Mapping individual differences in intermodal coupling in neurodevelopment.

Imaging neuroscience (Cambridge, Mass.) Pub Date : 2025-09-22 eCollection Date: 2025-01-01 DOI:10.1162/IMAG.a.156
Ruyi Pan, Sarah M Weinstein, Danni Tu, Fengling Hu, Büşra Tanrıverdi, Rongqian Zhang, Simon N Vandekar, Erica B Baller, Ruben C Gur, Raquel E Gur, Aaron F Alexander-Bloch, Theodore D Satterthwaite, Jun Young Park
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Abstract

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, including a new method, called CEIDR (Cluster Enhancement for testing Individual Differences in ρ (r)). CEIDR controls false positives in individual differences in intermodal correlations that arise from mean and variance heterogeneity and improves statistical power by adopting adaptive cluster enhancement. 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 these differences in two applications to brain development using data from the Philadelphia Neurodevelopmental Cohort.

绘制神经发育中多模态耦合的个体差异。
个体内大脑结构和功能在发育过程中演变的测量之间的耦合,可能是神经精神疾病差异风险的基础。尽管人们对结构-功能关系的发展越来越感兴趣,但量化和测试耦合个体差异的严格方法仍处于萌芽阶段。在本文中,我们探索并解决了在多式联运耦合中测试和空间定位个体差异方法中的差距,包括一种名为CEIDR(用于测试ρ (r)个体差异的聚类增强)的新方法。CEIDR控制了由均值和方差异质性引起的多式联运相关性个体差异的假阳性,并通过采用自适应聚类增强提高了统计能力。通过对测试多式联运耦合中个体差异的不同方法的比较,我们描述了他们所测试的假设的细微差异,这可能最终导致研究人员得出不同的结果。最后,我们用费城神经发育队列的数据说明了两种应用在大脑发育方面的差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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