Dataset Information

EEG-IP: an international infant EEG data integration platform for the study of risk and resilience in autism and related conditions.

ABSTRACT: BACKGROUND:Establishing 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. METHODS:EEG-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. RESULTS:First, 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. CONCLUSIONS:Implementing 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.

SUBMITTER: van Noordt S

PROVIDER: S-EPMC7203847 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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EEG-IP: an international infant EEG data integration platform for the study of risk and resilience in autism and related conditions.

van Noordt Stefon S Desjardins James A JA Huberty Scott S Abou-Abbas Lina L Webb Sara Jane SJ Levin April R AR Segalowitz Sidney J SJ Evans Alan C AC Elsabbagh Mayada M

Molecular medicine (Cambridge, Mass.) 20200507 1

<h4>Background</h4>Establishing 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.<h4>Methods</h4>EEG-IP is an International Infant EEG Data Integration Platform developed to advance biomarker discovery by enhancing the larg ...[more]

PMID: 32380941

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Project description:UnlabelledBackgroundAutism Spectrum Conditions (ASC) are a set of pervasive neurodevelopmental conditions characterized by a wide range of lifelong signs and symptoms. Recent explanatory models of autism propose abnormal neural connectivity and are supported by studies showing decreased interhemispheric coherence in individuals with ASC. The first aim of this study was to test the hypothesis of reduced interhemispheric coherence in ASC, and secondly to investigate specific effects of task performance on interhemispheric coherence in ASC.MethodsWe analyzed electroencephalography (EEG) data from 15 participants with ASC and 15 typical controls, using Wavelet Transform Coherence (WTC) to calculate interhemispheric coherence during face and chair matching tasks, for EEG frequencies from 5 to 40 Hz and during the first 400 ms post-stimulus onset.ResultsResults demonstrate a reduction of interhemispheric coherence in the ASC group, relative to the control group, in both tasks and for all electrode pairs studied. For both tasks, group differences were generally observed after around 150 ms and at frequencies lower than 13 Hz. Regarding within-group task comparisons, while the control group presented differences in interhemispheric coherence between faces and chairs tasks at various electrode pairs (FT7-FT8, TP7-TP8, P7-P8), such differences were only seen for one electrode pair in the ASC group (T7-T8). No significant differences in EEG power spectra were observed between groups.ConclusionsInterhemispheric coherence is reduced in people with ASC, in a time and frequency specific manner, during visual perception and categorization of both social and inanimate stimuli and this reduction in coherence is widely dispersed across the brain.Results of within-group task comparisons may reflect an impairment in task differentiation in people with ASC relative to typically developing individuals.Overall, the results of this research support the value of WTC in examining the time-frequency microstructure of task-related interhemispheric EEG coherence in people with ASC.

Dataset Information

EEG-IP: an international infant EEG data integration platform for the study of risk and resilience in autism and related conditions.

Publications

EEG-IP: an international infant EEG data integration platform for the study of risk and resilience in autism and related conditions.

Similar Datasets

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