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Sci Data. 2017 Dec 19;4:170181. doi: 10.1038/sdata.2017.181.

An open resource for transdiagnostic research in pediatric mental health and learning disorders.

Scientific data

Lindsay M Alexander, Jasmine Escalera, Lei Ai, Charissa Andreotti, Karina Febre, Alexander Mangone, Natan Vega-Potler, Nicolas Langer, Alexis Alexander, Meagan Kovacs, Shannon Litke, Bridget O'Hagan, Jennifer Andersen, Batya Bronstein, Anastasia Bui, Marijayne Bushey, Henry Butler, Victoria Castagna, Nicolas Camacho, Elisha Chan, Danielle Citera, Jon Clucas, Samantha Cohen, Sarah Dufek, Megan Eaves, Brian Fradera, Judith Gardner, Natalie Grant-Villegas, Gabriella Green, Camille Gregory, Emily Hart, Shana Harris, Megan Horton, Danielle Kahn, Katherine Kabotyanski, Bernard Karmel, Simon P Kelly, Kayla Kleinman, Bonhwang Koo, Eliza Kramer, Elizabeth Lennon, Catherine Lord, Ginny Mantello, Amy Margolis, Kathleen R Merikangas, Judith Milham, Giuseppe Minniti, Rebecca Neuhaus, Alexandra Levine, Yael Osman, Lucas C Parra, Ken R Pugh, Amy Racanello, Anita Restrepo, Tian Saltzman, Batya Septimus, Russell Tobe, Rachel Waltz, Anna Williams, Anna Yeo, Francisco X Castellanos, Arno Klein, Tomas Paus, Bennett L Leventhal, R Cameron Craddock, Harold S Koplewicz, Michael P Milham

Affiliations

  1. Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA.
  2. Universität Zürich, Zürich 8006, Switzerland.
  3. City University of New York, NY 10031, USA.
  4. Center for Autism and the Developing Brain, Weill Cornell Medicine, New York-Presbyterian, White Plains, NY 10605, USA.
  5. New York State Institute for Basic Research in Developmental Disabilities, Staten Island, NY 10314, USA.
  6. Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
  7. School of Electrical and Electronic Engineering, University College Dublin, Dublin D4, Ireland.
  8. Office of Staten Island Borough President, Staten Island, NY 10301, USA.
  9. Columbia University Medical Center, New York, NY 10032, USA.
  10. Genetic Epidemiology Research Branch, Intramural Research Program, National Institute of Mental Health, Bethesda, MD 20892, USA.
  11. Mercy College, Dobbs Ferry, NY 10522, USA.
  12. Yale University, New Haven, CT 06520, USA.
  13. Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA.
  14. Division of Child and Adolescent Psychiatric Research, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA.
  15. Department of Child and Adolescent Psychiatry, NYU Langone Health, New York, NY 10016, USA.
  16. Rotman Research Institute, Baycrest, Toronto M6A 2E1, Canada.
  17. Departments of Psychology and Psychiatry, University of Toronto, Toronto M5S, Canada.
  18. University of California, San Francisco, San Francisco, CA 94143, USA.

PMID: 29257126 PMCID: PMC5735921 DOI: 10.1038/sdata.2017.181

Abstract

Technological and methodological innovations are equipping researchers with unprecedented capabilities for detecting and characterizing pathologic processes in the developing human brain. As a result, ambitions to achieve clinically useful tools to assist in the diagnosis and management of mental health and learning disorders are gaining momentum. To this end, it is critical to accrue large-scale multimodal datasets that capture a broad range of commonly encountered clinical psychopathology. The Child Mind Institute has launched the Healthy Brain Network (HBN), an ongoing initiative focused on creating and sharing a biobank of data from 10,000 New York area participants (ages 5-21). The HBN Biobank houses data about psychiatric, behavioral, cognitive, and lifestyle phenotypes, as well as multimodal brain imaging (resting and naturalistic viewing fMRI, diffusion MRI, morphometric MRI), electroencephalography, eye-tracking, voice and video recordings, genetics and actigraphy. Here, we present the rationale, design and implementation of HBN protocols. We describe the first data release (n=664) and the potential of the biobank to advance related areas (e.g., biophysical modeling, voice analysis).

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