Use of Longitudinal EEG Measures in Estimating Language Development in Infants With and Without Familial Risk for Autism Spectrum Disorder

• Published in: Neurobiology of language 2020-01, Vol.1 (1), p.33-53
• Main Authors: Wilkinson, Carol L., Gabard-Durnam, Laurel J., Kapur, Kush, Tager-Flusberg, Helen, Levin, April R., Nelson, Charles A.
• Format: Article
• Language: English
• Subjects: Autism; autism spectrum disorder; biomarker; Brain; child; Children; Delayed language acquisition; EEG; Electroencephalography; electroencephalography (EEG); infant; Infants; Language; language development; Longitudinal studies; Native language acquisition; Risk groups; Siblings
• ISSN: 2641-4368; 2641-4368
• DOI: 10.1162/nol_a_00002

Language development in children with autism spectrum disorder (ASD) varies greatly among affected individuals and is a strong predictor of later outcomes. Younger siblings of children with ASD have increased risk of ASD, but also language delay. Identifying neural markers of language outcomes in infant siblings could facilitate earlier intervention and improved outcomes. This study aimed to determine whether electroencephalography (EEG) measures from the first 2 years of life can explain heterogeneity in language development in children at low and high risk for ASD, and whether associations between EEG measures and language development are different depending on ASD risk status or later ASD diagnosis. In this prospective longitudinal study, EEG measures collected between 3 and 24 months were used in a multivariate linear regression model to estimate participants’ 24-month language development. Individual baseline longitudinal EEG measures included (1) the slope of EEG power across 3 to 12 months or 3 to 24 months of life for six canonical frequency bands, (2) the estimated EEG power at 6 months of age for the same frequency bands, and (3) terms representing the interaction between ASD risk status and EEG power measures. Modeled 24-month language scores using EEG data from either the first 2 years (Pearson = 0.70, 95% CI [0.595, 0.783], = 1 × 10 ) or the first year of life (Pearson = 0.66, 95% CI [0.540, 0.761], = 2.5 × 10 ) were highly correlated with observed scores. All models included significant interaction effects of risk on EEG measures, suggesting that EEG-language associations are different depending on risk status, and that different brain mechanisms affect language development in low- versus high-risk infants.