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A Simulation Framework for Benchmarking EEG-Based Brain Connectivity Estimation Methodologies

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Abstract

Due to its high temporal resolution, electroencephalography (EEG) is widely used to study functional and effective brain connectivity. Yet, there is currently a mismatch between the vastness of studies conducted and the degree to which the employed analyses are theoretically understood and empirically validated. We here provide a simulation framework that enables researchers to test their analysis pipelines on realistic pseudo-EEG data. We construct a minimal example of brain interaction, which we propose as a benchmark for assessing a methodology’s general eligibility for EEG-based connectivity estimation. We envision that this benchmark be extended in a collaborative effort to validate methods in more complex scenarios. Quantitative metrics are defined to assess a method’s performance in terms of source localization, connectivity detection and directionality estimation. All data and code needed for generating pseudo-EEG data, conducting source reconstruction and connectivity estimation using baseline methods from the literature, evaluating performance metrics, as well as plotting results, are made publicly available. While this article covers only EEG modeling, we will also provide a magnetoencephalography version of our framework online.

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Acknowledgments

This work was supported by a Marie Curie International Outgoing Fellowship (Grant No. PIOF-GA-2013-625991) within the 7th European Community Framework Programme and the German Research Foundation (DFG) with SFB 936/Z3 and the BMBF (031A130). We thank Pedro Valdes-Sosa for suggesting the creation of a benchmark, Guido Nolte for contributing Matlab code, and the two Reviewers for their constructive comments.

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Authors and Affiliations

  1. Laboratory for Intelligent Imaging and Neural Computing, Columbia University, New York, NY, 10027, USA

    Stefan Haufe

  2. Machine Learning Department, Technische Universität Berlin, 10587, Berlin, Germany

    Stefan Haufe

  3. Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, 20246, Hamburg, Germany

    Arne Ewald

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  1. Stefan Haufe
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Correspondence to Stefan Haufe.

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This is one of several papers published together in Brain Topography on the "Special Issue: Controversies in EEG Source Analysis".

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Haufe, S., Ewald, A. A Simulation Framework for Benchmarking EEG-Based Brain Connectivity Estimation Methodologies. Brain Topogr 32, 625–642 (2019). https://doi.org/10.1007/s10548-016-0498-y

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