ArticleMolecular medicine (Cambridge, Mass.)2020
EEG-IP: an international infant EEG data integration platform for the study of risk and resilience in autism and related conditions.
Article in Molecular medicine (Cambridge, Mass.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Decreased variability of small-world propensity during non-response tasks in schizophrenia.Neuroimage. Reports · 2026Article
- Comprehensive methodology for sample enrichment in EEG biomarker studies for Alzheimer's risk classification.PloS one · 2026Article
- Sex differences in early brain development in a multi-site ASD likelihood cohort.Frontiers in computational neuroscience · 2026Article
- The Development of Lateralized Brain Oscillations in Infants: Lessons From Autism.Developmental psychobiology · 2025Article
- Eye-movement artifact correction in infant EEG: A systematic comparison between ICA and Artifact Blocking.Journal of neuroscience methods · 2025Article
- Behavioral and neural responses to social exclusion in women: the role of facial attractiveness and friendliness.Scientific reports · 2024Article
- EEG Biomarkers for Autism: Rational, Support, and the Qualification Process.Advances in neurobiology · 2024Review
- Dementia ConnEEGtome: Towards multicentric harmonization of EEG connectivity in neurodegeneration.International journal of psychophysiology : official journal of the International Organization of Psychophysiology · 2022Review
- Brain Network for Exploring the Change of Brain Neurotransmitter 5-Hydroxytryptamine of Autism Children by Resting-State EEG.Computational and mathematical methods in medicine · 2022Article
- Association between spectral electroencephalography power and autism risk and diagnosis in early development.Autism research : official journal of the International Society for Autism Research · 2021Article
- 12-Month peak alpha frequency is a correlate but not a longitudinal predictor of non-verbal cognitive abilities in infants at low and high risk for autism spectrum disorder.Developmental cognitive neuroscience · 2021Article
- Use of Empirical Mode Decomposition in ERP Analysis to Classify Familial Risk and Diagnostic Outcomes for Autism Spectrum Disorder.Brain sciences · 2021Article
- Structural templates for imaging EEG cortical sources in infants.NeuroImage · 2021Article
- Neural mechanisms of language development in infancy.Infancy : the official journal of the International Society on Infant StudiesArticle
Corrections and comments
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Authors and funding
9 authors.
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Abstract
backgroundEstablishing reliable predictive and diganostic biomarkers of autism would enhance early identification and facilitate targeted intervention during periods of greatest plasticity in early brain development. High impact research on biomarkers is currently limited by relatively small sample sizes and the complexity of the autism phenotype.
methodsEEG-IP is an International Infant EEG Data Integration Platform developed to advance biomarker discovery by enhancing the large scale integration of multi-site data. Currently, this is the largest multi-site standardized dataset of infant EEG data.
resultsFirst, multi-site data from longitudinal cohort studies of infants at risk for autism was pooled in a common repository with 1382 EEG longitudinal recordings, linked behavioral data, from 432 infants between 3- to 36-months of age. Second, to address challenges of limited comparability across independent recordings, EEG-IP applied the Brain Imaging Data Structure (BIDS)-EEG standard, resulting in a harmonized, extendable, and integrated data state. Finally, the pooled and harmonized raw data was preprocessed using a common signal processing pipeline that maximizes signal isolation and minimizes data reduction. With EEG-IP, we produced a fully standardized data set, of the pooled, harmonized, and pre-processed EEG data from multiple sites.
conclusionsImplementing these integrated solutions for the first time with infant data has demonstrated success and challenges in generating a standardized multi-site data state. The challenges relate to annotation of signal sources, time, and ICA analysis during pre-processing. A number of future opportunities also emerge, including validation of analytic pipelines that can replicate existing findings and/or test novel hypotheses.
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