EEG data quality: determinants and impact in a multicenter study of children, adolescents, and adults with attention-deficit/hyperactivity disorder (ADHD)

  • 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.

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Author:Anna Kaiser, Pascal AggensteinerORCiDGND, Martin HoltmannORCiDGND, Andreas FallgatterORCiD, Marcel RomanosORCiDGND, Karina AbenovaGND, Barbara Alm, Katja BeckerORCiD, Manfred DöpfnerORCiDGND, Thomas Ethofer, Christine M. FreitagORCiDGND, Julia Geissler, Johannes Hebebrand, Michael Huss, Thomas Jans, Lea Teresa Jendreizik, Johanna Ketter, Tanja LegenbauerORCiDGND, Alexandra PhilipsenORCiDGND, Luise PoustkaORCiDGND, Tobias Renner, Wolfgang Retz, Michael Rösler, Johannes Thome, Henrik Uebel-von Sandersleben, Elena von Wirth, Toivo Zinnow, Sarah HohmannORCiDGND, Sabina MillenetORCiDGND, Nathalie E. HolzORCiDGND, Tobias BanaschewskiORCiDGND, Daniel BrandeisGND
Parent Title (English):Brain Sciences
Publisher:MDPI AG
Place of publication:Basel
Document Type:Article
Date of Publication (online):2021/02/10
Date of first Publication:2021/02/10
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Contributing Corporation:ESCAlife-Consortium
Release Date:2021/11/03
Tag:artifacts; attention-deficit/hyperactivity disorder (ADHD); data quality; electroencephalography (EEG); multicenter study
Issue:2, art. 214
Page Number:36
First Page:1
Last Page:36
The current work was supported by the research consortium on ADHD, ESCA-Life, funded by the German Federal Ministry of Education and Research (FKZ 01EE1408E).
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Licence (German):License LogoCreative Commons - Namensnennung 4.0