A longitudinal resource for studying connectome development and its psychiatric associations during childhood

Russell H. Tobe, Anna MacKay-Brandt, Ryan Lim, Melissa Kramer, Melissa M. Breland, Lucia Tu, Yiwen Tian, Kristin Dietz Trautman, Caixia Hu, Raj Sangoi, Lindsay Alexander, Vilma Gabbay, F. Xavier Castellanos, Bennett L. Leventhal, R. Cameron Craddock, Stanley J. Colcombe, Alexandre R. Franco, Michael P. Milham

Research output: Contribution to journalArticlepeer-review

Abstract

Most psychiatric disorders are chronic, associated with high levels of disability and distress, and present during pediatric development. Scientific innovation increasingly allows researchers to probe brain-behavior relationships in the developing human. As a result, ambitions to (1) establish normative pediatric brain development trajectories akin to growth curves, (2) characterize reliable metrics for distinguishing illness, and (3) develop clinically useful tools to assist in the diagnosis and management of mental health and learning disorders have gained significant momentum. To this end, the NKI-Rockland Sample initiative was created to probe lifespan development as a large-scale multimodal dataset. The NKI-Rockland Sample Longitudinal Discovery of Brain Development Trajectories substudy (N = 369) is a 24- to 30-month multi-cohort longitudinal pediatric investigation (ages 6.0–17.0 at enrollment) carried out in a community-ascertained sample. Data include psychiatric diagnostic, medical, behavioral, and cognitive phenotyping, as well as multimodal brain imaging (resting fMRI, diffusion MRI, morphometric MRI, arterial spin labeling), genetics, and actigraphy. Herein, we present the rationale, design, and implementation of the Longitudinal Discovery of Brain Development Trajectories protocol.

Original languageEnglish (US)
Article number300
JournalScientific Data
Volume9
Issue number1
DOIs
StatePublished - Dec 2022

ASJC Scopus subject areas

  • Statistics and Probability
  • Information Systems
  • Education
  • Computer Science Applications
  • Statistics, Probability and Uncertainty
  • Library and Information Sciences

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