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The Developmental Chronnecto-Genomics (Dev-CoG) study: A multimodal study on the developing brain
J M Stephen1, I Solis2, J Janowich2
1The Mind Research Network a division of Lovelace Biomedical Research Institute, Albuquerque, NM, United States.
This study introduces a multimodal dataset for tracking child brain development, integrating brain imaging, cognitive, and genetic data to understand influencing factors. The data will be publicly available to advance developmental neuroscience research.
Area of Science:
- Neuroscience
- Developmental Psychology
- Genetics
Background:
- Traditional brain development studies often use unimodal neuroimaging, limiting understanding of structure-function relationships.
- Integrating structural and functional brain data is crucial for accurate models of typical and atypical development.
- Incorporating genetic and epigenetic factors is essential but currently under-specified in developmental models.
Purpose of the Study:
- To present a novel multi-site, multimodal dataset (Developmental Chronnecto-Genomics, Dev-CoG) for studying child brain development.
- To capture comprehensive data including cognitive, emotional, social, structural, functional, and genetic measures.
- To facilitate research into the factors influencing brain development from childhood through adolescence.
Main Methods:
- Collected data from over 200 children (aged 9-14 years) across two sites, with annual re-testing for at least 3 years.
- Utilized structural MRI, functional MRI, diffusion MRI, magnetoencephalography (MEG), cognitive/emotional/social scales, and saliva for genetic analysis (SNPs, DNA methylation).
- Ensured data quality and documented protocols, with plans for public data release via the COINS database.
Main Results:
- The Dev-CoG study successfully collected a rich, longitudinal, multimodal dataset on child brain development.
- Detailed protocols, demographics, and quality control measures for the dataset are presented.
- The dataset encompasses a wide range of measures crucial for understanding brain development.
Conclusions:
- The Dev-CoG dataset provides a valuable resource for investigating the interplay of structure, function, and genetics in brain development.
- Availability of this data will foster advanced research into typical and atypical developmental trajectories.
- Future research can leverage this resource to build more comprehensive models of human brain development across the lifespan.
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