The Mind Research Network a division of Lovelace Biomedical Research Institute, Albuquerque, NM, United States.
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.
Neuroimage. 2021 Jan 15;225:117438. doi: 10.1016/j.neuroimage.2020.117438. Epub 2020 Oct 8.
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.
大脑发育在很大程度上是通过对神经影像学数据的单模态分析来研究的，为结构和功能数据提供了独立的结果。然而，结构显然会影响功能，反之亦然，这表明需要进行多模态数据采集和分析，以提高我们对大脑发育的理解，并进一步为整个生命周期的典型和非典型大脑发育模型提供信息。最终，这些模型还应该包含大脑结构和功能背后的遗传和表观遗传机制，尽管目前这方面的描述还很不完善。为此，我们在这里报告了一个多地点、多模态数据集，该数据集涵盖了认知功能、大脑结构和功能以及遗传和表观遗传测量，以更好地量化影响儿童大脑发育的因素，这些儿童最初的年龄为 9-14 岁。发育性 Chronnecto-基因组学（Dev-CoG）研究（http://devcog.mrn.org/）的数据收集包括认知、情感和社会表现量表、结构和功能磁共振成像、弥散磁共振成像、脑磁图（MEG）以及唾液采集，用于分析单核苷酸多态性（SNP）和 DNA 甲基化模式的 DNA。在两个地点（思维研究所和内布拉斯加大学医学中心），共收集了 200 多名参与者的数据，这些儿童每年至少进行 3 年的重新测试。本文介绍了数据集的数据收集协议、样本人口统计学和数据质量措施。在研究结束时，该样本将通过协作信息学和神经影像学套件（COINS）数据库免费提供。
