Mapping fine-scale anatomy of gray matter, white matter, and trigeminal-root region applying spherical deconvolution to high-resolution 7-T diffusion MRI.

OBJECTIVES: We assessed the use of high-resolution ultra-high-field diffusion magnetic resonance imaging (dMRI) to determine neuronal fiber orientation density functions (fODFs) throughout the human brain, including gray matter (GM), white matter (WM), and small intertwined structures in the cerebellopontine region. MATERIALS AND METHODS: We acquired 7-T whole-brain dMRI data of 23 volunteers with 1.4-mm isotropic resolution; fODFs were estimated using constrained spherical deconvolution. RESULTS: High-resolution fODFs enabled a detailed view of the intravoxel distributions of fiber populations in the whole brain. In the brainstem region, the fODF of the extra- and intrapontine parts of the trigeminus could be resolved. Intrapontine trigeminal fiber populations were crossed in a network-like fashion by fiber populations of the surrounding cerebellopontine tracts. In cortical GM, additional evidence was found that in parts of primary somatosensory cortex, fODFs seem to be oriented less perpendicular to the cortical surface than in GM of motor, premotor, and secondary somatosensory cortices. CONCLUSION: With 7-T MRI being introduced into clinical routine, high-resolution dMRI and derived measures such as fODFs can serve to characterize fine-scale anatomic structures as a prerequisite to detecting pathologies in GM and small or intertwined WM tracts.

Increasing the spatial resolution and sensitivity of magnetic resonance elastography by correcting for subject motion and susceptibility-induced image distortions.

PURPOSE: To improve the resolution of elasticity maps by adapting motion and distortion correction methods for phase-based magnetic resonance imaging (MRI) contrasts such as magnetic resonance elastography (MRE), a technique for measuring mechanical tissue properties in vivo. MATERIALS AND METHODS: MRE data of the brain were acquired with echo-planar imaging (EPI) at 3T (n = 14) and 7T (n = 18). Motion and distortion correction parameters were estimated using the magnitude images. The real and imaginary part of the complex MRE data were corrected separately and recombined. The width of the point-spread function (PSF) and the position variability were calculated. The images were normalized to the Montreal Neurological Institute (MNI) anatomical template. The gray-to-white matter separability of the elasticity maps was tested. RESULTS: Motion correction sharpened the |G*| maps as demonstrated by a narrowing of the PSF by 0.78 ± 0.51 mm at 7T and 0.52 ± 0.63 mm at 3T. The amount of individual head motion during MRE acquisition correlated with the decrease in the width of the PSF at 7T (r = 0.53, P = 0.025) and at 3T (r = 0.69, P = 0.006) and with the increase of gray-to-white matter separability after motion correction at 7T (r = 0.64, P = 0.0039) and at 3T (r = 0.57, P = 0.0319). Improved spatial accuracy after distortion correction results in a significant increase in separability of gray and white matter stiffness (P = 0.0067), especially in inferior parts of the brain suffering from strong B0 inhomogeneities. CONCLUSION: We demonstrate that our method leads to sharper images and higher spatial accuracy, raising the prospect of the investigation of smaller brain areas with increased sensitivity in studies using MRE. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:134-141.

High-resolution mechanical imaging of the human brain by three-dimensional multifrequency magnetic resonance elastography at 7T.

Magnetic resonance elastography (MRE) is capable of measuring the viscoelastic properties of brain tissue in vivo. However, MRE is still limited in providing high-resolution maps of mechanical constants. We therefore introduce 3D multifrequency MRE (3DMMRE) at 7T magnetic field strength combined with enhanced multifrequency dual elasto-visco (MDEV) inversion in order to achieve high-resolution elastographic maps of in vivo brain tissue with 1mm(3) resolution. As demonstrated by phantom data, the new MDEV-inversion method provides two high resolution parameter maps of the magnitude (|G*|) and the phase angle (ϕ) of the complex shear modulus. MDEV inversion applied to cerebral 7T-3DMMRE data of five healthy volunteers revealed structures of brain tissue in greater anatomical details than previous work. The viscoelastic properties of cortical gray matter (GM) and white matter (WM) could be differentiated by significantly lower values of |G*| and ϕ in GM (21% [P<0.01]; 8%, [P<0.01], respectively) suggesting that GM is significantly softer and less viscous than WM. In conclusion, 3DMMRE at ultrahigh magnetic fields and MDEV inversion open a new window into characterizing the mechanical structure of in vivo brain tissue and may aid the detection of various neurological disorders based on their effects to mechanical tissue properties.

