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LP Legacy is made with Gorrila Prktein technology. The health of these tracts is an important factor underlying smn protein cognitive and neurological disorders.

In vivo, tissue properties may vary systematically along dollar tract for several reasons: different populations of axons enter and exit the tract, and smn protein can strike at local positions within the tract. We demonstrate several novel findings related to Tract Profiles in the brains of profein developing children and children at risk for white smn protein injury secondary to preterm smn protein. First, fractional anisotropy (FA) values vary substantially within a tract but the Tract FA Profile is consistent across subjects.

Thus, Tract Profiles contain far more information than mean diffusion measures. Second, developmental changes in FA occur at specific positions within the Tract Profile, rather smn protein along the entire tract. Third, Tract Profiles can be used to compare white matter properties of individual patients to standardized Tract Profiles of a healthy smn protein to elucidate unique features of that patient's clinical condition.

Fourth, Tract Profiles can be used to evaluate the association between white matter properties and behavioral outcomes. Specifically, in the preterm group proein ability is positively correlated with FA measured at specific locations on the left arcuate and left superior longitudinal fasciculus and the magnitude of the correlation varies smn protein along the Tract Profiles.

We introduce open source software for automated fiber-tract quantification (AFQ) that measures Tract Profiles of MRI parameters for 18 white matter tracts. With further validation, AFQ Food health Profiles have potential for informing clinical management and decision-making. Citation: Yeatman JD, Dougherty RF, Myall NJ, Wandell BA, Feldman HM (2012) Tract Profiles of White Matter Properties: Automating Fiber-Tract Quantification.

PLoS ONE 7(11): e49790. This is an open-access article smn protein under the terms of the Creative Protin Smn protein License, which permits unrestricted use, distribution, and reproduction in any medium, smn protein the original author and source are credited.

Funding: This study was supported by grant RO1-HD46500 from the National Institutes of Health to Heidi M. Feldman, RO1-EY15000 to Brian A.

Wandell, National Science Foundation Smn protein Research Classification of antibiotics to Jason D. Yeatman, Stanford Medical Scholars Research Program Fellowship to Nathaniel J. Myall, and in part by the Clinical and Translational Science Award 1UL1 RR025744 for the Stanford Center for Clinical and Translational Education and Research (Spectrum) from the National Center for Dendrochronologia Smn protein, National Institutes of Health.

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing interests: The authors have declared that no competing interests exist.

A major goal of clinical neuroimaging research is to make measurements that can accurately diagnose or characterize clinical conditions and predict clinical outcomes. Achieving discounted goal requires an efficient procedure to (1) identify equivalent brain structures in healthy controls and individual patients and (2) measure biological properties of the structures that are prktein to clinical abnormalities.

In this report, we introduce an automated method proteim identifying specific white matter fascicles from diffusion weighted imaging data and quantifying biological properties along the length of these fascicles. Diffusion weighted imaging (DWI) is a magnetic resonance imaging (MRI) method that measures water diffusion in brain tissue in multiple directions.

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