Ramduny Jivesh, Uddin Lucina Q, Vanderwal Tamara, Feczko Eric, Fair Damien A, Kelly Clare, Baskin-Sommers Arielle
Department of Psychology, Yale University, New Haven, Connecticut; Kavli Institute for Neuroscience, Yale University, New Haven, Connecticut.
Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, California; Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, California; Department of Psychology, University of California Los Angeles, Los Angeles, California.
Biol Psychiatry Cogn Neurosci Neuroimaging. 2025 Feb 5. doi: 10.1016/j.bpsc.2025.01.014.
Population neuroscience datasets provide an opportunity for researchers to estimate reproducible effect sizes for brain-behavior associations because of their large sample sizes. However, these datasets undergo strict quality control to mitigate sources of noise, such as head motion. This practice often excludes a disproportionate number of minoritized individuals.
We used motion-ordering and motion-ordering+resampling (bagging) to test whether these methods preserve functional magnetic resonance imaging (fMRI) data in the Adolescent Brain Cognitive Development (ABCD) Study (N = 5733). For the 2 methods, brain-behavior associations were computed as the partial Spearman's rank correlations (R) between functional connectivity and cognitive performance (NIH Cognition Toolbox) as well as externalizing and internalizing psychopathology (Child Behavior Checklist) while adjusting for participant sex assigned at birth and head motion.
Black and Hispanic youth exhibited excess head motion relative to data collected from White youth and were discarded disproportionately when conventional approaches were used. Motion-ordering and bagging methods retained more than 99% of Black and Hispanic youth. Both methods produced reproducible brain-behavior associations across low-/high-motion racial/ethnic groups based on motion-limited fMRI data.
The motion-ordering and bagging methods are 2 feasible approaches that can enhance sample representation for testing brain-behavior associations and that result in reproducible effect sizes in diverse populations.
群体神经科学数据集因其大样本量为研究人员提供了估计脑-行为关联的可重复效应大小的机会。然而，这些数据集要经过严格的质量控制以减少噪声源，如头部运动。这种做法往往会排除数量不成比例的少数群体个体。
我们使用运动排序和运动排序+重采样（装袋法）来测试这些方法是否能保留青少年大脑认知发展（ABCD）研究（N = 5733）中的功能磁共振成像（fMRI）数据。对于这两种方法，脑-行为关联被计算为功能连接与认知表现（美国国立卫生研究院认知工具箱）以及外化和内化精神病理学（儿童行为检查表）之间的偏斯皮尔曼等级相关性（R），同时对出生时指定的参与者性别和头部运动进行调整。
与从白人青年收集的数据相比，黑人和西班牙裔青年表现出过多的头部运动，并且在使用传统方法时被不成比例地排除。运动排序和装袋法保留了超过99%的黑人和西班牙裔青年。基于运动受限的fMRI数据，两种方法在低/高运动种族/族裔群体中都产生了可重复的脑-行为关联。
运动排序和装袋法是两种可行的方法，可以增强用于测试脑-行为关联的样本代表性，并在不同人群中产生可重复的效应大小。
