Computational Testing for Automated Preprocessing 2 : Practical Demonstration of a System for Scientific Data-Processing Workflow Management for High-Volume EEG

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dc.contributor.author Cowley, Benjamin U.
dc.contributor.author Korpela, Jussi
dc.date.accessioned 2018-05-02T11:45:01Z
dc.date.available 2018-05-02T11:45:01Z
dc.date.issued 2018-04-10
dc.identifier.citation Cowley , B U & Korpela , J 2018 , ' Computational Testing for Automated Preprocessing 2 : Practical Demonstration of a System for Scientific Data-Processing Workflow Management for High-Volume EEG ' , Frontiers in Neuroscience , vol. 12 , 236 . https://doi.org/10.3389/fnins.2018.00236
dc.identifier.other PURE: 105845109
dc.identifier.other PURE UUID: 608ce55e-946d-4fc9-8f45-c924e465f737
dc.identifier.other WOS: 000429597400001
dc.identifier.other Scopus: 85045289611
dc.identifier.other ORCID: /0000-0001-8828-2994/work/44473668
dc.identifier.uri http://hdl.handle.net/10138/234635
dc.description.abstract Existing tools for the preprocessing of EEG data provide a large choice of methods to suitably prepare and analyse a given dataset. Yet it remains a challenge for the average user to integrate methods for batch processing of the increasingly large datasets of modern research, 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 artifacts in channels, epochs or segments. This introduces extra subjectivity, is slow, and is not reproducible. Batching and well-designed automation can help to regularize EEG preprocessing, and thus reduce 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 preprocessing methods. Here we demonstrate the application of CTAP to high-resolution EEG data in three modes of use. First, a linear processing pipeline with mostly default parameters illustrates ease-of-use for naive users. Second, a branching pipeline illustrates CTAP's support for comparison of competing methods. Third, a pipeline with built-in parameter-sweeping illustrates CTAP's capability to support data-driven method parameterization. CTAP extends the existing functions and data structure from the well-known EEGLAB toolbox, based on Matlab, and produces extensive quality control outputs. CTAP is available under MIT open-source licence from https://github.com/bwrc/ctap. en
dc.format.extent 14
dc.language.iso eng
dc.relation.ispartof Frontiers in Neuroscience
dc.rights cc_by
dc.rights.uri info:eu-repo/semantics/openAccess
dc.subject EEG
dc.subject electroencephalography
dc.subject EEGLAB
dc.subject scientific workflow system
dc.subject workflow management
dc.subject computational testing
dc.subject automated preprocessing
dc.subject parameter sweep
dc.subject FEATURES
dc.subject PIPELINE
dc.subject 515 Psychology
dc.subject 213 Electronic, automation and communications engineering, electronics
dc.title Computational Testing for Automated Preprocessing 2 : Practical Demonstration of a System for Scientific Data-Processing Workflow Management for High-Volume EEG en
dc.type Article
dc.contributor.organization Department of Digital Humanities
dc.contributor.organization Department of Psychology and Logopedics
dc.description.reviewstatus Peer reviewed
dc.relation.doi https://doi.org/10.3389/fnins.2018.00236
dc.relation.issn 1662-453X
dc.rights.accesslevel openAccess
dc.type.version publishedVersion

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