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EEG-based biomarkers of language development in Down syndrome
Poster B23 in Poster Session B and Reception, Thursday, October 6, 6:30 - 8:30 pm EDT, Millennium Hall
McKena Geiger1, Megan Hartney1, Margaret Hojlo2, Anna Milliken2, Nicole Baumer2, Carol Wilkinson1; 1Labs of Cognitive Neuroscience, Developmental Medicine, Boston Children's Hospital, 2Down Syndrome Program, Developmental Medicine, Boston Children's Hospital
Introduction: Down syndrome (DS) is the most common cause of intellectual disability; yet little is known about the neurobiological pathways of cognitive and language impairments in DS. While there is well described characterization of language development in DS, the neurobiology underlying challenges in communication is unclear. There is a great need for brain-based biomarkers of language development in DS (1) for use as outcome measures within clinical trials and (2) to better our understanding of the neurobiology driving language delays. Given these language delays are likely initiated during early development, it is important to identify biomarkers in infants and young children with Down syndrome. As a low-cost, non-invasive measure of neural activity, electroencephalography (EEG) is a candidate tool to derive such biomarkers. Aims: (1) To characterize baseline EEG power spectra in children with DS compared to age-, and cognitive-matched comparison groups. (2) To identify neural markers of language development in DS. Design/Methods: Continuous resting state EEG from 26 boys and girls with DS (age 1-4 years) and respective age-matched (n=26) and cognitively-matched (n=26) comparison groups were successfully collected and analyzed. All participants completed the Mullen Scales of Early Learning (MSEL) as a measure of language ability. Power spectra were calculated using a multitaper spectral analysis and then further parametrized into aperiodic (1/f curve) and periodic components using FOOOF. Differences between groups were assessed using a Mann-Whitney U test. Associations between EEG measures and language were evaluated using Pearson Correlation and linear regression, with age as a covariate. Results: Participants with DS showed a significantly decreased aperiodic slope when compared to age-matched participants (p = 0.02), and significantly increased aperiodic gamma power compared to both age- and cognitive-matched comparison groups (p <0.01). After adjusting for age, the decreased aperiodic slope was significantly associated with better language (Adjusted R2= -0.51, p<0.005). Summary: Reduced aperiodic slope and associated increased aperiodic gamma power was observed in preschool aged children with DS. However, reduced aperiodic slope was also associated with better language development, suggesting the increased aperiodic slope may represent compensatory mechanisms.
Topic Areas: Disorders: Developmental, Language Genetics