EEG/ERP as a pragmatic method to expand the reach of infant-toddler neuroimaging in HBCD: Promises and challenges

Elizabeth S. Norton, Leigha A. MacNeill, Emily M. Harriott, Norrina Allen, Sheila Krogh-Jespersen, Christopher D. Smyser, Cynthia E. Rogers, Tara A. Smyser, Joan Luby, Lauren Wakschlag

Research output: Contribution to journalReview articlepeer-review

12 Scopus citations


Though electrophysiological measures (EEG and ERP) offer complementary information to MRI and a variety of advantages for studying infants and young children, these measures have not yet been included in large cohort studies of neurodevelopment. This review summarizes the types of EEG and ERP measures that could be used in the HEALthy Brain and Cognitive Development (HBCD) study, and the promises and challenges in doing so. First, we provide brief overview of the use of EEG/ERP for studying the developing brain and discuss exemplar findings, using resting or baseline EEG measures as well as the ERP mismatch negativity (MMN) as exemplars. We then discuss the promises of EEG/ERP such as feasibility, while balancing challenges such as ensuring good signal quality in diverse children with different hair types. We then describe an ongoing multi-site EEG data harmonization from our groups. We discuss the process of alignment and provide preliminary usability data for both resting state EEG data and auditory ERP MMN in diverse samples including over 300 infants and toddlers. Finally, we provide recommendations and considerations for the HBCD study and other studies of neurodevelopment.

Original languageEnglish
Article number100988
JournalDevelopmental Cognitive Neuroscience
StatePublished - Oct 2021


  • EEG
  • ERP
  • HBCD
  • Mismatch negativity
  • Neurodevelopment


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