Inter-subject connectivity-based parcellation of a patch of cerebral cortex

Med Image Comput Comput Assist Interv. 2010;13(Pt 2):347-54. doi: 10.1007/978-3-642-15745-5_43.

Abstract

This paper presents a connectivity-based parcellation of the human post-central gyrus, at the level of the group of subjects. The dimension of the clustering problem is reduced using a set of cortical regions of interest determined at the inter-subject level using a surface-based coordinate system, and representing the regions with a strong connection to the post-central gyrus. This process allows a clustering based on criteria which are more reproducible across subjects than in an intra-subject approach. We obtained parcels relatively stable in localisation across subjects as well as homogenous and well-separated to each other in terms of connectivity profiles. To address the parcellation at the inter-subject level provides a direct matching between parcels across subjects. In addition, this method allows the identification of subject-specific parcels. This property could be useful for the study of pathologies.

MeSH terms

  • Algorithms*
  • Cerebral Cortex / anatomy & histology*
  • Diffusion Tensor Imaging / methods*
  • Humans
  • Image Enhancement / methods
  • Image Interpretation, Computer-Assisted / methods*
  • Information Storage and Retrieval / methods*
  • Nerve Net / anatomy & histology*
  • Neural Pathways / anatomy & histology*
  • Pattern Recognition, Automated / methods*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Subtraction Technique*