Slice accelerated diffusion-weighted imaging at ultra-high field strength.

PURPOSE: Diffusion magnetic resonance imaging (dMRI) data with very high isotropic resolution can be obtained at 7T. However, for extensive brain coverage, a large number of slices is required, resulting in long acquisition times (TAs). Recording multiple slices simultaneously (SMS) promises to reduce the TA. METHODS: A combination of zoomed and parallel imaging is used to achieve high isotropic resolution dMRI data with a low level of distortions at 7T. The blipped-CAIPI (controlled aliasing in parallel imaging) approach is used to acquire several slices simultaneously. Due to their high radiofrequency (RF) power deposition and ensuing specific absorption rate (SAR) constraints, the commonly used multiband (MB) RF pulses for SMS imaging are inefficient at 7T and entail long repetition times, counteracting the usefulness of SMS acquisitions. To address this issue, low SAR multislice Power Independent of Number of Slices RF pulses are employed. RESULTS: In vivo dMRI results with and without SMS acceleration are presented at different isotropic spatial resolutions at ultra high field strength. The datasets are recorded at a high angular resolution to detect fiber crossings. CONCLUSION: From the results and compared with earlier studies at these resolutions, it can be seen that scan time is significantly reduced, while image quality is preserved.

Event-related functional magnetic resonance imaging (efMRI) of depth-by-disparity perception: additional evidence for right-hemispheric lateralization.

In natural environments depth-related information has to be extracted very fast from binocular disparity even if cues are presented shortly. However, few studies used efMRI to study depth perception. We therefore analyzed extension and localization of activation evoked by depth-by-disparity stimuli that were displayed for 1 s. As some clinical as well as neuroimaging studies had found a right-hemispheric lateralization of depth perception the sample size was increased to 26 subjects to gain higher statistical significance. All individuals reported a stable depth perception. In the random effects analysis the maximum activation of the disparity versus no disparity condition was highly significant and located in the extra-striate cortex, presumably in V3A (P < 0.05, family wise error). The activation was more pronounced in the right hemisphere. However, in the single-subject analysis depth-related right-hemispheric lateralization was observed only in 65% of the subjects. Lateralization of depth-by-disparity may therefore be obscured in smaller groups.

Enabling of grid based diffusion tensor imaging using a workflow implementation of FSL.

Tensor analysis of diffusion weighted magnetic resonance images is increasingly used for non-invasive tracking of nerve fibers in the human brain. Diffusion-tensor imaging (DTI) enables in-vivo research on the internal structure of the central nervous system, encompassing interconnection of functional areas, correlation between fiber deformations and certain disease patterns, as well as brain tumor localization. But the modeling of the local diffusion parameters is a computationally expensive part of the processing pipeline, resulting to run times up to days on standard desktop computers. A grid implementation of the algorithm with slice based parallelization reduces the processing down to 10% compared to a local cluster and 20% compared to sequential processing on the grid. A workflow implementation enables fault-tolerant handling of temporary failures within the grid. Furthermore, pure web-based access to the grid application allows for collaborative utilization even from protected infrastructures, as they are typically found in clinical environments.

A proof-of-principle study of multi-site real-time functional imaging at 3T and 7T: Implementation and validation.

