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Basics of Multivariate Analysis in Neuroimaging Data
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Analyses of microstructural variation in the human striatum using non-negative matrix factorization
Corinne Robert1, Raihaan Patel2, Nadia Blostein3
1Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, QC, Canada.
Neuroimage
|December 1, 2021
Summary
Researchers mapped the human striatum using multimodal MRI data, identifying distinct microstructural patterns. These patterns, largely symmetrical, correlate with age and sex, suggesting functional relevance.
Area of Science:
- Neuroimaging
- Neuroanatomy
- Computational Neuroscience
Background:
- The striatum is a crucial subcortical hub for motor and cognitive functions.
- Understanding its microstructural organization is key to deciphering its complex roles.
Purpose of the Study:
- To develop a data-driven, multimodal microstructural parcellation of the human striatum.
- To investigate the stability and biological/functional relationships of these striatal parcellations.
Main Methods:
- Utilized non-negative matrix factorization (NMF) on multimodal MRI metrics (MD, FA, T1/T2 ratio).
- Analyzed data from the Human Connectome Project Young Adult dataset (n=329).
- Correlated parcellation findings with motor/cognitive performance and demographics.
Main Results:
- Identified 5 distinct, largely symmetrical striatal components per hemisphere.
- Demonstrated improved component stability with multimodal versus unimodal metrics.
- Found associations between striatal patterns, age, and sex.
Conclusions:
- The human striatum exhibits distinct microstructural patterns with significant hemispheric symmetry.
- These patterns show relationships with demographic factors (age, sex) and putative functional relevance.
- Multimodal MRI data enhances the reliability of striatal microstructural parcellation.
