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Nature 404, 190-193 (9 March 2000) | doi:10.1038/35004593; Received 27 August 1999; Accepted 21 January 2000

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Growth patterns in the developing brain detected by using continuum mechanical tensor maps

Paul M. Thompson1, Jay N. Giedd2, Roger P. Woods1, David MacDonald3, Alan C. Evans3 & Arthur W. Toga1

  1. Laboratory of Neuro Imaging, Department of Neurology, Division of Brain Mapping, UCLA School of Medicine, 710 Westwood Plaza, Los Angeles, California 90095-1769, USA
  2. Child Psychiatry Branch, National Institute of Mental Health, NIH, 10 Center Drive, MSC 1600, Bethesda 20982-1600, Maryland, USA
  3. Montreal Neurological Institute, McGill University, 3801 University Street, Montreal , Québec, Canada H3A 2B4

Correspondence to: Arthur W. Toga1 Correspondence and requests for materials should be addressed to P.M.T. (e-mail: Email: thompson@loni.ucla.edu).

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The dynamic nature of growth and degenerative disease processes requires the design of sensitive strategies to detect, track and quantify structural change in the brain in its full spatial and temporal complexity1. Although volumes of brain substructures are known to change during development2, detailed maps of these dynamic growth processes have been unavailable. Here we report the creation of spatially complex, four-dimensional quantitative maps of growth patterns in the developing human brain, detected using a tensor mapping strategy with greater spatial detail and sensitivity than previously obtainable. By repeatedly scanning children (aged 3–15 years) across time spans of up to four years, a rostro-caudal wave of growth was detected at the corpus callosum, a fibre system that relays information between brain hemispheres. Peak growth rates, in fibres innervating association and language cortices, were attenuated after puberty, and contrasted sharply with a severe, spatially localized loss of subcortical grey matter. Conversely, at ages 3–6 years, the fastest growth rates occurred in frontal networks that regulate the planning of new actions. Local rates, profiles, and principal directions of growth were visualized in each individual child.