Real-time functional Magnetic Resonance Imaging (rtfMRI) is used mainly for neurofeedback or for brain-computer interfaces (BCI). But multi-site rtfMRI could in fact help in the application of new interactive paradigms such as the monitoring of mutual information flow or the controlling of objects in shared virtual environments. For that reason, a previously developed framework that provided an integrated control and data analysis of rtfMRI experiments was extended to enable multi-site rtfMRI. Important new components included a data exchange platform for analyzing the data of both MR scanners independently and/or jointly. Information related to brain activation can be displayed separately or in a shared view. However, a signal calibration procedure had to be developed and integrated in order to permit the connecting of sites that had different hardware and to account for different inter-individual brain activation levels. The framework was successfully validated in a proof-of-principle study with twelve volunteers. Thus the overall concept, the calibration of grossly differing signals, and BCI functionality on each site proved to work as required. To model interactions between brains in real-time, more complex rules utilizing mutual activation patterns could easily be implemented to allow for new kinds of social fMRI experiments.

Structural brain alterations in patients with lumbar disc herniation: a preliminary study.

Chronic pain is one of the most common health complaints in industrial nations. For example, chronic low back pain (cLBP) disables millions of people across the world and generates a tremendous economic burden. While previous studies provided evidence of widespread functional as well as structural brain alterations in chronic pain, little is known about cortical changes in patients suffering from lumbar disc herniation. We investigated morphometric alterations of the gray and white matter of the brain in patients suffering from LDH. The volumes of the gray and white matter of 12 LDH patients were determined in a prospective study and compared to the volumes of healthy controls to distinguish local differences. High-resolution MRI brain images of all participants were performed using a 3 Tesla MRI scanner. Voxel-based morphometry was used to investigate local differences in gray and white matter volume between patients suffering from LDH and healthy controls. LDH patients showed significantly reduced gray matter volume in the right anterolateral prefrontal cortex, the right temporal lobe, the left premotor cortex, the right caudate nucleus, and the right cerebellum as compared to healthy controls. Increased gray matter volume, however, was found in the right dorsal anterior cingulate cortex, the left precuneal cortex, the left fusiform gyrus, and the right brainstem. Additionally, small subcortical decreases of the white matter were found adjacent to the left prefrontal cortex, the right premotor cortex and in the anterior limb of the left internal capsule. We conclude that the lumbar disk herniation can lead to specific local alterations of the gray and white matter in the human brain. The investigation of LDH-induced brain alterations could provide further insight into the underlying nature of the chronification processes and could possibly identify prognostic factors that may improve the conservative as well as the operative treatment of the LDH.

Ethanol modulates the neurovascular coupling.

Despite some evidence of the underlying molecular mechanisms the neuronal basis of ethanol-induced effects on the neurovascular coupling that forms the BOLD (blood oxygenation level dependent) signal is poorly understood. In a recent fMRI (functional magnetic resonance imaging) study monitoring ethanol-induced changes of the BOLD signal a reduction of the amplitude and a prolongation of the BOLD signal were observed. However, the BOLD signal is assumed to consist of a complex superposition of different underlying signals. To gain insight how ethanol influences stimulus efficacy, oxygen extraction, transit time and vessel-related parameters the fMRI time series from the sensori-motor and the visual cortex were analyzed using the balloon model. The results show a region-dependent decrease of the stimulus efficacy to trigger a post-stimulus neurovascular response as well as a prolongation of the transit time through the venous compartment. Oxygen extraction, feedback mechanisms and other vessel-related parameters were not affected. The results may be interpreted as follows: the overall mechanisms of the neurovascular coupling are still acting well at the moderate ethanol level of about 0.8‰ (in particular the vessel-related parts), but the potency to evoke a neurovascular response is already compromised most obviously in the supplementary motor area responsible for complex synchronizing and planning processes.

Decreased effective connectivity in the visuomotor system after alcohol consumption.

