Modeling Developmental Change: Practical Integration of Advanced Neuroimaging and Statistical Methods

发育变化建模：先进神经影像和统计方法的实际整合

• 批准号: 1736406
• 负责人: Michelle Byrne
• 金额: $ 1.99万
• 依托单位: University of Oregon Eugene
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-06-01 至 2018-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1736406&HistoricalAwards=false
• 关键词: Modeling; Developmental; Change; Practical; Integration

Neuroimaging techniques, including structural and functional magnetic resonance imaging (MRI), have allowed researchers to investigate the neural bases of developmental changes in cognition. In recent years, it has become more common for researchers to obtain multiple measures of the same individual across development. These longitudinal MRI datasets require special consideration for processing and analysis, yet the field as a whole has not standardized best practices for these datasets, which could be one reason why it is difficult to replicate results across laboratories and research studies. A two-day workshop will be open to 60 developmental neuroimaging researchers and will teach best practices for processing, analyzing, modeling, and interpreting longitudinal neuroimaging data. This will help researchers conduct robust and consistent research on how the brain and cognition change across development. Importantly, this workshop will fund at least nine students or trainees who are planning to, or are directly working with, longitudinal neuroimaging data, providing strong practical skills for emerging research scientists in the field of developmental cognitive neuroscience. It is both timely and vital to hold a workshop for researchers in the field of developmental cognitive neuroscience to examine differences in longitudinal modeling, statistical processing and analysis, and interpretation. Recent work has uncovered how methodological differences may be adversely affecting replicability in the field of neuroimaging, and there is an increasing drive to validate the processing and statistical techniques that are employed in neuroimaging research. There has also been increasing support for standardization of techniques and reporting criteria, such as the recent Brain Imaging Data Structure (BIDS) protocol for organizing and describing MRI datasets. The overarching aim of this workshop is to teach best practice guidelines for processing, analyzing, modeling, and interpreting longitudinal structural and functional neuroimaging data, which will inform our knowledge of how the brain and cognition change across development. It will address additional statistical concerns specific to longitudinal neuroimaging that also need validation, and consider standardization of techniques and reporting criteria that will improve the comparability of findings. The main outcome of this workshop will be that researchers leave with answers to questions about processing longitudinal functional and structural MRI data and the correct tools to move forward with research in developmental cognitive neuroscience. This type of work has the potential to answer fundamental questions about neural plasticity and sensitive periods of cognitive development through observing neural changes during learning. It is also inherently related to the fields of developmental affective, social, and clinical neuroscience, and therefore has the potential to translate directly to the prevention and treatment of emerging psychopathology. This workshop will push the field of developmental cognitive neuroscience forward to develop robust and precise models that have strong translational applications for public policy.

神经成像技术，包括结构和功能磁共振成像（MRI），使研究人员能够研究认知发育变化的神经基础。近年来，研究人员在整个发展过程中获得同一个体的多种测量方法变得越来越普遍。这些纵向MRI数据集在处理和分析时需要特别考虑，但整个领域尚未对这些数据集进行标准化的最佳实践，这可能是难以在实验室和研究中复制结果的原因之一。为期两天的研讨会将向60名发育神经影像学研究人员开放，并将教授处理，分析，建模和解释纵向神经影像学数据的最佳实践。这将有助于研究人员对大脑和认知如何在发展过程中发生变化进行强有力和一致的研究。重要的是，本次研讨会将资助至少9名正在计划或直接从事纵向神经影像学数据研究的学生或学员，为发展认知神经科学领域的新兴研究科学家提供强大的实用技能。为发展认知神经科学领域的研究人员举办一个研讨会来研究纵向建模、统计处理和分析以及解释方面的差异是及时而重要的。最近的工作揭示了方法差异如何对神经成像领域的可重复性产生不利影响，并且越来越多的人希望验证神经成像研究中使用的处理和统计技术。技术和报告标准的标准化也得到了越来越多的支持，例如最近用于组织和描述MRI数据集的脑成像数据结构（BIDS）协议。本次研讨会的首要目标是教授处理、分析、建模和解释纵向结构和功能神经成像数据的最佳实践指南，这将告知我们大脑和认知如何在发展过程中变化的知识。它将解决纵向神经成像的额外统计问题，这些问题也需要验证，并考虑技术和报告标准的标准化，这将提高结果的可比性。本次研讨会的主要成果是，研究人员将带着关于处理纵向功能和结构MRI数据的问题的答案和正确的工具离开，以推进发展认知神经科学的研究。这种类型的工作有可能通过观察学习过程中的神经变化来回答有关神经可塑性和认知发展敏感期的基本问题。它也与发育情感、社会和临床神经科学领域有着内在的联系，因此有可能直接转化为新出现的精神病理学的预防和治疗。本次研讨会将推动发展认知神经科学领域向前发展，以开发具有强大的公共政策转化应用的稳健和精确的模型。