A Population-Average, Landmark- and Surface-based (PALS) atlas of human cerebral cortex

This report describes a new electronic atlas of human cerebral cortex that provides a substrate for a wide variety of brain-mapping analyses. The Population-Average, Landmark- and Surface-based (PALS) atlas approach involves surface-based and volume-based representations of cortical shape, each available as population averages and as individual subject data. The specific PALS-B12 atlas introduced here is derived from structural MRI volumes of 12 normal young adults. Accurate cortical surface reconstructions were generated for each hemisphere, and the surfaces were inflated, flattened, and mapped to standard spherical configurations using SureFit and Caret software. A target atlas sphere was generated by averaging selected landmark contours from each of the 24 contributing hemispheres. Each individual hemisphere was deformed to this target using landmark-constrained surface registration. The utility of the resultant PALS-B12 atlas was demonstrated using a variety of analyses. (i) Probabilistic maps of sulcal identity were generated using both surface-based registration (SBR) and conventional volume-based registration (VBR). The SBR approach achieved markedly better consistency of sulcal alignment than did VBR. (ii) A method is introduced for dmulti-fiducial mappingT of volume-averaged group data (e.g., fMRI data, probabilistic architectonic maps) onto each individual hemisphere in the atlas, followed by spatial averaging across the individual maps. This yielded a population-average surface representation that circumvents the biases inherent in choosing any single hemisphere as a target. (iii) Surface-based and volume-based morphometry applied to maps of sulcal depth and sulcal identity demonstrated prominent left–right asymmetries in and near the superior temporal sulcus and Sylvian fissure. Moreover, shape variability in the temporal lobe is significantly greater in the left than the right hemisphere. The PALS-B12 atlas has been registered to other surface-based atlases to facilitate interchange of data and comparison across atlases. All data sets in the PALS-B12 atlas are accessible via the SumsDB database for online and offline

[1]  J. Mazziotta,et al.  Brain Mapping: The Methods , 2002 .

[2]  David C. Van Essen,et al.  Surface-based approaches to spatial localization and registration in primate cerebral cortex , 2004, NeuroImage.

[3]  L. Chalupa,et al.  The visual neurosciences , 2004 .

[4]  M. Raichle,et al.  Anatomic Localization and Quantitative Analysis of Gradient Refocused Echo-Planar fMRI Susceptibility Artifacts , 1997, NeuroImage.

[5]  Alan C. Evans,et al.  Automated 3-D Extraction of Inner and Outer Surfaces of Cerebral Cortex from MRI , 2000, NeuroImage.

[6]  Jeffrey R. Binder,et al.  Volumetric vs. surface-based alignment for localization of auditory cortex activation , 2005, NeuroImage.

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

[8]  Abraham Z. Snyder,et al.  A unified approach for morphometric and functional data analysis in young, old, and demented adults using automated atlas-based head size normalization: reliability and validation against manual measurement of total intracranial volume , 2004, NeuroImage.

[9]  D. V. van Essen,et al.  Mapping of architectonic subdivisions in the macaque monkey, with emphasis on parieto‐occipital cortex , 2000, The Journal of comparative neurology.

[10]  A. Dale,et al.  High‐resolution intersubject averaging and a coordinate system for the cortical surface , 1999, Human brain mapping.

[11]  P. Cavanagh,et al.  Retinotopy and color sensitivity in human visual cortical area V8 , 1998, Nature Neuroscience.

[12]  J. Maunsell,et al.  Two‐dimensional maps of the cerebral cortex , 1980, The Journal of comparative neurology.

[13]  D. V. von Cramon,et al.  Sulcal variability of twins. , 1999, Cerebral cortex.

[14]  M S Gazzaniga,et al.  Three-dimensional quantitative analysis of hemispheric asymmetry in the human superior temporal region. , 1993, Cerebral cortex.

[15]  Jean-Francois Mangin,et al.  Sulcal pattern and morphology of the superior temporal sulcus , 2004, NeuroImage.

[16]  A. Galaburda,et al.  Topographical variation of the human primary cortices: implications for neuroimaging, brain mapping, and neurobiology. , 1993, Cerebral cortex.

[17]  K. Zilles,et al.  Areas 3a, 3b, and 1 of Human Primary Somatosensory Cortex 2. Spatial Normalization to Standard Anatomical Space , 2000, NeuroImage.

[18]  K. Brodmann.  Vergleichende Lokalisationslehre der Großhirnrinde : in ihren Prinzipien dargestellt auf Grund des Zellenbaues , 1985 .

[19]  A. Schleicher,et al.  Two different areas within the primary motor cortex of man , 1996, Nature.

[20]  K. Zilles,et al.  Human brain atlas: For high‐resolution functional and anatomical mapping , 1994, Human brain mapping.

[21]  K. Amunts,et al.  Brodmann's Areas 17 and 18 Brought into Stereotaxic Space—Where and How Variable? , 2000, NeuroImage.

[22]  Brenna Argall,et al.  SUMA: an interface for surface-based intra- and inter-subject analysis with AFNI , 2004, 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821).

[23]  P. Morosan,et al.  Probabilistic Mapping and Volume Measurement of Human Primary Auditory Cortex , 2001, NeuroImage.

[24]  Dr. Stefan Geyer.  The Microstructural Border Between the Motor and the Cognitive Domain in the Human Cerebral Cortex , 2004, Advances in Anatomy Embryology and Cell Biology.

