Attaining a consensus whole-cortex parcellation has been difficult because of practical and technical challenges that we address here
2016
Key concepts
- maximum probability map
- topography
- Human Connectome Project
- cerebral cortex
- atypical parcellations
- cortical architecture
- 29 test
- centuryold objective
- neuroanatomical precision
- magnetic resonance imaging
- accurate areal
- new area
- frontal eye field
- task functional MRI
- major subdivision
- signal-to-noise ratio
- neuroanatomical approach
- premotor eye field
- human cerebral cortex
- sharp change
- region of interest
- Resting-state functional MRI
- complex human
- magnetic resonance
- 3 tesla
- cortical area
- multi modal
- multimodal surface matching
- areal map
- healthy young
- group average
- microscopy
- young adult
- resonance image
- modal magnetic
Scholarcy highlights
- Understanding the amazingly complex human cerebral cortex requires a map of its major subdivisions, known as cortical areas
- We have produced a population-based 180-area per hemisphere human cortical parcellation using exceptionally high quality multimodal data from hundreds of Human Connectome Project subjects aligned using an improved areal feature-based cross-subject alignment method
- Inspired by an observer-independent post-mortem architectural parcellation approach, we developed a semi-automated neuroanatomical approach adapted to non-invasively acquired multi-modal magnetic resonance imaging data
- Though algorithms determined the final areal borders, the multi-modal data were carefully interpreted by neuroanatomists, the properties of each cortical area were documented, and each area was named in relation to the extant neuroanatomical literature
- A crossvalidation showed that the areas forming the parcellation were robustly and statistically significantly different from their neighbours across multiple modalities. We identify this parcellation as HCP-MMP1.0, with version 1.0 anticipating future refinements as better data become available
- Though we made extensive use of the HCP’s specialized task fMRI battery when generating the parcellation, we showed that task fMRI data is not essential for future studies aiming to use the areal classifier to automatically define the cortical areas in their subjects
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