The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Human Cerebral Cortex: Localization, Parcellation, and Morphometry with Magnetic Resonance Imaging
Abstract
We describe a system of parcellation of the human brain that is based on the functional anatomy of the cerebral cortex and that is applied to the analysis of magnetic resonance images. This system is designed to support investigations of hemispheric asymmetries and quantitative lesion localization studies in cognitive neuroscience. The system of cortical subdivision is a neural systems oriented model that approximates subdivisions supported by previous architectonic and functional analyses. It is based primarily on boundaries determined by "limiting fissures." It is completed by a set of coronal planes, keyed to visible anatomic landmarks, which "close" the borders of the parcellation subdivisions. The method depends on computational reconstruction of the primary image data in multiple planes so as to allow the observed pattern of limiting fissures in a given brain to be digitized. In this presentation, the method is applied in order to define the surface anatomy of the cerebral hemispheres in a normal subject. Volumetric measurements of individual cortical regions are compared as hemispheric percentiles to areal perceniiles derived from the analysis of Jouandet et al. (1989), a conceptually related though methodologically different approach. We specifically address the approach to the study of interhemispheric differences and interindividual variations in cortical anatomy.
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Citations
Cites
Specification of Cerebral Cortical Areas
Rakic, P. (1988) · Science · doi:10.1126/science.3291116 · Cited by 3,127
Object vision and spatial vision: Two cortical pathways
Mishkin, M., Ungerleider, L. G., & Macko, K. A. (1983) · Trends in Neurosciences · doi:10.1016/0166-2236(83)90190-x · Cited by 2,947
Large-scale neurocognitive networks and distributed processing for attention, language, and memory
Mesulam, M. (1990) · Annals of Neurology · doi:10.1002/ana.410280502 · Cited by 2,684
Synaptic density in human frontal cortex —Developmental changes and effects of aging
Peter R., H. (1979) · Brain Research · doi:10.1016/0006-8993(79)90349-4 · Cited by 2,645
Functional mapping of the human visual cortex by magnetic resonance imaging
Belliveau, J. W., Kennedy, D. N., McKinstry, R. C., Buchbinder, B. R., Weisskoff, R. M., Cohen, M. S., Vevea, J. M., Brady, T. J., & Rosen, B. R. (1991) · Science · doi:10.1126/science.1948051 · Cited by 1,883
Self-citationConcurrent overproduction of synapses in diverse regions of the primate cerebral cortex
Rakic, P., Bourgeois, J.-P., Eckenhoff, M. F., Zecevic, N., & Goldman-Rakic, P. S. (1986) · Science · doi:10.1126/science.3952506 · Cited by 1,133
Broca aphasia: Pathologic and clinical
MOHR, J. P., PESSIN, M. S., FINKELSTEIN, S., FUNKENSTEIN, H. H., DUNCAN, G. W., & DAVIS, K. R. (1978) · Neurology · doi:10.1212/wnl.28.4.311 · Cited by 549
Mapping human visual cortex with positron emission tomography
Fox, P. T., Mintun, M. A., Raichle, M. E., Miezin, F. M., Allman, J. M., & Van Essen, D. C. (1986) · Nature · doi:10.1038/323806a0 · Cited by 422
Cited by
Tzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., Crivello, F., Etard, O., Delcroix, N., Mazoyer, B., & Joliot, M. (2002) · NeuroImage · doi:10.1006/nimg.2001.0978 · Cited by 16,319
Desikan, R. S., Ségonne, F., Fischl, B., Quinn, B. T., Dickerson, B. C., Blacker, D., Buckner, R. L., Dale, A. M., Maguire, R. P., Hyman, B. T., et al. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.01.021 · Cited by 13,324
Fischl, B., Salat, D. H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., van der Kouwe, A., Killiany, R., Kennedy, D., Klaveness, S., et al. (2002) · Neuron · doi:10.1016/s0896-6273(02)00569-x · Cited by 8,610
Self-citationThe Angular Gyrus: Multiple Functions and Multiple Subdivisions
Seghier, M. L. (2013) · The Neuroscientist · doi:10.1177/1073858412440596 · Cited by 1,585
Just, M. A. (2004) · Brain · doi:10.1093/brain/awh199 · Cited by 1,589
Metadata
- Authors
- Rademacher, J., Galaburda, A. M., Kennedy, D. N., Filipek, P. A., & Caviness, V. S.
- Venue
- Journal of Cognitive Neuroscience
- Publisher
- MIT Press - Journals
- Published
- 1992
- Volume
- 4
- Issue
- 4
- Pages
- 352-374
- ISSN
- 0898-929X (ISSN-L)
- 1530-8898
- OpenAlex
- W1991785932
- Cited by
- 378
- References
- 8
- FWCI
- 13.62
- Type
- journal article
- Language
- en
- Open access
- closed
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