Title
A novel method for device-related electroencephalography artifact suppression to explore cochlear implant-related cortical changes in single-sided deafness A novel method for device-related electroencephalography artifact suppression to explore cochlear implant-related cortical changes in single-sided deafness
Author
Faculty/Department
Faculty of Medicine and Health Sciences
Publication type
article
Publication
Amsterdam ,
Subject
Chemistry
Biology
Human medicine
Source (journal)
Journal of neuroscience methods. - Amsterdam
Volume/pages
255(2015) , p. 22-28
ISSN
0165-0270
ISI
000364247600004
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
Background: Quantitative electroencephalography (qEEG) is effective when used to analyze ongoing cortical oscillations in cochlear implant (CI) users. However, localization of cortical activity in such users via qEEG is confounded by the presence of artifacts produced by the device itself. Typically, independent component analysis (ICA) is used to remove CI artifacts in auditory evoked EEG signals collected upon brief stimulation and it is effective for auditory evoked potentials (AEPs). However, AEPs do not reflect the daily environments of patients, and thus, continuous EEG data that are closer to such environments are desirable. In this case, device-related artifacts in EEG data are difficult to remove selectively via ICA due to over-completion of EEG data removal in the absence of preprocessing. New methods: EEGs were recorded for a long time under conditions of continuous auditory stimulation. To obviate the over-completion problem, we limited the frequency of CI artifacts to a significant characteristic peak and apply ICA artifact removal. Results: Topographic brain mapping results analyzed via band-limited (BL)-ICA exhibited a better energy distribution, matched to the CI location, than data obtained using conventional ICA. Also, source localization data verified that BL-ICA effectively removed Cl artifacts. Comparison with existing method: The proposed method selectively removes Cl artifacts from continuous EEG recordings, while ICA removal method shows residual peak and removes important brain activity signals. Conclusion: Cl artifacts in EEG data obtained during continuous passive listening can be effectively removed with the aid of BL-ICA, opening up new EEG research possibilities in subjects with Cls. (C) 2015 Elsevier B.V. All rights reserved.
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