Evidence map›Paper›PMID 38605061›Full record

ArticleScientific reports2024

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

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

7 authors.

Alessio BastiDepartment of Neuroscience, Imaging and Clinical Sciences, "G. d'Annunzio" University of Chieti-Pescara, 66100, Chieti, Italy. alessiobasti@hotmail.it.
Guido NolteDepartment of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, 20246, Hamburg, Germany.
Roberto GuidottiDepartment of Neuroscience, Imaging and Clinical Sciences, "G. d'Annunzio" University of Chieti-Pescara, 66100, Chieti, Italy.
Risto J IlmoniemiDepartment of Neuroscience and Biomedical Engineering, Aalto University School of Science, 02150, Espoo, Finland.
Gian Luca RomaniInstitute for Advanced Biomedical Technologies, "G. d'Annunzio" University of Chieti-Pescara, 66100, Chieti, Italy.
Vittorio PizzellaDepartment of Neuroscience, Imaging and Clinical Sciences, "G. d'Annunzio" University of Chieti-Pescara, 66100, Chieti, Italy.
Laura MarzettiDepartment of Neuroscience, Imaging and Clinical Sciences, "G. d'Annunzio" University of Chieti-Pescara, 66100, Chieti, Italy.

Funding

European Research Council (ERC Synergy) under the European Union's Horizon 2020 research and innovation programme 810377
6 · The paper itself

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.

Identifiers

PMID38605061
PMCPMC11009359

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.