EPOS: EEG Processing Open-Source Scripts

  title={EPOS: EEG Processing Open-Source Scripts},
  author={Johannes Rodrigues and Martin Wei{\ss} and Johannes Hewig and John J. B. Allen},
  journal={Frontiers in Neuroscience},
Background Since the replication crisis, standardization has become even more important in psychological science and neuroscience. As a result, many methods are being reconsidered, and researchers’ degrees of freedom in these methods are being discussed as a potential source of inconsistencies across studies. New Method With the aim of addressing these subjectivity issues, we have been working on a tutorial-like EEG (pre-)processing pipeline to achieve an automated method based on the semi… 
The methodology and dataset of the coscience eeg-personality project – a large-scale, multi-laboratory project grounded in cooperative forking paths analysis
The design and methodology of the project are outlined, a detailed overview of the resulting large-scale dataset is provided, and the basis for consistency and depth to the methodology of all resulting empirical articles are formed.
Mental chronometry in big noisy data
It is demonstrated that fractional area latency in pruned and jackknifed data may amplify within-subjects effect sizes dramatically in the analyzed data set, and the recently introduced method of Standardized Measurement Error (SME) to prune the dataset.
HAPPILEE: The Harvard Automated Processing Pipeline In Low Electrode Electroencephalography, a standardized software for low density EEG and ERP data
The HAPPILEE pipeline is proposed as a standardized, automated pipeline optimized for EEG recordings with low density channel layouts of any size and includes post-processing reports of data and pipeline quality metrics to facilitate the evaluation and reporting of data quality and processing-related changes to the data in a standardized manner.
Introducing RELAX (the Reduction of Electroencephalographic Artifacts): A fully automated pre-processing pipeline for cleaning EEG data – Part 2: Application to Event-Related Potentials
This companion article introduced RELAX (the Reduction of Electroencephalographic Artifacts), an automated and modular cleaning pipeline that reduces artifacts with Multiple Wiener Filtering and wavelet enhanced independent component analysis ( wICA) applied to artifact components detected with ICLabel (wICA_ICLabel) (Bailey et al., 2022).
Reliability of reward ERPs in middle-late adolescents using a custom and a standardized preprocessing pipeline.
Despite advantage of neuroimaging measures in translational research frameworks, less is known about the psychometric properties thereof, especially in middle-late adolescents. Earlier, we examined
Scorepochs: A Computer-Aided Scoring Tool for Resting-State M/EEG Epochs
M/EEG resting-state analysis often requires the definition of the epoch length and the criteria to select which epochs to include in the subsequent steps. However, the effects of epoch selection
EEG-Based Identification of Emotional Neural State Evoked by Virtual Environment Interaction
This study proposes a machine learning framework for emotion state classification using EEG signals in virtual reality (VR) environments and expects that this framework can be applied widely not only to psychological research but also to mental health-related issues.
The Influence of Mental Imagery Expertise of Pen and Paper Players versus Computer Gamers upon Performance and Electrocortical Correlates in a Difficult Mental Rotation Task
We investigated the influence of mental imagery expertise in 15 pen and paper role-players as an expert group compared to the gender-matched control group of computer role-players in the difficult
Timing of adoption is associated with electrophysiological brain activity and externalizing problems among children adopted internationally.
This study investigated middle childhood resting electroencephalography (EEG) and behavioral adjustment in 35 internationally adopted children removed from early caregiving adversity between 6 and 29


An automatic pre-processing pipeline for EEG analysis (APP) based on robust statistics
Computational testing for automated preprocessing: a Matlab toolbox to enable large scale electroencephalography data processing
The computational testing for automated preprocessing (CTAP) toolbox is presented, to facilitate batch-processing that is easy for experts and novices alike; testing and manual comparison of preprocessing methods.
Automagic: Standardized preprocessing of big EEG data
This examination suggests that a applying a pipeline of algorithms to detect artifactual channels in combination with Multiple Artifact Rejection Algorithm (MARA), an independent component analysis (ICA)-based artifact correction method, is sufficient to reduce a large extent of artifacts.
The PREP pipeline: standardized preprocessing for large-scale EEG analysis
It is demonstrated that ordinary average referencing improves the signal-to-noise ratio, but that noisy channels can contaminate the results and a multi-stage robust referencing scheme is introduced to deal with the noisy channel-reference interaction.
Event-related potentials : a methods handbook
The use of ERPs in relation to such specific participant populations as children and neuropsychological patients and the ways in which ERPs can be combined with related methodologies, including intracranial ERPs and hemodynamic imaging are covered.
BEAPP: The Batch Electroencephalography Automated Processing Platform
The Batch EEG Automated Processing Platform (BEAPP), an automated, flexible EEG processing platform incorporating freely available software tools for batch processing of multiple EEG files across multiple processing steps, aims to streamline batch EEG processing, improve accessibility to computational EEG assessment, and increase reproducibility of results.
Automatic Classification of Artifactual ICA-Components for Artifact Removal in EEG Signals
This work proposes a universal and efficient classifier of ICA components for the subject independent removal of artifacts from EEG data that is applicable for different electrode placements and supports the introspection of results.