1 Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, Canada; Department of Biological and Biomedical Engineering, McGill University, Montreal, Canada. Electronic address: mohammed.patel@mail.mcgill.ca.
2 Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, Canada; Department of Psychology, Concordia University, Montreal, Quebec, H4B 1R6, Canada; Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
3 Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, Canada; School of Computer Science, McGill University, Montreal, Canada.
4 Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, Canada; Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Canada; Institute of Medical Science, University of Toronto, Toronto, Canada.
5 Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, Canada; Department of Psychiatry, McGill University, Montreal, Canada.
6 Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, Canada; University Health Network, Toronto, Canada.
7 Department of Biological and Biomedical Engineering, McGill University, Montreal, Canada; McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada; Department of Neurology and Neurosurgery, McGill University, Montreal, Canada.
8 Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, Canada; Department of Biological and Biomedical Engineering, McGill University, Montreal, Canada; Department of Psychiatry, McGill University, Montreal, Canada. Electronic address: mallar@cobralab.ca.

Investigating microstructural variation in the human hippocampus using non-negative matrix factorization.

Neuroimage. 2019 Nov 09;:116348

Authors: Patel R, Steele CJ, Chen A, Patel S, Devenyi GA, Germann J, Tardif CL, Chakravarty MM

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.

PMID: 31715254 [PubMed - as supplied by publisher]