An extendable simulation framework for benchmarking EEG-based brain connectivity estimation methodologies

Due to its high temporal resolution, electroencephalography (EEG) is a promising research tool for studying functional and effective brain interaction. Yet, it is rather uncommon for researchers to validate their connectivity estimation methodologies prior to applying them to real data, even though problems have been pointed out regarding the validity of some of the predominant approaches. We here provide an extendable simulation framework that enables researchers to test their analysis pipelines on customizable realistically simulated EEG data. We define three simple criteria to measure source localization, connectivity detection and directionality estimation performance. All data and code needed to generate pseudo-EEG data and to benchmark a method's estimation performance are provided.