Connectivity-based structural and functional parcellation of the human cortex using diffusion imaging and tractography

• Main Authors: Lauren Louise Cloutman (Author), Matthew A Lambon Ralph (Author)
• Format: Book
• Published: Frontiers Media S.A., 2012-08-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 1662-5129; 10.3389/fnana.2012.00034
• Keywords: Diffusion; connectivity; tractography; Cytoarchitecture; Functional Specialization; Inferior parietal cortex; Neurosciences. Biological psychiatry. Neuropsychiatry; RC321-571; Human anatomy; QM1-695
• Source: Frontiers in Neuroanatomy, Vol 6 (2012)

The parcellation of the cortex via its anatomical properties has been an important research endeavor for over a century. To date, however, a universally accepted parcellation scheme for the human brain still remains elusive. In the current review, we explore the use of in vivo diffusion imaging and white matter tractography as a non-invasive method for the structural and functional parcellation of the human cerebral cortex, discussing the strengths and limitations of the current approaches. Cortical parcellation via white matter connectivity is based on the premise that, as connectional anatomy determines functional organisation, it should be possible to segregate functionally-distinct cortical regions by identifying similarities and differences in connectivity profiles. Recent studies have provided initial evidence in support of the efficacy of this connectional parcellation methodology. Such investigations have identified distinct cortical subregions which correlate strongly with functional regions identified via fMRI and meta-analyses. Furthermore, a strong parallel between the cortical regions defined via tractographic and more traditional cytoarchitectonic parcellation methods has been observed. However, the degree of correspondence and relative functional importance of cytoarchitectonic- versus connectivity-derived parcellations still remains unclear. Diffusion tractography remains one of the only methods capable of visualizing the structural networks of the brain in vivo. As such, it is of vital importance to continue to improve the accuracy of the methodology and to extend its potential applications in the study of cognition in neurological health and disease.