Untangling cross-frequency coupling in neuroscience

Aru, J.; Aru, J.; Priesemann, Viola; Wibral, M.; Lana, L.; Pipa, G.; Singer, W.; Vicente, R.

doi:10.1016/j.conb.2014.08.002

Item

ITEM ACTIONSEXPORT

Add to Basket

Local TagsRelease HistoryDetailsSummary

Released

Journal Article

Untangling cross-frequency coupling in neuroscience

MPS-Authors

/persons/resource/persons173619

Priesemann, Viola
Department of Nonlinear Dynamics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society;

External Resource

http://linkinghub.elsevier.com/retrieve/pii/S0959-4388(14)00164-0
(Publisher version)

Fulltext (restricted access)

There are currently no full texts shared for your IP range.

Fulltext (public)

There are no public fulltexts stored in PuRe

Supplementary Material (public)

There is no public supplementary material available

Citation

Aru, J., Aru, J., Priesemann, V., Wibral, M., Lana, L., Pipa, G., et al. (2015). Untangling cross-frequency coupling in neuroscience. Current Opinion in Neurobiology, 31, 51-61. doi:10.1016/j.conb.2014.08.002.

Cite as: https://hdl.handle.net/11858/00-001M-0000-002B-A20A-D

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.