A Probabilistic Atlas and Reference System for the Human Brain

Journal of the Royal Society [submitted, June 2000]

John Mazziotta1, Arthur Toga2, Alan Evans3, Peter Fox4, Jack Lancaster4, Karl Zilles5,11,
Roger Woods1, Tomas Paus3, Gregory Simpson6, Bruce Pike3, Colin Holmes2, Louis Collins3,
Paul Thompson 2, David MacDonald3, Marco Iacoboni1, Thorsten Schormann5,
Katrin Amunts11, Nicola Palomero-Gallagher11, Stefan Geyer5, Larry Parsons4,
Katherine Narr2, Noor Kabani3, Georges Le Goualher3, Dorret Boomsma8,
Tyrone Cannon7, Ryuta Kawashima10, Bernard Mazoyer9



1.   Brain Mapping Center, UCLA School of Medicine, Los Angeles, CA

2.   Laboratory of Neuroimaging, UCLA School of Medicine, Los Angeles, CA

3.   Montreal Neurologic Institute, McGill University, Montreal, Canada

4.   Research Imaging Laboratory, University of Texas at San Antonio

5.   Heinrich Heine University, Düsseldorf, Germany

6.   Department of Radiology, University of California at San Francisco

7.   Department of Psychology, UCLA, Los Angeles, CA

8.   Vrije University, Amsterdam, The Netherlands

9.   University de Caen, Caen, France

10. Tohoku University, Sendai, Japan

11. Institute of Medicine, Research Center Jülich, Germany


Motivated by the vast amount of information that is rapidly accumulating about the human brain in digital form, we embarked upon a program in 1992 to develop a four-dimensional probabilistic atlas and reference system for the human brain. Through an International Consortium for Brain Mapping (ICBM) a data set is being collected that includes 7,000 subjects between the ages of eighteen and ninety years and including 342 mono- and dizygotic twins. Data on each subject includes detailed demographic, clinical, behavioral, and imaging information. Fifty-eight hundred subjects have DNA collected for genotyping. A component of the program uses postmortem tissue to determine the probabilistic distribution of microscopic cyto- and chemoarchitectural regions in the human brain. This combined with macroscopic information about structure and function derived from subjects in vivo, provides the first opportunity to gain meaningful insights into the concordance or discordance in micro- and macroscopic structure and function. The philosophy, strategy, algorithm development, data acquisition techniques and validation methods are described in this report along with database structures. Examples of results are described for the normal adult human brain as well as examples in patients with Alzheimer's disease and multiple sclerosis. The ability to quantify the variance of the human brain as a function of age in a large population of subjects for whom data is also available about their genetic composition and behavior will allow for the first large-scale assessment of cerebral genotype-phenotype-behavioral correlations in humans. This approach and its application should provide new insights and opportunities for investigators interested in basic neuroscience, clinical diagnostics and the evaluation of neuropsychiatric disorders in patients.


Key Words: atlas, probabilistic, four-dimensional, cytoarchitecture, chemoarchitecture, magnetic resonance imaging, database, segmentation, brain mapping, neuroanatomy, genetics, Alzheimer's disease, multiple sclerosis

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    Paul Thompson, Ph.D.
    Assistant Professor of Neurology
    4238 Reed Neurology, 710 Westwood Plaza
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