Weinstein Sarah M, Tu Danni, Hu Fengling, Pan Ruyi, Zhang Rongqian, Vandekar Simon N, Baller Erica B, Gur Ruben C, Gur Raquel E, Alexander-Bloch Aaron F, Satterthwaite Theodore D, Park Jun Young
Department of Epidemiology and Biostatistics, Temple University College of Public Health, Philadelphia, PA, USA.
Regeneron Pharmaceuticals, Tarrytown, NY, USA.
bioRxiv. 2024 Jun 28:2024.06.26.600817. doi: 10.1101/2024.06.26.600817.
Within-individual coupling between measures of brain structure and function evolves in development and may underlie differential risk for neuropsychiatric disorders. Despite increasing interest in the development of structure-function relationships, rigorous methods to quantify and test individual differences in coupling remain nascent. In this article, we explore and address gaps in approaches for testing and spatially localizing individual differences in intermodal coupling. We propose a new method, called CIDeR, which is designed to simultaneously perform hypothesis testing in a way that limits false positive results and improve detection of true positive results. Through a comparison across different approaches to testing individual differences in intermodal coupling, we delineate subtle differences in the hypotheses they test, which may ultimately lead researchers to arrive at different results. Finally, we illustrate the utility of CIDeR in two applications to brain development using data from the Philadelphia Neurodevelopmental Cohort.
脑结构与功能测量之间的个体内耦合在发育过程中不断演变,可能是神经精神疾病不同风险的基础。尽管人们对结构 - 功能关系的发展越来越感兴趣,但用于量化和测试耦合中个体差异的严格方法仍处于起步阶段。在本文中,我们探讨并解决了测试和在空间上定位多模态耦合中个体差异的方法存在的差距。我们提出了一种名为CIDeR的新方法,该方法旨在以限制假阳性结果并提高真阳性结果检测率的方式同时进行假设检验。通过比较测试多模态耦合中个体差异的不同方法,我们描绘了它们所测试假设中的细微差异,这可能最终导致研究人员得出不同的结果。最后,我们使用费城神经发育队列的数据,在脑发育的两个应用中说明了CIDeR的实用性。