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Resting-state FMRI single subject cortical parcellation based on region growing
Thomas Blumensath1, Timothy E J Behrens, Stephen M Smith
1Oxford Centre for Functional MRI of the Brain (FMRIB Centre), University of Oxford, Oxford, UK. tblumens@fmrib.ox.ac.uk
Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
|January 5, 2013
Summary
This study introduces a novel method for mapping brain regions using functional Magnetic Resonance Imaging (fMRI) resting-state data. The approach provides reproducible, subject-specific cortical parcellations with clear functional connectivity borders.
Area of Science:
- Neuroimaging
- Computational Neuroscience
- Brain Mapping
Background:
- Accurate parcellation of the cerebral cortex is crucial for understanding brain function.
- Existing methods may lack subject-specificity or anatomical plausibility.
- Resting-state functional Magnetic Resonance Imaging (fMRI) offers a non-invasive window into intrinsic brain activity.
Purpose of the Study:
- To develop a novel, surface-based method for subject-specific cortical parcellation.
- To leverage spatial dependencies in resting-state fMRI data for improved brain mapping.
- To achieve reproducible parcellations with anatomically meaningful subregions.
Main Methods:
- A surface-based region growing algorithm was employed on the cortical surface.
- Locally stable seed points were identified and grown into spatially contiguous regions.
- Spatially constrained hierarchical clustering was used to refine the parcellation hierarchy.
- Short-TR resting-state fMRI data was utilized for subject-specific analysis.
Main Results:
- The proposed method successfully parcellates the cerebral cortex into 1000-5000 anatomically plausible subregions per subject.
- High scan-to-scan reproducibility was achieved for the generated parcellations.
- Parcellation borders effectively delineated significant changes in functional connectivity.
Conclusions:
- This novel fMRI-based parcellation method offers a reproducible and subject-specific approach to cortical mapping.
- The technique generates anatomically plausible regions with borders reflecting functional connectivity.
- This method advances the study of individual brain organization and function.
