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Conference Paper

Analyzing the neocortical fine-structure

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Kruggel,  Frithjof J.
Department Cognitive Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Wiggins,  Christopher J.
Department Cognitive Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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von Cramon,  D. Yves
Department Cognitive Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Citation

Kruggel, F. J., Brückner, M. K., Arendt, T., Wiggins, C. J., & von Cramon, D. Y. (2001). Analyzing the neocortical fine-structure. In M. F. Insana, & R. M. Leahy (Eds.), Information Processing in Medical Science: 17th International Conference, IPMI 2001 Davis, CA, USA, June 18–22, 2001 Proceedings (pp. 239-245). Berlin: Springer. doi:10.1007/3-540-45729-1_26.


Cite as: http://hdl.handle.net/21.11116/0000-0003-2188-E
Abstract
Cytoarchitectonic fields of the human neocortex are defined by characteristic variations in the composition of a general six-layer structure. It is commonly accepted that these fields correspond to functionally homogeneous entities. Diligent techniques were developed to characterize cytoarchitectonic fields by staining sections of post-mortem brains and subsequent statistical evaluation. Fields were found to show a considerable interindividual variability in extent and relation to macroscopic anatomical landmarks. With upcoming new high-resolution magnetic resonance imaging (MRI) protocols, it appears worthwhile to examine the feasibility of characterizing the neocortical fine-structure from anatomical MRI scans, thus, defining neocortical fields by in vivo techniques. A fixated brain hemisphere was scanned at a resolution of approximately 0.3 mm. After correcting for intensity inhomogeneities in the dataset, the cortex boundaries (the white/grey matter and grey matter/background interfaces) were determined as a triangular mesh. Radial intensity profiles following the shortest path through the cortex were computed and characterized by a sparse set of features. A statistical similarity measure between features of different regions was defined, and served to define the extent of Brodmann's Areas 4, 17, 44 and 45 in this dataset.