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Publications

Journal Article Epublish

PubMed: 42416353 DOI: 10.3389/fninf.2026.1791461

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

Front Neuroinform 20:1791461

Authors: Miroslaw Wyczesany, Sara Spadone, Tomasz Górski, Adam Łabaza, Michal Domagala, Maciej Kaminski, Tomasz S Ligeza, Paolo Capotosto, Thomas Kroker, Markus Junghöfer, Stefania Della Penna

Affiliations

  • Institute of Psychology, Jagiellonian University, Kraków, Poland.
  • Departmental Faculty of Medicine, Saint Camillus International University of Health and Medical Sciences (UniCamillus), Rome, Italy.
  • The Faculty of Physics, Astronomy and Informatics, Nicolaus Copernicus University, Toruń, Poland.
  • Center for Cognitive Science, Jagiellonian University, Kraków, Poland.
  • Department of Physics, University of Warsaw, Warsaw, Poland.
  • Department of Neuroscience, Imaging and Clinical Sciences, University "G. d'Annunzio", Chieti, Italy.
  • Institute for Advanced Biomedical Technologies (ITAB), University "G. d'Annunzio", Chieti, Italy.
  • UdA-TechLab, Research Center, University "G. d'Annunzio", Chieti, Italy.
  • Institute for Biomagnetism and Biosignal Analysis, University of Münster, Münster, Germany.

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.