Big Data-Driven Brain Parcellation from fMRI: Impact of Cohort Heterogeneity on Functional Connectivity Maps

Brooks, Skylar J; Parks, Sean M; Stamoulis, Catherine

doi:10.1109/embc46164.2021.9630267

Cited by 1 publication

(1 citation statement)

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“…Significantly heterogeneous variability across MRI scanner manufacturers has implications for consortium research using multiple sites with different MRI scanners. To this point, multiple neuroimaging studies using several large datasets have noted the impact of demographic and scanner diversity across samples on brain-phenotype associations, and the importance of incorporating appropriate covariates in multivariate modeling thereof (Benkarim et al, 2022; Brooks et al, 2021; Greene et al, 2022; Miller et al, 2016). This work emphasizes the importance of theoretical justifications in covariate inclusion, instead of including covariates to conform with research norms.…”

Section: Discussionmentioning

confidence: 99%

Profiling intra- and inter-individual differences in brain development across early adolescence

Bottenhorn

Cardenas‐Iniguez

Mills

et al. 2022

Preprint

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As we move toward population-level developmental neuroscience, understanding intra- and interindividual variability in brain maturation and sources of neurodevelopmental heterogeneity becomes paramount. Large-scale, longitudinal neuroimaging studies have uncovered group-level neurodevelopmental trajectories, and while recent work has begun to untangle intra- and interindividual differences, they remain largely unclear. Here, we aim to quantify both intra- and inter-individual variability across facets of neurodevelopment from late childhood to early adolescence in the Adolescent Brain Cognitive Development (ABCD) Study, and examine the contributions of age, sex, puberty, sociodemographic factors, and MRI scanner manufacturer to inter-individual variability. Our results provide novel insight into differences in microstructure development between cortical and subcortical gray matter. We found that an individual's starting point is related to how their brain changes, across all brain outcomes. Although both sex and pubertal status contributed to inter-individual variability, we found limited support for hypotheses regarding greater male-than-female variability and increases in inter-individual variability throughout puberty. Finally, we uncovered enmeshed contributions of sociodemographics and MRI scanner manufacturers to inter-individual variability in this dataset, due in part to sociodemographic differences in participants scanned on Siemens, GE, and Philips MRIs. This work highlights pockets of individual variability for future investigation, describes a promising approach for quantifying deviations from normative development, and urges caution in covariate choice for investigators using ABCD Study data.

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