Functional diffusion tensor imaging: Measuring task-related fractional anisotropy changes in the human brain along white matter tracts

René C.W. Mandl, Hugo G. Schnack, Marcel P. Zwiers, Arjen van der Schaaf, René S. Kahn, Hilleke E. Hulshoff Pol

Research output: Contribution to journalArticlepeer-review

58 Scopus citations

Abstract

Background: Functional neural networks in the human brain can be studied from correlations between activated gray matter regions measured with fMRI. However, while providing important information on gray matter activation, no information is gathered on the co-activity along white matter tracts in neural networks. Methodology/Principal Findings: We report on a functional diffusion tensor imaging (fDTI) method that measures task-related changes in fractional anisotropy (FA) along white matter tracts. We hypothesize that these fractional anisotropy changes relate to morphological changes of glial cells induced by axonal activity although the exact physiological underpinnings of the measured FA changes remain to be elucidated. As expected, these changes are very small as compared to the physiological noise and a reliable detection of the signal change would require a large number of measurements. However, a substantial increase in signal-to-noise ratio was achieved by pooling the signal over the complete fiber tract. Adopting such a tract-based statistics enabled us to measure the signal within a practically feasible time period. Activation in the sensory thalamocortical tract and optic radiation in eight healthy human subjects was found during tactile and visual stimulation, respectively. Conclusions/Significance: The results of our experiments indicate that these FA changes may serve as a functional contrast mechanism for white matter. This noninvasive fDTI method may provide a new approach to study functional neural networks in the human brain.

Original languageEnglish
Article numbere3631
JournalPLoS ONE
Volume3
Issue number11
DOIs
StatePublished - 4 Nov 2008
Externally publishedYes

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