A bicoherence approach to analyze multi-dimensional cross-frequency coupling in EEG/MEG data

Alessio Basti*, Guido Nolte, Roberto Guidotti, Risto J. Ilmoniemi, Gian Luca Romani, Vittorio Pizzella, Laura Marzetti

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

We introduce a blockwise generalisation of the Antisymmetric Cross-Bicoherence (ACB), a statistical method based on bispectral analysis. The Multi-dimensional ACB (MACB) is an approach that aims at detecting quadratic lagged phase-interactions between vector time series in the frequency domain. Such a coupling can be empirically observed in functional neuroimaging data, e.g., in electro/magnetoencephalographic signals. MACB is invariant under orthogonal trasformations of the data, which makes it independent, e.g., on the choice of the physical coordinate system in the neuro-electromagnetic inverse procedure. In extensive synthetic experiments, we prove that MACB performance is significantly better than that obtained by ACB. Specifically, the shorter the data length, or the higher the dimension of the single data space, the larger the difference between the two methods.

Original languageEnglish
Article number8461
Number of pages12
JournalScientific Reports
Volume14
Issue number1
DOIs
Publication statusPublished - 11 Apr 2024
MoE publication typeA1 Journal article-refereed

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