ArticleNeuroImage. Clinical2022
General additive models address statistical issues in diffusion MRI: An example with clinically anxious adolescents.
Article in NeuroImage. Clinical, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed, 19 citations in OpenAlex.
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- A Pubertal Shift in Anxiety Reporting: Parent-child Discrepancies Intensify During Peri-Adolescence.Research on child and adolescent psychopathology · 2026Article
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- A software ecosystem for brain tractometry processing, analysis, and insight.PLoS computational biology · 2025Article
- Structural Development of Speech Networks in Young Children: A Cross-Sectional Study.Neurobiology of language (Cambridge, Mass.) · 2025Article
- Detecting mild traumatic brain injury with MEG scan data: One-vs-K-sample tests.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Development of the arcuate fasciculus is linked to learning gains in reading.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Tractometry of Human Visual White Matter Pathways in Health and Disease.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2024Review
- Development of the Alpha Rhythm Is Linked to Visual White Matter Pathways and Visual Detection Performance.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- Subtle microstructural alterations in white matter tracts involved in socio-emotional processing after very preterm birth.NeuroImage. Clinical · 2024Article
- Diagnostic reference level quantities for adult chest and abdomen-pelvis CT examinations: correlation with organ doses.Insights into imaging · 2023Article
- Multimodal tract-based MRI metrics outperform whole brain markers in determining cognitive impact of small vessel disease-related brain injury.Brain structure & function · 2022Article
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
Statistical models employed to test for group differences in quantized diffusion-weighted MRI white matter tracts often fail to account for the large number of data points per tract in addition to the distribution, type, and interdependence of the data. To address these issues, we propose the use of Generalized Additive Models (GAMs) and supply code and examples to aid in their implementation. Specifically, using diffusion data from 73 periadolescent clinically anxious and no-psychiatric-diagnosis control participants, we tested for group tract differences and show that a GAM allows for the identification of differences within a tract while accounting for the nature of the data as well as covariates and group factors. Further, we then used these tract differences to investigate their association with performance on a memory test. When comparing our high versus low anxiety groups, we observed a positive association between the left uncinate fasciculus and memory overgeneralization for negatively valenced stimuli. This same association was not evident in the right uncinate or anterior forceps. These findings illustrate that GAMs are well-suited for modeling diffusion data while accounting for various aspects of the data, and suggest that the adoption of GAMs will be a powerful investigatory tool for diffusion-weighted analyses.
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