The ionic DTI model (iDTI) of dynamic diffusion tensor imaging (dDTI)

Autor: Leoncio Garrido, Gregory P. Gasic, Nikos Makris
Rok vydání: 2014
Předmět:
Zdroj: MethodsX
Digital.CSIC. Repositorio Institucional del CSIC
instname
MethodsX, Vol 1, Iss C, Pp 217-224 (2014)
Popis: Measurements of water molecule diffusion along fiber tracts in CNS by diffusion tensor imaging (DTI) provides a static map of neural connections between brain centers, but does not capture the electrical activity along axons for these fiber tracts. Here, a modification of the DTI method is presented to enable the mapping of active fibers. It is termed dynamic diffusion tensor imaging (dDTI) and is based on a hypothesized >anisotropy reduction due to axonal excitation> (>AREX>). The potential changes in water mobility accompanying the movement of ions during the propagation of action potentials along axonal tracts are taken into account. Specifically, the proposed model, termed >ionic DTI model>, was formulated as follows.First, based on theoretical calculations, we calculated the molecular water flow accompanying the ionic flow perpendicular to the principal axis of fiber tracts produced by electrical conduction along excited myelinated and non-myelinated axons.Based on the changes in molecular water flow we estimated the signal changes as well as the changes in fractional anisotropy of axonal tracts while performing a functional task.The variation of fractional anisotropy in axonal tracts could allow mapping the active fiber tracts during a functional task. Although technological advances are necessary to enable the robust and routine measurement of this electrical activity-dependent movement of water molecules perpendicular to axons, the proposed model of dDTI defines the vectorial parameters that will need to be measured to bring this much needed technique to fruition.
This work was done in part by funding for Nikos Makris by NIH-NIDAR01DA027804,NIH-NDSR21NS077059, and for Leoncio Garrido by Ministerio de Economía e Innovación FIS-PI11/01436.
Databáze: OpenAIRE