Computational Testing for Automated Preprocessing : a Matlab toolbox to enable large scale electroencephalography data processing

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http://hdl.handle.net/10138/214421

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Cowley , B U , Korpela , J & Torniainen , J 2017 , ' Computational Testing for Automated Preprocessing : a Matlab toolbox to enable large scale electroencephalography data processing ' , PeerJ , vol. 3 , 108 . https://doi.org/10.7717/peerj-cs.108

Title: Computational Testing for Automated Preprocessing : a Matlab toolbox to enable large scale electroencephalography data processing
Author: Cowley, Benjamin U.; Korpela, Jussi; Torniainen, Jari
Contributor: University of Helsinki, Department of Psychology and Logopedics
University of Helsinki, University of Eastern Finland
Date: 2017-03-06
Language: eng
Number of pages: 26
Belongs to series: PeerJ
ISSN: 2167-8359
URI: http://hdl.handle.net/10138/214421
Abstract: Electroencephalography (EEG) is a rich source of information regarding brain function. However, the preprocessing of EEG data can be quite complicated, due to several factors. For example, the distinction between true neural sources and noise is indeterminate; EEG data can also be very large. The various factors create a large number of subjective decisions with consequent risk of compound error. Existing tools present the experimenter with a large choice of analysis methods. Yet it remains a challenge for the researcher to integrate methods for batch-processing of the average large datasets, and compare methods to choose an optimal approach across the many possible parameter configurations. 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 extra subjectivity, is slow and is not reproducible. Batching and well-designed automation can help to regularise EEG preprocessing, and thus reduce human effort, subjectivity and consequent error. We present the computational testing for automated preprocessing (CTAP) toolbox, to facilitate: (i) batch-processing that is easy for experts and novices alike; (ii) testing and manual comparison of preprocessing methods. CTAP extends the existing data structure and functions from the well-known EEGLAB toolbox, based on Matlab and produces extensive quality control outputs. CTAP is available under MIT licence from https://github.com/bwrc/ctap.
Subject: Computation, Testing, Automation, Preprocessing, EEGLAB, Electroencephalography, Signal processing
113 Computer and information sciences
318 Medical biotechnology
6162 Cognitive science
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