Analyses of microstructural variation in the human striatum using non-negative 
matrix factorization

Robert, Corinne; Patel, Raihaan; Blostein, Nadia; Steele, Christopher; Chakravarty, M. Mallar

doi:10.1016/j.neuroimage.2021.118744

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Analyses of microstructural variation in the human striatum using non-negative matrix factorization

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Steele, Christopher
Department of Psychology, Concordia University, Montréal, QC, Canada;
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Citation

Robert, C., Patel, R., Blostein, N., Steele, C., & Chakravarty, M. M. (2022). Analyses of microstructural variation in the human striatum using non-negative matrix factorization. NeuroImage, 246: 118744. doi:10.1016/j.neuroimage.2021.118744.

Cite as: https://hdl.handle.net/21.11116/0000-0009-9A34-F

Abstract

The striatum is a major subcortical connection hub that has been heavily implicated in a wide array of motor and cognitive functions. Here, we developed a normative multimodal, data-driven microstructural parcellation of the striatum using non-negative matrix factorization (NMF) based on multiple magnetic resonance imaging-based metrics (mean diffusivity, fractional anisotropy, and the ratio between T1- and T2-weighted structural scans) from the Human Connectome Project Young Adult dataset (n = 329 unrelated participants, age range: 22–35, F/M: 185/144). We further explored the biological and functional relationships of this parcellation by relating our findings to motor and cognitive performance in tasks known to involve the striatum as well as demographics. We identified 5 spatially distinct striatal components for each hemisphere. We also show the gain in component stability when using multimodal versus unimodal metrics. Our findings suggest distinct microstructural patterns in the human striatum that are largely symmetric and that relate mostly to age and sex. Our work also highlights the putative functional relevance of these striatal components to different designations based on a Neurosynth meta-analysis.