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Automatic Segmentation of Human Cortical Layer-Complexes and Architectural Areas Using Ex vivo Diffusion MRI and Its
Matteo Bastiani1, Ana-Maria Oros-Peusquens2, Arne Seehaus3
1Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht UniversityMaastricht, Netherlands; Research Centre Jülich, Institute of Neuroscience and Medicine (INM-4)Jülich, Germany.
Frontiers in Neuroscience
|November 29, 2016
Summary
High-resolution diffusion MRI can differentiate cortical layers and identify distinct brain areas using automated clustering. This technique offers a non-invasive method for MR-based cortical histology, revealing layer-specific fiber organization.
Area of Science:
- Neuroimaging
- Neuroanatomy
- Biophysics
Background:
- Magnetic resonance imaging (MRI) contrast mechanisms can differentiate cortical layers.
- Understanding cortical organization is crucial for neuroscience research.
Purpose of the Study:
- To investigate cortical layer and area differentiation using automated unsupervised clustering of high-resolution diffusion MRI data.
- To validate diffusion MRI findings with histological analysis.
Main Methods:
- High-resolution diffusion MRI data acquisition.
- Automatized unsupervised clustering of diffusion MRI signals.
- Analysis of diffusion MRI signal signatures along cortical depth.
- Histological validation of clustering results.
Main Results:
- Distinguished groups of adjacent cortical layers in the human primary motor and premotor cortex.
- Identified area boundaries by detecting abrupt changes in diffusion MRI signal signatures.
- Confirmed that diffusion MRI can probe layer-specific intracortical fiber organization.
- Demonstrated the potential for automatic classification of architecturally distinct cortical areas.
Conclusions:
- Diffusion MRI contains sufficient information for automated classification of cortical areas.
- The automated clustering approach shows promise for MR-based cortical histology.
- Diffusion MRI is a valuable tool for studying layer-specific intracortical organization and cortical architecture.
