Diffusion Tensor Imaging (DTI)

Diffusion Tensor Imaging (DTI) is a Magnetic Resonance Imaging‑based neuroimaging technique that makes it possible to estimate the location, orientation, and anisotropy of the white matter tracts of the brain.

In NTR projects YC_BS1, YC_BS2, and YC_BS3, a whole-head MRI scan was acquired with a 1.5 Tesla Philips Achieva scanner (Philips, Best, The Netherlands, for protocol details see: https://doi.org/10.1017/thg.2012.4; https://doi.org/10.1002/hbm.22988; https://doi.org/10.1016/j.neuroimage.2019.116073).

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Keywords
Constructs
Waves
  • Young Netherlands Twin Register

  • YC_BS1
    •   C S
    9.0 years   From 2005-01-01 to 2005-01-01
  • YC_BS2
    •   C S
    12.0 years   From 2007-01-01 to 2009-01-01
  • YC_BS3
    •   C S
    17.0 years   From 2012-01-01 to 2014-01-01
    Mode of collection MeasurementsAndTests    MRI
    Analysis unit Individual
    References
    van Soelen, I. L. C., Brouwer, R. M., Peper, J. S., van Leeuwen, M., Koenis, M. M. G., van Beijsterveldt, T. C. E. M., Swagerman, S. C., Kahn, R. S., Hulshoff Pol, H. E., & Boomsma, D. I. (2012). Brain SCALE: Brain Structure and Cognition: an Adolescent Longitudinal Twin Study into the Genetic Etiology of Individual Differences. Twin Research and Human Genetics, 15(3), 453–467. https://doi.org/10.1017/thg.2012.4
    Koenis, M. M. G., Brouwer, R. M., van den Heuvel, M. P., Mandl, R. C. W., van Soelen, I. L. C., Kahn, R. S., Boomsma, D. I., & Hulshoff Pol, H. E. (2015). Development of the brain’s structural network efficiency in early adolescence: A longitudinal<scp>DTI</scp>twin study. Human Brain Mapping, 36(12), 4938–4953. Portico. https://doi.org/10.1002/hbm.22988
    Teeuw, J., Brouwer, R. M., Guimarães, J. P. O. F. T., Brandner, P., Koenis, M. M. G., Swagerman, S. C., Verwoert, M., Boomsma, D. I., & Hulshoff Pol, H. E. (2019). Genetic and environmental influences on functional connectivity within and between canonical cortical resting-state networks throughout adolescent development in boys and girls. NeuroImage, 202, 116073. https://doi.org/10.1016/j.neuroimage.2019.116073
    You can also access this dataset using the API (see API Docs).