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Diffusion Tensor Imaging (DTI) and Tractography

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Neuroeconomics

Abstract

Diffusion Tensor Imaging is a Magnet Resonance Imaging-technique that allows for the non-invasive in vivo assessment and delineation of white matter tracts. The Magnet Resonance signal is sensitized to the natural diffusion process of protons and a tensor model is fitted to the resulting data. By following the direction of the diffusion maximum across the brain, the process of tractography yields three-dimensional reconstructions of white matter tracts, which may be microstructurally analyzed by means of diffusivity parameters. Before the advent of Diffusion Tensor Imaging, studies of connectional anatomy in humans could only be conducted post-mortem. Diffusion Tensor Imaging has shifted neuroscientific attention from single brain regions to the networks connecting them. This, however, has not only extended our knowledge on brain networks but also on single loci being part of these networks. Although the biological substrates of Diffusion Tensor Imaging-derived parameters remain unclear to a certain extent, Diffusion Tensor Imaging and tractography have successfully informed many studies in the field of age- or training-related neuronal changes. In addition, it has been found to be applicable in clinical settings. However, Diffusion Tensor Imaging studies covering the fields of neuroeconomics and behavioral psychology are sparse. Two pioneer studies from these fields have successfully related personality characteristics of interest to Diffusion Tensor Imaging- and tractography-derived measures. This chapter tries to give an introduction to the mechanisms of Diffusion Tensor Imaging and will work to explain its utilization while highlighting limitations of Diffusion Tensor Imaging as well as examples of its successful applications.

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Correspondence to Theodor Rüber .

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Rüber, T., Elger, C.E., Weber, B. (2016). Diffusion Tensor Imaging (DTI) and Tractography. In: Reuter, M., Montag, C. (eds) Neuroeconomics. Studies in Neuroscience, Psychology and Behavioral Economics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35923-1_22

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