In diffusion tensor imaging (DTI), spatial and temporal variations of the static magnetic field (B(0)) caused by susceptibility effects and time-varying eddy currents result in severe distortions, blurring, and misregistration artifacts, which in turn lead to errors in DTI metrics and in fiber tractography. Various correction methods have been proposed, but typically assume that the eddy current-induced magnetic field can be modeled as a constant or a single exponential decay within the DTI readout window. Here, we show that its temporal dependence is more complex because of the interaction of multiple eddy currents with different time constants, but that it remains very consistent over time. As such, we propose a novel dynamic B(0) mapping and off-resonance correction method that measures the exact spatial, temporal, and diffusion-weighting direction dependence of the susceptibility- and eddy current-induced magnetic fields to effectively and efficiently correct for artifacts caused by both susceptibility effects and time-varying eddy currents, thereby resulting in a high spatial fidelity and accuracy.
Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive neuromodulation technique that has been used to treat neurological and psychiatric conditions. Although results of rTMS intervention are promising, so far, little is known about the rTMS effect on brain functional networks in clinical populations. In this study, we used a whole-brain connectivity analysis of resting-state functional magnetic resonance imaging data to uncover changes in functional connectivity following rTMS intervention and their association with motor symptoms in patients with multiple system atrophy (MSA). Patients were randomized to active rTMS or sham rTMS groups and completed a 10-session 5-Hz rTMS treatment over the left primary motor area. The results showed significant rTMS-related changes in motor symptoms and functional connectivity. Specifically, (1) significant improvement of motor symptoms was observed in the active rTMS group, but not in the sham rTMS group; and (2) several functional links involving the default mode, cerebellar, and limbic networks exhibited positive changes in functional connectivity in the active rTMS group. Moreover, the positive changes in functional connectivity were associated with improvement in motor symptoms for the active rTMS group. The present findings suggest that rTMS may improve motor symptoms by modulating functional links connecting to the default mode, cerebellar, and limbic networks, inferring a future therapeutic candidate for patients with MSA.
Age-related macular degeneration (AMD), the leading cause of blindness in developed nations, has been associated with poor performance on tests of phonemic fluency. This pilot study sought to (1) characterize the relationship between phonemic fluency and resting-state functional brain connectivity in AMD patients and (2) determine whether regional connections associated with phonemic fluency in AMD patients were similarly linked to phonemic fluency in healthy participants. Behavior-based connectivity analysis was applied to resting-state, functional magnetic resonance imaging data from seven patients (mean age=79.9±7.5 years) with bilateral AMD who completed fluency tasks prior to imaging. Phonemic fluency was inversely related to the strength of functional connectivity (FC) among six pairs of brain regions, representing eight nodes: left opercular portion of inferior frontal gyrus (which includes Broca's area), left superior temporal gyrus (which includes part of Wernicke's area), inferior parietal lobe (bilaterally), right superior parietal lobe, right supramarginal gyrus, right supplementary motor area, and right precentral gyrus. The FC of these reference links was not related to phonemic fluency among 32 healthy individuals (16 younger adults, mean age=23.5±4.6 years and 16 older adults, mean age=68.3±3.4 years). Compared with healthy individuals, AMD patients exhibited higher mean connectivity within the reference links and within the default mode network, possibly reflecting compensatory changes to support performance in the setting of reduced vision. These findings are consistent with the hypothesis that phonemic fluency deficits in AMD reflect underlying brain changes that develop in the context of AMD.
Age-related decline in fluid cognition can be characterized as a disconnection among specific brain structures, leading to a decline in functional efficiency. The potential sources of disconnection, however, are unclear. We investigated imaging measures of cerebral white-matter integrity, resting-state functional connectivity, and white-matter hyperintensity volume as mediators of the relation between age and fluid cognition, in 145 healthy, community-dwelling adults 19-79 years of age. At a general level of analysis, with a single composite measure of fluid cognition and single measures of each of the 3 imaging modalities, age exhibited an independent influence on the cognitive and imaging measures, and the imaging variables did not mediate the age-cognition relation. At a more specific level of analysis, resting-state functional connectivity of sensorimotor networks was a significant mediator of the age-related decline in executive function. These findings suggest that different levels of analysis lead to different models of neurocognitive disconnection, and that resting-state functional connectivity, in particular, may contribute to age-related decline in executive function.
The partial Fourier gradient-echo echo planar imaging (EPI) technique makes it possible to acquire high-resolution functional MRI (fMRI) data at an optimal echo time. This technique is especially important for fMRI studies at high magnetic fields, where the optimal echo time is short and may not be achieved with a full Fourier acquisition scheme. In addition, it has been shown that partial Fourier EPI provides better anatomic resolvability than full Fourier EPI. However, the partial Fourier gradient-echo EPI may be degraded by artifacts that are not usually seen in other types of imaging. Those unique artifacts in partial Fourier gradient-echo EPI, to our knowledge, have not yet been systematically evaluated. Here we use the k-space energy spectrum analysis method to understand and characterize two types of partial Fourier EPI artifacts. Our studies show that Type 1 artifact, originating from k-space energy loss, cannot be corrected with pure postprocessing, and Type 2 artifact can be eliminated with an improved reconstruction method. We propose a novel algorithm, that combines images obtained from two or more reconstruction schemes guided by k-space energy spectrum analysis, to generate partial Fourier EPI with greatly reduced Type 2 artifact. Quality control procedures for avoiding Type 1 artifact in partial Fourier EPI are also discussed.
