A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM)

John C. Mazziotta(Brain Mapping Foundation), Arthur W. Toga, Alan C. Evans(Montreal Neurological Institute and Hospital), Peter T. Fox(The University of Texas at San Antonio Health Science Center), Jack L. Lancaster(The University of Texas at San Antonio Health Science Center), Karl Zilles(Tohoku University), Roger P. Woods(Brain Mapping Foundation), Tomáš Paus(Montreal Neurological Institute and Hospital), Gregory V. Simpson(University of California, Los Angeles), Bruce Pike(Montreal Neurological Institute and Hospital), Colin J. Holmes(University of California, Los Angeles), D. Louis Collins(Montreal Neurological Institute and Hospital), Paul M. Thompson, David MacDonald(Montreal Neurological Institute and Hospital), Marco Iacoboni(Brain Mapping Foundation), Thorsten Schormann(University of California, Los Angeles), Katrin Amunts(University of California, Los Angeles), Nicola Palomero‐Gallagher(University of California, Los Angeles), Stefan Geyer(Heinrich Heine University Düsseldorf), Larry Parsons(The University of Texas at San Antonio Health Science Center), Katherine L. Narr, Noor Jehan Kabani(Montreal Neurological Institute and Hospital), Georges Le Goualher(Montreal Neurological Institute and Hospital), Dorret I. Boomsma(University of California, Los Angeles), Tyrone D. Cannon(University of California, Los Angeles), Ryuta Kawashima(Tohoku University), Bernard Mazoyer(University of California, Los Angeles)
Philosophical Transactions of the Royal Society B Biological Sciences
August 29, 2001
10.1098/rstb.2001.0915
Cited by 2,401Open Access
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Abstract

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 dataset is being collected that includes 7000 subjects between the ages of eighteen and ninety years and including 342 mono- and dizygotic twins. Data on each subject includes detailed demographic, clinical, behavioural and imaging information. DNA has been collected for genotyping from 5800 subjects. A component of the programme uses post-mortem 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 large scale 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 behaviour will allow for the first assessment of cerebral genotype-phenotype-behavioural correlations in humans to take place in a population this large. 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.

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