[25]  K. Amunts,et al.  Advances in cytoarchitectonic mapping of the human cerebral cortex. , 2001, Neuroimaging clinics of North America.

[26]  P. Morosan,et al.  Human Primary Auditory Cortex: Cytoarchitectonic Subdivisions and Mapping into a Spatial Reference System , 2001, NeuroImage.

[27]  D. J. Felleman,et al.  Distributed hierarchical processing in the primate cerebral cortex. , 1991, Cerebral cortex.

[28]  J Mazziotta,et al.  A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM). , 2001, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[29]  T Schormann,et al.  Three‐Dimensional linear and nonlinear transformations: An integration of light microscopical and MRI data , 1998, Human brain mapping.

[30]  B. Fischer,et al.  Visual field representations and locations of visual areas V1/2/3 in human visual cortex. , 2003, Journal of vision.

[31]  A. Schleicher,et al.  21 – Quantitative Analysis of Cyto- and Receptor Architecture of the Human Brain , 2002 .

[32]  R. Buckner,et al.  Dissociation of human prefrontal cortical areas across different speech production tasks and gender groups. , 1995, Journal of neurophysiology.

[33]  A. Dale,et al.  Thinning of the cerebral cortex in aging. , 2004, Cerebral cortex.

[34]  M. Corbetta,et al.  Control of goal-directed and stimulus-driven attention in the brain , 2002, Nature Reviews Neuroscience.

[35]  David C. Van Essen,et al.  Application of Information Technology: An Integrated Software Suite for Surface-based Analyses of Cerebral Cortex , 2001, J. Am. Medical Informatics Assoc..

[36]  Jean-Francois Mangin,et al.  Automatic recognition of cortical sulci of the human brain using a congregation of neural networks , 2002, Medical Image Anal..

[37]  M. Torrens.  Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268 , 1990 .

[38]  P. Goldman-Rakic,et al.  Preface: Cerebral Cortex Has Come of Age , 1991 .

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

[40]  A. Schleicher,et al.  Broca's region revisited: Cytoarchitecture and intersubject variability , 1999, The Journal of comparative neurology.

[41]  D. Head,et al.  Frontal-hippocampal double dissociation between normal aging and Alzheimer's disease. , 2005, Cerebral cortex.

[42]  Alan C. Evans,et al.  Structural asymmetries in the human brain: a voxel-based statistical analysis of 142 MRI scans. , 2001, Cerebral cortex.

[43]  A. Toga,et al.  Mapping sulcal pattern asymmetry and local cortical surface gray matter distribution in vivo: maturation in perisylvian cortices. , 2002, Cerebral cortex.

[44]  A. Toga,et al.  Mapping brain asymmetry , 2003, Nature Reviews Neuroscience.

[45]  J. Price,et al.  Architectonic subdivision of the human orbital and medial prefrontal cortex , 2003, The Journal of comparative neurology.

[46]  Karl J. Friston,et al.  Statistical parametric maps in functional imaging: A general linear approach , 1994 .

[47]  A. Schleicher,et al.  Areas 3a, 3b, and 1 of Human Primary Somatosensory Cortex 1. Microstructural Organization and Interindividual Variability , 1999, NeuroImage.

[48]  W. H. Dobelle,et al.  The topography and variability of the primary visual cortex in man. , 1974, Journal of neurosurgery.

[49]  R. Woods,et al.  Cortical change in Alzheimer's disease detected with a disease-specific population-based brain atlas. , 2001, Cerebral cortex.

[50]  D. V. Essen,et al.  A tension-based theory of morphogenesis and compact wiring in the central nervous system , 1997, Nature.

[51]  A. Schleicher,et al.  Integration of microstructural and functional aspects of human somatosensory areas 3a, 3b, and 1 on the basis of a computerized brain atlas , 2001, Anatomy and Embryology.

[52]  D. V. van Essen,et al.  Computerized Mappings of the Cerebral Cortex: A Multiresolution Flattening Method and a Surface-Based Coordinate System , 1996, Journal of Cognitive Neuroscience.

[53]  David C. Van Essen,et al.  Windows on the brain: the emerging role of atlases and databases in neuroscience , 2002, Current Opinion in Neurobiology.

[54]  Simon B. Eickhoff,et al.  Analysis of neural mechanisms underlying verbal fluency in cytoarchitectonically defined stereotaxic space—The roles of Brodmann areas 44 and 45 , 2004, NeuroImage.

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

[56]  A. Toga,et al.  New approaches in brain morphometry. , 2002, The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry.

[57]  K. Zilles,et al.  Human Somatosensory Area 2: Observer-Independent Cytoarchitectonic Mapping, Interindividual Variability, and Population Map , 2001, NeuroImage.

[58]  S. Koslow,et al.  Databasing the brain : from data to knowledge (neuroinformatics) , 2005 .

[59]  Moo K. Chung,et al.  Deformation-based surface morphometry applied to gray matter deformation , 2003, NeuroImage.

[60]  R. Thatcher.  Functional neuroimaging : technical foundations , 1994 .

[61]  小野 道夫,et al.  Atlas of the Cerebral Sulci , 1990 .

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

[63]  Karl J. Friston,et al.  Cerebral Asymmetry and the Effects of Sex and Handedness on Brain Structure: A Voxel-Based Morphometric Analysis of 465 Normal Adult Human Brains , 2001, NeuroImage.