High‐resolution intersubject averaging and a coordinate system for the cortical surface

The neurons of the human cerebral cortex are arranged in a highly folded sheet, with the majority of the cortical surface area buried in folds. Cortical maps are typically arranged with a topography oriented parallel to the cortical surface. Despite this unambiguous sheetlike geometry, the most commonly used coordinate systems for localizing cortical features are based on 3‐D stereotaxic coordinates rather than on position relative to the 2‐D cortical sheet. In order to address the need for a more natural surface‐based coordinate system for the cortex, we have developed a means for generating an average folding pattern across a large number of individual subjects as a function on the unit sphere and of nonrigidly aligning each individual with the average. This establishes a spherical surface‐based coordinate system that is adapted to the folding pattern of each individual subject, allowing for much higher localization accuracy of structural and functional features of the human brain. Hum. Brain Mapping 8:272–284, 1999. © 1999 Wiley‐Liss, Inc.

[1]  Edgar M. Housepian Atlas d'anatomie stereotaxique du telencephale. , 1968 .

[2]  E Halgren,et al.  Cognitive evoked potentials as modulatory processes in human memory formation and retrieval. , 1987, Human neurobiology.

[3]  J. Talairach,et al.  Co-Planar Stereotaxic Atlas of the Human Brain: 3-Dimensional Proportional System: An Approach to Cerebral Imaging , 1988 .

[4]  H. Freund,et al.  Cerebral Cortical Localization: Application and Validation of the Proportional Grid System in MR Imaging , 1989, Journal of computer assisted tomography.

[5]  F M Miezin,et al.  Activation of the hippocampus in normal humans: a functional anatomical study of memory. , 1992, Proceedings of the National Academy of Sciences of the United States of America.

[6]  M I Miller,et al.  Mathematical textbook of deformable neuroanatomies. , 1993, Proceedings of the National Academy of Sciences of the United States of America.

[7]  A. Dale,et al.  Improved Localizadon of Cortical Activity by Combining EEG and MEG with MRI Cortical Surface Reconstruction: A Linear Approach , 1993, Journal of Cognitive Neuroscience.

[8]  Adrian T. Lee,et al.  fMRI of human visual cortex , 1994, Nature.

[9]  E. DeYoe,et al.  Functional magnetic resonance imaging (FMRI) of the human brain , 1994, Journal of Neuroscience Methods.

[10]  Stuart Tugendreich,et al.  Alu sequences in RMSA-1 protein? , 1994, Nature.

[11]  S. Petersen,et al.  Practice-related changes in human brain functional anatomy during nonmotor learning. , 1994, Cerebral cortex.

[12]  G J Ross,et al.  Spontaneous healing of basilar artery dissection: MR findings. , 1994, Journal of computer assisted tomography.

[13]  J W Belliveau,et al.  Borders of multiple visual areas in humans revealed by functional magnetic resonance imaging. , 1995, Science.

[14]  Leslie G. Ungerleider Functional Brain Imaging Studies of Cortical Mechanisms for Memory , 1995, Science.

[15]  M. Miller,et al.  Automatic Analysis of Medical Images Using a , 1995 .

[16]  M. Rugg ERP studies of memory. , 1995 .

[17]  M. Rugg,et al.  Electrophysiology of Mind: Event-Related Brain Potentials and Cognition , 1995 .

[18]  R. Andersen,et al.  Functional analysis of human MT and related visual cortical areas using magnetic resonance imaging , 1995, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[19]  Paul M. Thompson,et al.  A surface-based technique for warping three-dimensional images of the brain , 1996, IEEE Trans. Medical Imaging.

[20]  R. Buckner,et al.  An assessment of functional‐anatomical variability in neuroimaging studies , 1996, Human brain mapping.

[21]  E. DeYoe,et al.  Mapping striate and extrastriate visual areas in human cerebral cortex. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[22]  A. Dale,et al.  A surface-based coordinate system for a canonical cortex , 1996, NeuroImage.

[23]  D. V. Essen,et al.  Analysis and comparison of areal partitioning schemes using two-dimensional fluid deformations , 1996, NeuroImage.

[24]  J. B. Demb,et al.  Functional Magnetic Resonance Imaging of Semantic Memory Processes in the Frontal Lobes , 1996 .

[25]  D. V. van Essen,et al.  Structural and Functional Analyses of Human Cerebral Cortex Using a Surface-Based Atlas , 1997, The Journal of Neuroscience.

[26]  Christos Davatzikos,et al.  Spatial Transformation and Registration of Brain Images Using Elastically Deformable Models , 1997, Comput. Vis. Image Underst..

[27]  A. Toga,et al.  Detection and mapping of abnormal brain structure with a probabilistic atlas of cortical surfaces. , 1997, Journal of computer assisted tomography.

[28]  Michael E. Mortenson Geometric modeling (2nd ed.) , 1997 .

[29]  A. Dale,et al.  Functional-Anatomic Correlates of Object Priming in Humans Revealed by Rapid Presentation Event-Related fMRI , 1998, Neuron.

[30]  D. Schacter,et al.  Priming and the Brain , 1998, Neuron.

[31]  D. V. van Essen,et al.  Functional and structural mapping of human cerebral cortex: solutions are in the surfaces. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[32]  A. M. Dale,et al.  A Coordinate System for the Cortical Surface , 1998, NeuroImage.

[33]  Anders M. Dale,et al.  Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction , 1999, NeuroImage.

[34]  A. Dale,et al.  Cortical Surface-Based Analysis II: Inflation, Flattening, and a Surface-Based Coordinate System , 1999, NeuroImage.

[35]  Abraham Z. Snyder,et al.  Surface-Based Analyses of the Human Cerebral Cortex , 1999 .

[36]  R. Woods,et al.  Mathematical/computational challenges in creating deformable and probabilistic atlases of the human brain , 2000, Human brain mapping.

[37]  A. Toga,et al.  A SURFACE-BASED TECHNIQUE FOR WARPING 3-DIMENSIONAL IMAGES OF THE BRAIN , 2000 .