Cerebral Cortex Advance Access originally published online on May 17, 2006
Cerebral Cortex 2007 17(4):816-825; doi:10.1093/cercor/bhk034
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Connectivity-Based Parcellation of Broca's Area
1 Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 2 Max Planck Institute for Neurological Research, Cologne, Germany
Address correspondence to Dr Marc Tittgemeyer, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstrasse 1a, 04103 Leipzig, Germany. Email: tittge{at}cbs.mpg.de.
It is generally agreed that the cerebral cortex can be segregated into structurally and functionally distinct areas. Anatomical subdivision of Broca's area has been achieved using different microanatomical criteria, such as cytoarchitecture and distribution of neuroreceptors. However, brain function also strongly depends upon anatomical connectivity, which therefore forms a sensible criterion for the functio-anatomical segregation of cortical areas. Diffusion-weighted magnetic resonance (MR) imaging offers the opportunity to apply this criterion in the individual living subject. Probabilistic tractographic methods provide excellent means to extract the connectivity signatures from diffusion-weighting MR data sets. The correlations among these signatures may then be used by an automatic clustering method to identify cortical regions with mutually distinct and internally coherent connectivity. We made use of this principle to parcellate Broca's area. As it turned out, 3 subregions are discernible that were identified as putative Brodmann area (BA) 44, BA45, and the deep frontal operculum. These results are discussed in the light of previous evidence from other methods in both human and nonhuman primates. We conclude that plausible results can be achieved by the proposed technique, which cannot be obtained by any other method in vivo. For the first time, there is a possibility to investigate the anatomical subdivision of Broca's area noninvasively in the individual living human subject.
Key Words: Broca's area connectivity cortex parcellation diffusion tensor imaging tractography
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