ArticleResearch in autism spectrum disorders2019
EEG Data Collection in Children with ASD: The Role of State in Data Quality and Spectral Power.
Article in Research in autism spectrum disorders, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed, 52 citations in OpenAlex.
- Resting state aperiodic and periodic EEG activity in preschool-aged autistic children: differences from neurotypical peers and links to language skills.Molecular autism · 2026Article
- Autism spectrum disorder disrupts brain network connectivity maturation during childhood development.Scientific reports · 2025Article
- QEEG-Guided rTMS in Pediatric ASD with Contextual Evidence on Home-Based tDCS: Within-Cohort Reanalysis and Narrative Contextualization.Children (Basel, Switzerland) · 2025Article
- A protocol for measuring sleep at home in children with autism using EEG headbands.Research square · 2025Article
- Brain Complexity and Parametrization of Power Spectral Density in Children with Specific Language Impairment.Entropy (Basel, Switzerland) · 2025Article
- Remote EEG acquisition in Angelman syndrome using PANDABox-EEG.Journal of neurodevelopmental disorders · 2025Article
- Considerations and procedures for acquiring EEG as part of multi-site studies for Rett syndrome and other genetic neurodevelopmental disorders.Frontiers in integrative neuroscience · 2025Article
- RELAX-Jr: An Automated Pre-Processing Pipeline for Developmental EEG Recordings.Human brain mapping · 2024Article
- Conducting head-mounted eye-tracking research with young children with autism and children with increased likelihood of later autism diagnosis.Journal of neurodevelopmental disorders · 2024Article
- "Neural Noise" in Auditory Responses in Young Autistic and Neurotypical Children.Journal of autism and developmental disorders · 2024Article
- Behavioral and neural measures of infant responsivity increase with maternal multisensory input in non-irritable infants.Brain and behavior · 2023Article
- Linear and Non-linear Analyses of EEG in a Group of ASD Children During Resting State Condition.Brain topography · 2023Article
- Systematic Review on EEG Analysis to Diagnose and Treat Autism by Evaluating Functional Connectivity and Spectral Power.Neuropsychiatric disease and treatment · 2023Review
- Bridging the translational gap: what can synaptopathies tell us about autism?Frontiers in molecular neuroscience · 2023Review
- Dynamic Functional Connectivity of Emotion Processing in Beta Band with Naturalistic Emotion Stimuli.Brain sciences · 2022Article
- Independent evaluation of the harvard automated processing pipeline for Electroencephalography 1.0 using multi-site EEG data from children with Fragile X Syndrome.Journal of neuroscience methods · 2022Article
- The autism biomarkers consortium for clinical trials: evaluation of a battery of candidate eye-tracking biomarkers for use in autism clinical trials.Molecular autism · 2022Observational
- Workflow for health-related and brain data lifecycle.Frontiers in digital health · 2022Review
- The Synaptic Gene Study: Design and Methodology to Identify Neurocognitive Markers in Phelan-McDermid Syndrome andFrontiers in neuroscience · 2022Article
- A single-session behavioral protocol for successful event-related potential recording in children with neurodevelopmental disorders.Developmental psychobiology · 2021Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
backgroundElectroencephalography can elucidate neurobiological mechanisms underlying heterogeneity in ASD. Studying the full range of children with ASD introduces methodological challenges stemming from participants' difficulties tolerating the data collection process, leading to diminished EEGdataretentionandincreasedvariabilityin participant 'state' during the recording. Quantifying state will improve data collection methods and aide in interpreting results.
objectivesObservationally quantify participant state during the EEG recording; examine its relationship to child characteristics, data retention and spectral power.
methodsParticipants included 5-11 year-old children with D (N=39) and age-matched TD children (N=16). Participants were acclimated to the EEG environment using behavioral strategies. EEG was recorded while participants watched a video of bubbles. Participant 'state' was rated using a Likert scale (Perceived State Rating: PSR).
resultsParticipants with ASD had more elevated PSR than TD participants. Less EEG data were retained in participants with higher PSR scores, but this was not related to age or IQ. TD participants had higher alpha power compared with the ASD group. Within the ASD group, participants with high PSR had decreased frontal alpha power.
conclusionsGiven supportive strategies, EEG data was collected from children with ASD across cognitive levels. Participant state influenced both EEG data retention and alpha spectral power. Alpha suppression is linked to attention and vigilance, suggesting that these participants were less 'at rest'. This highlights the importance of considering state when conducting EEG studies with challenging participants, both to increase data retention rates and to quantify the influence of state on EEG variables.
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