Please use this identifier to cite or link to this item: doi:10.22028/D291-33447
Title: EEG Data Quality: Determinants and Impact in a Multicenter Study of Children, Adolescents, and Adults with Attention-Deficit/Hyperactivity Disorder (ADHD)
Author(s): Kaiser, Anna
Aggensteiner, Pascal-M.
Holtmann, Martin
Fallgatter, Andreas
Romanos, Marcel
Abenova, Karina
Alm, Barbara
Becker, Katja
Döpfner, Manfred
Ethofer, Thomas
Freitag, Christine M.
Geissler, Julia
Hebebrand, Johannes
Jans, Thomas
Jendreizik, Lea Teresa
Ketter, Johanna
Legenbauer, Tanja
Philipsen, Alexandra
Poustka, Luise
Renner, Tobias
Retz, Wolfgang
Rösler, Michael
Thome, Johannes
Uebel-von Sandersleben, Henrik
von Wirth, Elena
Zinnow, Toivo
Hohmann, Sarah
Millenet, Sabina
Holz, Nathalie E.
Banaschewski, Tobias
Brandeis, Daniel
on behalf of the ESCAlife-Consortium
Huss, Michael
Language: English
Title: Brain Sciences
Volume: 11
Issue: 2
Publisher/Platform: MDPI
Year of Publication: 2021
Free key words: electroencephalography (EEG)
data quality
attention-deficit/hyperactivity disorder (ADHD)
multicenter study
DDC notations: 610 Medicine and health
Publikation type: Journal Article
Abstract: Electroencephalography (EEG) represents a widely established method for assessing altered and typically developing brain function. However, systematic studies on EEG data quality, its correlates, and consequences are scarce. To address this research gap, the current study focused on the percentage of artifact-free segments after standard EEG pre-processing as a data quality index. We analyzed participant-related and methodological influences, and validity by replicating landmark EEG effects. Further, effects of data quality on spectral power analyses beyond participant-related characteristics were explored. EEG data from a multicenter ADHD-cohort (age range 6 to 45 years), and a non-ADHD school-age control group were analyzed (ntotal = 305). Resting-state data during eyes open, and eyes closed conditions, and task-related data during a cued Continuous Performance Task (CPT) were collected. After pre-processing, general linear models, and stepwise regression models were fitted to the data. We found that EEG data quality was strongly related to demographic characteristics, but not to methodological factors. We were able to replicate maturational, task, and ADHD effects reported in the EEG literature, establishing a link with EEG-landmark effects. Furthermore, we showed that poor data quality significantly increases spectral power beyond effects of maturation and symptom severity. Taken together, the current results indicate that with a careful design and systematic quality control, informative large-scale multicenter trials characterizing neurophysiological mechanisms in neurodevelopmental disorders across the lifespan are feasible. Nevertheless, results are restricted to the limitations reported. Future work will clarify predictive value.
DOI of the first publication: 10.3390/brainsci11020214
Link to this record: urn:nbn:de:bsz:291--ds-334474
ISSN: 2076-3425
Date of registration: 1-Mar-2021
Faculty: M - Medizinische Fakultät
Department: M - Forensische Psychologie und Psychiatrie
Professorship: M - Prof. Dr. Wolfgang Retz
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

Files for this record:
File Description SizeFormat 
brainsci-11-00214.pdf12,96 MBAdobe PDFView/Open

This item is licensed under a Creative Commons License Creative Commons