ASCT: a pipeline for standardized analysis of MEG/EEG directional connectivity. Practical guidelines for applications of source-based Directed Transfer Function.
IF 2.9 4区 医学Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Miroslaw Wyczesany, Sara Spadone, Tomasz Górski, Adam Łabaza, Michal Domagala, Maciej Kaminski, Tomasz S Ligeza, Paolo Capotosto, Thomas Kroker, Markus Junghöfer, Stefania Della Penna
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引用次数: 0
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.
期刊介绍：
Frontiers in Neuroinformatics publishes rigorously peer-reviewed research on the development and implementation of numerical/computational models and analytical tools used to share, integrate and analyze experimental data and advance theories of the nervous system functions. Specialty Chief Editors Jan G. Bjaalie at the University of Oslo and Sean L. Hill at the École Polytechnique Fédérale de Lausanne are supported by an outstanding Editorial Board of international experts. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics and the public worldwide.
Neuroscience is being propelled into the information age as the volume of information explodes, demanding organization and synthesis. Novel synthesis approaches are opening up a new dimension for the exploration of the components of brain elements and systems and the vast number of variables that underlie their functions. Neural data is highly heterogeneous with complex inter-relations across multiple levels, driving the need for innovative organizing and synthesizing approaches from genes to cognition, and covering a range of species and disease states.
Frontiers in Neuroinformatics therefore welcomes submissions on existing neuroscience databases, development of data and knowledge bases for all levels of neuroscience, applications and technologies that can facilitate data sharing (interoperability, formats, terminologies, and ontologies), and novel tools for data acquisition, analyses, visualization, and dissemination of nervous system data. Our journal welcomes submissions on new tools (software and hardware) that support brain modeling, and the merging of neuroscience databases with brain models used for simulation and visualization.
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