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Stephen JM, Solis I, Janowich J, Stern M, Frenzel MR, Eastman JA, Mills MS, Embury CM, Coolidge NM, Heinrichs-Graham E, Mayer A, Liu J, Wang YP, Wilson TW, Calhoun VD. The Developmental Chronnecto-Genomics (Dev-CoG) study: A multimodal study on the developing brain. Neuroimage 2020; 225:117438. [PMID: 33039623 DOI: 10.1016/j.neuroimage.2020.117438] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Revised: 08/07/2020] [Accepted: 10/05/2020] [Indexed: 01/10/2023] Open
Abstract
Brain development has largely been studied through unimodal analysis of neuroimaging data, providing independent results for structural and functional data. However, structure clearly impacts function and vice versa, pointing to the need for performing multimodal data collection and analysis to improve our understanding of brain development, and to further inform models of typical and atypical brain development across the lifespan. Ultimately, such models should also incorporate genetic and epigenetic mechanisms underlying brain structure and function, although currently this area is poorly specified. To this end, we are reporting here a multi-site, multi-modal dataset that captures cognitive function, brain structure and function, and genetic and epigenetic measures to better quantify the factors that influence brain development in children originally aged 9-14 years. Data collection for the Developmental Chronnecto-Genomics (Dev-CoG) study (http://devcog.mrn.org/) includes cognitive, emotional, and social performance scales, structural and functional MRI, diffusion MRI, magnetoencephalography (MEG), and saliva collection for DNA analysis of single nucleotide polymorphisms (SNPs) and DNA methylation patterns. Across two sites (The Mind Research Network and the University of Nebraska Medical Center), data from over 200 participants were collected and these children were re-tested annually for at least 3 years. The data collection protocol, sample demographics, and data quality measures for the dataset are presented here. The sample will be made freely available through the collaborative informatics and neuroimaging suite (COINS) database at the conclusion of the study.
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Affiliation(s)
- J M Stephen
- The Mind Research Network a division of Lovelace Biomedical Research Institute, Albuquerque, NM, United States.
| | - I Solis
- The Mind Research Network a division of Lovelace Biomedical Research Institute, Albuquerque, NM, United States; Department of Psychology, University of New Mexico, Albuquerque, NM, United States
| | - J Janowich
- The Mind Research Network a division of Lovelace Biomedical Research Institute, Albuquerque, NM, United States; Department of Psychology, University of New Mexico, Albuquerque, NM, United States
| | - M Stern
- The Mind Research Network a division of Lovelace Biomedical Research Institute, Albuquerque, NM, United States; Department of Psychology, University of New Mexico, Albuquerque, NM, United States
| | - M R Frenzel
- University of Nebraska Medical Center, Omaha, NE, United States
| | - J A Eastman
- University of Nebraska Medical Center, Omaha, NE, United States
| | - M S Mills
- University of Nebraska Medical Center, Omaha, NE, United States
| | - C M Embury
- University of Nebraska Medical Center, Omaha, NE, United States
| | - N M Coolidge
- University of Nebraska Medical Center, Omaha, NE, United States
| | | | - A Mayer
- The Mind Research Network a division of Lovelace Biomedical Research Institute, Albuquerque, NM, United States
| | - J Liu
- The Mind Research Network a division of Lovelace Biomedical Research Institute, Albuquerque, NM, United States
| | - Y P Wang
- Tulane University, New Orleans, LA, United States
| | - T W Wilson
- University of Nebraska Medical Center, Omaha, NE, United States
| | - V D Calhoun
- The Mind Research Network a division of Lovelace Biomedical Research Institute, Albuquerque, NM, United States; Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, United States; Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
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