Multi-site EEG studies in early infancy: Methods to enhance data quality

Abigail Dickinson; Madison Booth; Manjari Daniel; Alana Campbell; Neely Miller; Bonnie Lau; John Zempel; Sara Jane Webb; Jed Elison; Adrian K.C. Lee; Annette Estes; Stephen Dager; Heather Hazlett; Jason Wolff; Robert Schultz; Natasha Marrus; Alan Evans; Joseph Piven; John R. Pruett, Jr.; Shafali Jeste

Developmental Cognitive Neuroscience (Oct 2024)

Multi-site EEG studies in early infancy: Methods to enhance data quality

Abigail Dickinson,
Madison Booth,
Manjari Daniel,
Alana Campbell,
Neely Miller,
Bonnie Lau,
John Zempel,
Sara Jane Webb,
Jed Elison,
Adrian K.C. Lee,
Annette Estes,
Stephen Dager,
Heather Hazlett,
Jason Wolff,
Robert Schultz,
Natasha Marrus,
Alan Evans,
Joseph Piven,
John R. Pruett, Jr.,
Shafali Jeste

Affiliations

Abigail Dickinson: Center for Autism Research and Treatment, Semel Institute for Neuroscience, University of California, Los Angeles, CA, USA; Correspondence to: Center for Autism Research and Treatment, Semel Institute for Neuroscience, University of California, 760 Westwood Plaza, Suite A7-469, Los Angeles, CA 90095, USA.
Madison Booth: Department of Neurology, Children’s Hospital of Los Angeles, Los Angeles, CA, USA
Manjari Daniel: Center for Autism Research and Treatment, Semel Institute for Neuroscience, University of California, Los Angeles, CA, USA
Alana Campbell: Carolina Institute for Developmental Disabilities, Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Neely Miller: Center for Neurobehavioral Development, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
Bonnie Lau: Department of Otolaryngology – Head and Neck Surgery, University of Washington, Seattle, WA, USA
John Zempel: Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
Sara Jane Webb: Center for Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA, USA
Jed Elison: Institute of Child Development, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
Adrian K.C. Lee: Department of Speech and Hearing Sciences, Institute for Learning and Brain Sciences, University of Washington, Seattle, WA, USA
Annette Estes: Department of Speech and Hearing Sciences, Institute for Learning and Brain Sciences, University of Washington, Seattle, WA, USA
Stephen Dager: Department of Radiology, University of Washington, Seattle, WA, USA
Heather Hazlett: Carolina Institute for Developmental Disabilities, Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
Jason Wolff: Center for Neurobehavioral Development, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
Robert Schultz: Center for Autism Research, Children’s Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
Natasha Marrus: Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
Alan Evans: McGill Centre for Integrative Neuroscience, Montreal Neurological Institute, McGill University, Montréal, QC, Canada
Joseph Piven: Carolina Institute for Developmental Disabilities, Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
John R. Pruett, Jr.: Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
Shafali Jeste: Department of Neurology, Children’s Hospital of Los Angeles, Los Angeles, CA, USA; Department of Pediatrics and Neurology, University of Southern California, Los Angeles, CA, USA

Journal volume & issue: Vol. 69
p. 101425

Abstract

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Brain differences linked to autism spectrum disorder (ASD) can manifest before observable symptoms. Studying these early neural precursors in larger and more diverse cohorts is crucial for advancing our understanding of developmental pathways and potentially facilitating earlier identification. EEG is an ideal tool for investigating early neural differences in ASD, given its scalability and high tolerability in infant populations. In this context, we integrated EEG into an existing multi-site MRI study of infants with a higher familial likelihood of developing ASD. This paper describes the comprehensive protocol established to collect longitudinal, high-density EEG data from infants across five sites as part of the Infant Brain Imaging Study (IBIS) Network and reports interim feasibility and data quality results. We evaluated feasibility by measuring the percentage of infants from whom we successfully collected each EEG paradigm. The quality of task-free data was assessed based on the duration of EEG recordings remaining after artifact removal. Preliminary analyses revealed low data loss, with average in-session loss rates at 4.16 % and quality control loss rates at 11.66 %. Overall, the task-free data retention rate, accounting for both in-session issues and quality control, was 84.16 %, with high consistency across sites. The insights gained from this preliminary analysis highlight key sources of data attrition and provide practical considerations to guide similar research endeavors.

Published in Developmental Cognitive Neuroscience

ISSN: 1878-9293 (Print); 1878-9307 (Online)
Publisher: Elsevier
Country of publisher: Netherlands
LCC subjects: Science: Physiology: Neurophysiology and neuropsychology
Website: http://www.journals.elsevier.com/developmental-cognitive-neuroscience/

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