The Developmental Chronnecto-Genomics (Dev-CoG) study: A multimodal study on the developing brain
| Autor: | Elizabeth Heinrichs-Graham, Jingyu Liu, Yu-Ping Wang, I. Solis, Mackenzie S. Mills, Michaela R. Frenzel, Jacob A. Eastman, Christine M. Embury, M. Stern, Vince D. Calhoun, Andrew R. Mayer, Julia M. Stephen, Nathan M. Coolidge, Tony W. Wilson, Jacqueline R. Janowich |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Male
Time Factors Adolescent Cognitive Neuroscience Neurodevelopment Brain Structure and Function Neuroimaging Polymorphism Single Nucleotide 050105 experimental psychology Article lcsh:RC321-571 03 medical and health sciences 0302 clinical medicine Cog Child Development Cognition medicine Genetics Connectome Humans 0501 psychology and cognitive sciences Child lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry Data collection Resting state fMRI medicine.diagnostic_test Functional Neuroimaging 05 social sciences Brain Magnetoencephalography Genomics DNA Methylation Magnetic Resonance Imaging Adolescence Diffusion Magnetic Resonance Imaging Neurology Informatics FMRI Female Psychology 030217 neurology & neurosurgery Cognitive psychology MRI |
| Zdroj: | Neuroimage NeuroImage, Vol 225, Iss, Pp 117438-(2021) |
| ISSN: | 1095-9572 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect