupling. Non-stationarity of a time-series leads to spectral correlations interpreted as CFC. We offer practical recommendations, which can relieve some of the current confounds. Further theoretical and experimental work is needed to ground the CFC analysis.

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Metadata

Authors
Aru, J., Aru, J., Priesemann, V., Wibral, M., Lana, L., Pipa, G., Singer, W., & Vicente, R.
Venue
Current Opinion in Neurobiology
Publisher
Elsevier BV
Published
2015-04
Volume
31
Pages
51-61
ISSN
0959-4388 (ISSN-L)
DOI
10.1016/j.conb.2014.08.002
OpenAlex
W2067058552
Cited by
608
References
52
FWCI
3.69
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Untangling cross-frequency coupling in neuroscience. https://app.cochat.ai/papers/10.1016/j.conb.2014.08.002
The paper
Aru, J., Aru, J., Priesemann, V., Wibral, M., Lana, L., Pipa, G., Singer, W., & Vicente, R. (2015). Untangling cross-frequency coupling in neuroscience. Current Opinion in Neurobiology. https://doi.org/10.1016/j.conb.2014.08.002

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.