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A statistical framework to assess cross-frequency coupling while accounting for confounding analysis effects

What is being modeled?
Interactions between different frequency brain rhythms.
Description & purpose of resource

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We provide a statistical modeling framework to estimate high frequency amplitude as a function of both the low frequency amplitude and low frequency phase; the result is a measure of phase-amplitude coupling that accounts for changes in the low frequency amplitude. The proposed method successfully detects cross-frequency coupling (CFC) between the low frequency phase or amplitude and the high frequency amplitude, and outperforms an existing method in biologically-motivated examples.

Spatial scales
tissue
Temporal scales
10-3 - 1 s
1 - 103 s
This resource is currently
mature and useful in ongoing research
Has this resource been validated?
No
How has the resource been validated?

Details, simulation results, and applications to in vivo data are published.

Can this resource be associated with other resources? (e.g.: modular models, linked tools and platforms)
No
Key publications (e.g. describing or using resource)

A statistical framework to assess cross-frequency coupling while accounting for confounding analysis effects, Nadalin et al eLife 2019;8:e44287
https://elifesciences.org/articles/44287

DOI link to publication describing this resource

https://doi.org/10.7554/eLife.44287

Link to resource
All code to use and further develop this method is available on GitHub.
Collaborators
Mark Kramer
PI contact information
mak@math. bu.edu
Keywords
BRAIN TMM
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