Previous neuroimaging research has documented that patterns of intrinsic (resting state) functional connectivity (FC) among brain regions covary with individual measures of cognitive performance. Here, we examined the relation between intrinsic FC and a reaction time (RT) measure of performance, as a function of age group and task demands. We obtained filtered, event-related functional magnetic resonance imaging data, and RT measures of visual search performance, from 21 younger adults (19-29 years old) and 21 healthy, older adults (60-87 years old). Age-related decline occurred in the connectivity strength in multiple brain regions, consistent with previous findings. Among 8 pairs of regions, across somatomotor, orbitofrontal, and subcortical networks, increasing FC was associated with faster responding (lower RT). Relative to younger adults, older adults exhibited a lower strength of this RT-connectivity relation and greater disruption of this relation by a salient but irrelevant display item (color singleton distractor). Age-related differences in the covariation of intrinsic FC and cognitive performance vary as a function of task demands.
Connectivity mapping based on resting-state fMRI is rapidly developing, and this methodology has great potential for clinical applications. However, before resting-state fMRI can be applied for diagnosis, prognosis, and monitoring treatment for an individual patient with neurologic or psychiatric diseases, it is essential to assess its long-term reproducibility and between-subject variations among healthy individuals. The purpose of the study was to quantify the long-term test-retest reproducibility of ICN measures derived from resting-state fMRI and to assess the between-subject variation of ICN measures across the whole brain.
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.
