Relationships between variance in electroencephalography relative power and developmental status in infants with typical development and at risk for developmental disability: An observational study.

Journal Article (Journal Article)

Background: Electroencephalography (EEG) is a non-invasive tool that has the potential to identify and quantify atypical brain development. We introduce a new measure here, variance of relative power of resting-state EEG. We sought to assess whether variance of relative power of resting-state EEG could predict i) classification of infants as typical development (TD) or at risk (AR) for developmental disability, and ii) Bayley developmental scores at the same visit or future visits. Methods: A total of 22 infants with TD participated, aged between 38 and 203 days. In addition, 11 infants broadly at risk participated (6 high-risk pre-term, 4 low-risk pre-term, 1 high-risk full-term), aged between 40 and 225 days of age (adjusted for prematurity). We used EEG to measure resting-state brain function across months. We calculated variance of relative power as the standard deviation of the relative power across each of the 32 EEG electrodes. The Bayley Scales of Infant Development (3 rd edition) was used to measure developmental level. Infants were measured 1-6 times each, with 1 month between measurements. Results: Our main findings were: i) variance of relative power of resting state EEG can predict classification of infants as TD or AR, and ii) variance of relative power of resting state EEG can predict Bayley developmental scores at the same visit (Bayley raw fine motor, Bayley raw cognitive, Bayley total raw score, Bayley motor composite score) and at a future visit (Bayley raw fine motor). Conclusions: This was a preliminary, exploratory, small study. Our results support variance of relative power of resting state EEG as an area of interest for future study as a biomarker of neurodevelopmental status and as a potential outcome measure for early intervention.

Full Text

Duke Authors

Cited Authors

  • Hooyman, A; Kayekjian, D; Xiao, R; Jiang, C; Vanderbilt, DL; Smith, BA

Published Date

  • January 2018

Published In

Volume / Issue

  • 2 /

Start / End Page

  • 47 -

PubMed ID

  • 30569037

Pubmed Central ID

  • PMC6266744

Electronic International Standard Serial Number (EISSN)

  • 2572-4754

International Standard Serial Number (ISSN)

  • 2572-4754

Digital Object Identifier (DOI)

  • 10.12688/gatesopenres.12868.2

Language

  • eng