ArticleNeuroImage2018
Tests of cortical parcellation based on white matter connectivity using diffusion tensor imaging.
Article in NeuroImage, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 18 citations in OpenAlex.
- Direct segmentation of cortical cytoarchitectonic domains using ultra-high-resolution whole-brain diffusion MRI.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Evaluation of functional MRI-based human brain parcellation: a review.Journal of neurophysiology · 2022Review
- A novel method for estimating connectivity-based parcellation of the human brain from diffusion MRI: Application to an aging cohort.Human brain mapping · 2022Article
- Multiple b-values improve discrimination of cortical gray matter regions using diffusion MRI: an experimental validation with a data-driven approach.Magma (New York, N.Y.) · 2021Article
- Joint contributions of cortical morphometry and white matter microstructure in healthy brain aging: A partial least squares correlation analysis.Human brain mapping · 2019Article
- A fiber coherence index for quality control of B-table orientation in diffusion MRI scans.Magnetic resonance imaging · 2019Article
- Functional tractography of white matter by high angular resolution functional-correlation imaging (HARFI).Magnetic resonance in medicine · 2019Article
- Article
- Imaging-based parcellations of the human brain.Nature reviews. Neuroscience · 2018Review
- Tests of clustering thalamic nuclei based on various dMRI models in the squirrel monkey brain.Proceedings of SPIE--the International Society for Optical Engineering · 2018Article
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
The cerebral cortex is conventionally divided into a number of domains based on cytoarchitectural features. Diffusion tensor imaging (DTI) enables noninvasive parcellation of the cortex based on white matter connectivity patterns. However, the correspondence between DTI-connectivity-based and cytoarchitectural parcellation has not been systematically established. In this study, we compared histological parcellation of New World monkey neocortex to DTI- connectivity-based classification and clustering in the same brains. First, we used supervised classification to parcellate parieto-frontal cortex based on DTI tractograms and the cytoarchitectural prior (obtained using Nissl staining). We performed both within and across sample classification, showing reasonable classification performance in both conditions. Second, we used unsupervised clustering to parcellate the cortex and compared the clusters to the cytoarchitectonic standard. We then explored the similarities and differences with several post-hoc analyses, highlighting underlying principles that drive the DTI-connectivity-based parcellation. The differences in parcellation between DTI-connectivity and Nissl histology probably represent both DTI's bias toward easily-tracked bundles and true differences between cytoarchitectural and connectivity defined domains. DTI tractograms appear to cluster more according to functional networks, rather than mapping directly onto cytoarchitectonic domains. Our results show that caution should be used when DTI-tractography classification, based on data from another brain, is used as a surrogate for cytoarchitectural parcellation.
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