Fast functional brain signal changes detected by diffusion weighted fMRI.
Functional magnetic resonance imaging (fMRI) has become the method of choice in the study of system neuroscience, as evidenced by an explosion of such literature in the past decade. Contrast mechanisms based on the blood oxygenation level, volume, and flow changes have been used to non-invasively detect brain activation secondary to the neuronal activity. However, because of the hemodynamic modulations inherent in these signals, their spatial and temporal characteristics are influenced by the complex geometry and varying delivery speed of the brain vasculature. Consequently, spatial dispersions and temporal delays are commonly seen in the brain activity using fMRI. It is thus of critical importance to investigate alternative contrast mechanisms that may offer shorter temporal delays and more direct spatial localization. In light of a recent phantom study which demonstrated the possibility to detect the destructive phase addition from the spatially incoherent, yet temporally synchronized, displacements caused by the Lorentz force experienced during electrical conduction within a strong magnetic field, we seek to apply similar imaging technique to investigate the functional signal changes that may provide alternative temporal and spatial characteristics. It is found that by using heavy diffusion weighting, which is one form of displacement encoding strategies, to remove the vascular signal and sensitize the minute and incoherent displacement, one can detect fast dynamic signal changes synchronized to the task. This finding may help take an initial step toward direct non-invasive MRI detection of the neuronal activity with improved temporal accuracy.
Li
Tianlu
T
Brain Imaging and Analysis Center, Duke University, Durham, NC 27710, USA.
Song
Allen W
AW
D000328:Adult; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping; D038524:Diffusion Magnetic Resonance Imaging; D006801:Humans; D009044:Motor Cortex / Q000502:physiology