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EEG is a rich source of information regarding brain functioning, and is the most lightweight and affordable method of brain imaging. However, the pre-processing of EEG data is quite complicated and most existing tools present the experimenter with a large choice of methods for analysis, but no framework for method comparison to choose an optimal approach. Additionally, many tools still require a high degree of manual decision making for, e.g. the classification of artefacts in channels, epochs or segments. This introduces excessive subjectivity, is slow, and is not reproducible. Batching and well-designed automation can help to regularise EEG preprocessing, and thus minimise human effort, subjectivity, and consequent error. The Computational Testing for Automated Preprocessing (CTAP) toolbox facilitates: i) batch processing that is easy for experts and novices alike; ii) testing and comparison of automated methods. CTAP uses the existing data structure and functions from the well-known EEGLAB tool, based on Matlab, and produces extensive quality control outputs.
This is a submission to PeerJ Computer Science for review.
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