fDTI
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fDTI is a conceptual evolution of Diffusion Tensor Imaging (DTI): the basic idea is to allow the visualisation of what happens in the white matter while a subject is executing a specific task, on the wave of the paradigm of a typical BOLD-fMRI experiment.
Indeed, the idea of an experimental protocol to allow the use of Diffusion techniques for functional purpose is taking place worldwide in different manner, such as dfMRI (see Links).
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[edit] Conceptual background
While fMRI takes into account blood oxygenation variations in the vessels,[1] DTI is a technique that allows the measurement of the behaviour of the molecules of water in an anisotropic mean.[2][3]
The two techniques can be applied separately on a same subject to identify the white matter bundles that connect separated functional areas on the cortex. Nevertheless, using this combination of the two techniques gives as result a certain number of bundles and does not allow to identify which fibers of the white matter are indeed responsible for signal transportation during a specific task. fDTI integrates fMRI and DTI to show the activity in the white matter bundles rather than in the vessels near the target neurons.
The first thing to be considered is the possibility that there is some kind of activity in the white matter that may be visible with MR techniques.
Speculations can be made on which one, among the phenomena that take place in transmitting an information to the cortex, could be seen with Diffusion MR techniques. For example, the presence of the action potential may interfere with the degrees of freedom of water molecules: this possibility finds a justification by the fact that a water molecule is a dipole and it can then interact with an electromagnetic wave. Another possible reason for temporary local FA changes is a variation in shape of the post-synaptic junction when a chemical information passes through that specific synapse: in this case, a kind of result should be found in correspondence of a synapse position, if there were any. The real cause of a variation in DTI signal while executing a task can still be considered as a topic on debate - as well as the following, of course.
Being Diffusion Tensor Imaging based on the evaluation of the mean free path of water molecules in a structured environment, a significant parameter to identify any temporary functional variations in a structured volume as the White Matter could be Fractional Anisotropy (FA). This parameter identifies the grade of spherical probability of diffusion of a molecule in the environment: being normalised, FA value 0 indicates a perfectly spherical distribution of probability, while FA value 1 indicates a completely definite direction of diffusion. Other parameters may be taken in consideration, as Mean Diffusivity (MD), Apparent Diffusion Coefficient (ADC), Linear, Planar or Spherical Index, and surely more.
[edit] References
- ^ Ogawa S., Lee T.M., Kay A.R., and Tank D.W. Brain magnetic resonance imaging with blood oxygenation”. Proceedings of the National Academy of Sciences USA, 1990, Vol. 87, pp. 9868-9872
- ^ Mori S, Baker,P. Diffusion Magnetic Resonance Imaging: Its Principle and Applications. The Anatomical Record (New Anat.), 1999, 257:102–109
- ^ Shimony J.S., McKinstry R.C., Akbudak E., Aronovitz J.A., Snyder A.Z., Lori N.F., Cull T.S., Conturo T.E. Quantitative Diffusion-Tensor Anisotropy Brain MR Imaging: Normative Human Data and Anatomic Analysis. Radiology, 1999; 212:770-783
- Coots A., Shi R., and Rosen A.D. Effect of a 0.5-T static magnetic field on conduction in guinea pig spinal cord. Journal of the Neurological Sciences, 2004, Jul 15; 222(1-2)
- Hu H. and Wu M. Action Potential Modulation of Neural Spin Networks Suggests Possible Role of Spin. NeuroQuantology, 2004 - Issue 4 - Page 309-317
- Della-Maggiore V., Chau W., Peres-Neto P.R., and McIntosh A.R. An Empirical Comparison of
- SPM Preprocessing Parameters to the Analysis of fMRI Data. NeuroImage, 2002, 17, 19–28
- Desjardins A.E., Kiehl K.A., and Liddle P. Removal of Confounding Effects of Global Signal in Functional MRI Analyses. NeuroImage, 2001, 13, 751–758
