Investigating microstructural variation in the human hippocampus using non-negative matrix factorization.
Neuroimage
; 207: 116348, 2020 02 15.
Article
in En
| MEDLINE
| ID: mdl-31715254
ABSTRACT
In this work we use non-negative matrix factorization to identify patterns of microstructural variance in the human hippocampus. We utilize high-resolution structural and diffusion magnetic resonance imaging data from the Human Connectome Project to query hippocampus microstructure on a multivariate, voxelwise basis. Application of non-negative matrix factorization identifies spatial components (clusters of voxels sharing similar covariance patterns), as well as subject weightings (individual variance across hippocampus microstructure). By assessing the stability of spatial components as well as the accuracy of factorization, we identified 4 distinct microstructural components. Furthermore, we quantified the benefit of using multiple microstructural metrics by demonstrating that using three microstructural metrics (T1-weighted/T2-weighted signal, mean diffusivity and fractional anisotropy) produced more stable spatial components than when assessing metrics individually. Finally, we related individual subject weightings to demographic and behavioural measures using a partial least squares analysis. Through this approach we identified interpretable relationships between hippocampus microstructure and demographic and behavioural measures. Taken together, our work suggests non-negative matrix factorization as a spatially specific analytical approach for neuroimaging studies and advocates for the use of multiple metrics for data-driven component analyses.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Image Processing, Computer-Assisted
/
Neuroimaging
/
White Matter
/
Hippocampus
Type of study:
Prognostic_studies
Limits:
Female
/
Humans
/
Male
Language:
En
Journal:
Neuroimage
Journal subject:
DIAGNOSTICO POR IMAGEM
Year:
2020
Document type:
Article