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doi:10.22028/D291-33447
Titel: | EEG Data Quality: Determinants and Impact in a Multicenter Study of Children, Adolescents, and Adults with Attention-Deficit/Hyperactivity Disorder (ADHD) |
VerfasserIn: | 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 |
Sprache: | Englisch |
Titel: | Brain Sciences |
Bandnummer: | 11 |
Heft: | 2 |
Verlag/Plattform: | MDPI |
Erscheinungsjahr: | 2021 |
Freie Schlagwörter: | electroencephalography (EEG) data quality attention-deficit/hyperactivity disorder (ADHD) artifacts multicenter study |
DDC-Sachgruppe: | 610 Medizin, Gesundheit |
Dokumenttyp: | Journalartikel / Zeitschriftenartikel |
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 der Erstveröffentlichung: | 10.3390/brainsci11020214 |
Link zu diesem Datensatz: | urn:nbn:de:bsz:291--ds-334474 hdl:20.500.11880/30753 http://dx.doi.org/10.22028/D291-33447 |
ISSN: | 2076-3425 |
Datum des Eintrags: | 1-Mär-2021 |
Fakultät: | M - Medizinische Fakultät |
Fachrichtung: | M - Forensische Psychologie und Psychiatrie |
Professur: | M - Prof. Dr. Wolfgang Retz |
Sammlung: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
Dateien zu diesem Datensatz:
Datei | Beschreibung | Größe | Format | |
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brainsci-11-00214.pdf | 12,96 MB | Adobe PDF | Öffnen/Anzeigen |
Diese Ressource wurde unter folgender Copyright-Bestimmung veröffentlicht: Lizenz von Creative Commons