Evidence map›Paper›PMID 42416353›Full record

ArticleFrontiers in neuroinformatics2026

ASCT: a pipeline for standardized analysis of MEG/EEG directional connectivity. Practical guidelines for applications of source-based Directed Transfer Function.

Miroslaw Wyczesany, Sara Spadone, Tomasz Górski, Adam Łabaza, Michal Domagala, Maciej Kaminski, Tomasz S Ligeza, Paolo Capotosto, Thomas Kroker, Markus Junghöfer and 1 more

Abstract read
In one paragraph

Article in Frontiers in neuroinformatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

11 authors.

Miroslaw WyczesanyInstitute of Psychology, Jagiellonian University, Kraków, Poland.
Sara SpadoneDepartmental Faculty of Medicine, Saint Camillus International University of Health and Medical Sciences (UniCamillus), Rome, Italy.
Tomasz GórskiThe Faculty of Physics, Astronomy and Informatics, Nicolaus Copernicus University, Toruń, Poland.
Adam ŁabazaInstitute of Psychology, Jagiellonian University, Kraków, Poland.
Michal DomagalaCenter for Cognitive Science, Jagiellonian University, Kraków, Poland.
Maciej KaminskiDepartment of Physics, University of Warsaw, Warsaw, Poland.
Tomasz S LigezaInstitute of Psychology, Jagiellonian University, Kraków, Poland.
Paolo CapotostoDepartment of Neuroscience, Imaging and Clinical Sciences, University "G. d'Annunzio", Chieti, Italy.
Thomas KrokerInstitute for Biomagnetism and Biosignal Analysis, University of Münster, Münster, Germany.
Markus JunghöferInstitute for Biomagnetism and Biosignal Analysis, University of Münster, Münster, Germany.
Stefania Della PennaDepartment of Neuroscience, Imaging and Clinical Sciences, University "G. d'Annunzio", Chieti, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The article presents the Atlantis Source Connectivity Toolbox (ASCT), a pipeline for the complete analysis of source-based directed (effective) connectivity from MEG/EEG signals. Connectivity estimation is implemented with the Directed Transfer Function, a multivariate autoregressive method grounded in the Granger causality approach. The theoretical concepts and challenges in source reconstruction and causal inferences from electrophysiological and biomagnetic recordings are introduced. Importantly, the guidelines for the custom analyses are also presented together with the toolbox user manual. By providing the complete analytic pipeline with practical recommendations, we intend to support standardization and replicability in connectivity studies. The validation of the method is further demonstrated with simulated MEG data, prepared from real resting data recording, as well as with realistic EEG data from the Eriksen flanker task. Our results highlight the importance of routine use of the leakage correction that prevents the appearance of spurious links. We also discuss potential benefits of source separation prior to their reconstruction for more accurate estimates of connectivity.

Indexed as

directed connectivityEEGleakage correctionmanualrecommendationsreplicabilitysource reconstructionstandardization

Identifiers

PMID42416353
PMCPMC13337504

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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.