A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM)
Philosophical Transactions of the Royal Society B: Biological Sciences. 2001-08-29; 356(1412): 1293-1322
DOI: 10.1098/rstb.2001.0915
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1. Philos Trans R Soc Lond B Biol Sci. 2001 Aug 29;356(1412):1293-322.
A probabilistic atlas and reference system for the human brain: International
Consortium for Brain Mapping (ICBM).
Mazziotta J(1), Toga A, Evans A, Fox P, Lancaster J, Zilles K, Woods R, Paus T,
Simpson G, Pike B, Holmes C, Collins L, Thompson P, MacDonald D, Iacoboni M,
Schormann T, Amunts K, Palomero-Gallagher N, Geyer S, Parsons L, Narr K, Kabani
N, Le Goualher G, Boomsma D, Cannon T, Kawashima R, Mazoyer B.
Author information:
(1)Ahmanson-Lovelace Brain Mapping Center, UCLA School of Medicine, 660 Charles
E. Young Drive, South Los Angeles, CA 90095, USA.
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.
DOI: 10.1098/rstb.2001.0915
PMCID: PMC1088516
PMID: 11545704 [Indexed for MEDLINE]