Evidence map›Paper›PMID 38825981›Full record

ArticleHuman brain mapping2024

The effects of spatial leakage correction on the reliability of EEG-based functional connectivity networks.

Péter Nagy, Brigitta Tóth, István Winkler, Ádám Boncz

Abstract read
In one paragraph

Article in Human brain mapping, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

13 citing papers in PubMed.

  1. Article
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  4. Shared spatial and temporal principles govern connectome dynamics across timescales.Proceedings of the National Academy of Sciences of the United States of America · 2026
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  5. Review
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  10. Light-Driven HPlants (Basel, Switzerland) · 2024
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Péter NagyHUN-REN Research Centre for Natural Sciences, Budapest, Hungary.ORCID 0000-0003-1902-0469
Brigitta TóthHUN-REN Research Centre for Natural Sciences, Budapest, Hungary.
István WinklerHUN-REN Research Centre for Natural Sciences, Budapest, Hungary.
Ádám BonczHUN-REN Research Centre for Natural Sciences, Budapest, Hungary.

Funding

National Research, Development and Innovation Office of Hungary ANN131305National Research, Development and Innovation Office of Hungary K132642Office of Naval Research N62909-23-1-2025
6 · The paper itself

Abstract

Electroencephalography (EEG) functional connectivity (FC) estimates are confounded by the volume conduction problem. This effect can be greatly reduced by applying FC measures insensitive to instantaneous, zero-lag dependencies (corrected measures). However, numerous studies showed that FC measures sensitive to volume conduction (uncorrected measures) exhibit higher reliability and higher subject-level identifiability. We tested how source reconstruction contributed to the reliability difference of EEG FC measures on a large (n = 201) resting-state data set testing eight FC measures (including corrected and uncorrected measures). We showed that the high reliability of uncorrected FC measures in resting state partly stems from source reconstruction: idiosyncratic noise patterns define a baseline resting-state functional network that explains a significant portion of the reliability of uncorrected FC measures. This effect remained valid for template head model-based, as well as individual head model-based source reconstruction. Based on our findings we made suggestions how to best use spatial leakage corrected and uncorrected FC measures depending on the main goals of the study.

Indexed as

ConnectomeElectroencephalographyNerve NetAdultBrainFemaleHumansMagnetic Resonance ImagingMaleReproducibility of ResultsYoung AdultEEGfunctional connectivityreliabilitysource reconstructionspatial leakage

Identifiers

PMID38825981
PMCPMC11144954

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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.