Functional magnetic resonance imaging (fMRI) allows observing cerebral activity not only in separated cortical regions but also in functionally coupled cortical networks. Although moderate doses of ethanol slowdown the neurovascular coupling, the functions of the primary sensorimotor and the visual system remain intact. Yet little is known about how more complex interactions between cortical regions are affected even at moderate doses of alcohol. Therefore the method of psychophysiological interaction (PPI) was applied to analyze ethanol-induced effects on the effective connectivity in the visuomotor system. Fourteen healthy social drinkers with no personal history of neurological disorders or substance abuse were examined. In a test/re-test design they served as their own controls by participating in both the sober and the ethanol condition. All participants were scanned in a 3 T MR scanner before and after ingestion of a body-weight-dependent amount of ethanol calculated to achieve a blood alcohol concentration of 1.0‰. PPIs were calculated for the primary visual cortex, the supplementary motor area, and the left and right primary motor cortex using the statistical software package SPM. The PPI analysis showed selective disturbance of the effective connectivity between different cortical areas. The regression analysis revealed the influence of the supplementary motor area on connected regions like the primary motor cortex to be decreased yet preserved. However, the connection between the primary visual cortex and the posterior parietal cortex was more severely impaired by the influence of ethanol, leading to an uncoupled regression between these regions. The decreased effective connectivity in the visuomotor system suggests that complex tasks requiring interaction or synchronization between different brain areas are affected even at moderate levels of alcohol. This finding may have important consequences for determining which components of demanding tasks such as driving a car might be compromised earlier than the functions of the main cortical motor and visual areas.

Tactile motion and pattern processing assessed with high-field FMRI.

Processing of motion and pattern has been extensively studied in the visual domain, but much less in the somatosensory system. Here, we used ultra-high-field functional magnetic resonance imaging (fMRI) at 7 Tesla to investigate the neuronal correlates of tactile motion and pattern processing in humans under tightly controlled stimulation conditions. Different types of dynamic stimuli created the sensation of moving or stationary bar patterns during passive touch. Activity in somatosensory cortex was increased during both motion and pattern processing and modulated by motion directionality in primary and secondary somatosensory cortices (SI and SII) as well as by pattern orientation in the anterior intraparietal sulcus. Furthermore, tactile motion and pattern processing induced activity in the middle temporal cortex (hMT+/V5) and in the inferior parietal cortex (IPC), involving parts of the supramarginal und angular gyri. These responses covaried with subjects' individual perceptual performance, suggesting that hMT+/V5 and IPC contribute to conscious perception of specific tactile stimulus features. In addition, an analysis of effective connectivity using psychophysiological interactions (PPI) revealed increased functional coupling between SI and hMT+/V5 during motion processing, as well as between SI and IPC during pattern processing. This connectivity pattern provides evidence for the direct engagement of these specialized cortical areas in tactile processing during somesthesis.

Predicting decisions in human social interactions using real-time fMRI and pattern classification.

Negotiation and trade typically require a mutual interaction while simultaneously resting in uncertainty which decision the partner ultimately will make at the end of the process. Assessing already during the negotiation in which direction one's counterpart tends would provide a tremendous advantage. Recently, neuroimaging techniques combined with multivariate pattern classification of the acquired data have made it possible to discriminate subjective states of mind on the basis of their neuronal activation signature. However, to enable an online-assessment of the participant's mind state both approaches need to be extended to a real-time technique. By combining real-time functional magnetic resonance imaging (fMRI) and online pattern classification techniques, we show that it is possible to predict human behavior during social interaction before the interacting partner communicates a specific decision. Average accuracy reached approximately 70% when we predicted online the decisions of volunteers playing the ultimatum game, a well-known paradigm in economic game theory. Our results demonstrate the successful online analysis of complex emotional and cognitive states using real-time fMRI, which will enable a major breakthrough for social fMRI by providing information about mental states of partners already during the mutual interaction. Interestingly, an additional whole brain classification across subjects confirmed the online results: anterior insula, ventral striatum, and lateral orbitofrontal cortex, known to act in emotional self-regulation and reward processing for adjustment of behavior, appeared to be strong determinants of later overt behavior in the ultimatum game. Using whole brain classification we were also able to discriminate between brain processes related to subjective emotional and motivational states and brain processes related to the evaluation of objective financial incentives.