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The boundaries between tissues with different magnetic susceptibilities generate inhomogeneities in the main magnetic field which change over time due to motion, respiration and system instabilities. The dynamically changing field can be measured from the phase of the fMRI data and corrected. However, methods for doing so need multi-echo data, time-consuming reference scans and/or involve error-prone processing steps, such as phase unwrapping, which are difficult to implement robustly on the MRI host. The improved dynamic distortion correction method we propose is based on the phase of the single-echo EPI data acquired for fMRI, phase offsets calculated from a triple-echo, bipolar reference scan of circa 3-10 s duration using a method which avoids the need for phase unwrapping and an additional correction derived from one EPI volume in which the readout direction is reversed. This Reverse-Encoded First Image and Low resoLution reference scan (REFILL) approach is shown to accurately measure B 0 as it changes due to shim, motion and respiration, even with large dynamic changes to the field at 7 T, where it led to a > 20% increase in time-series signal to noise ratio compared to data corrected with the classic static approach. fMRI results from REFILL-corrected data were free of stimulus-correlated distortion artefacts seen when data were corrected with static field mapping. The method is insensitive to shim changes and eddy current differences between the reference scan and the fMRI time series, and employs calculation steps that are simple and robust, allowing most data processing to be performed in real time on the scanner image reconstruction computer. These improvements make it feasible to routinely perform dynamic distortion correction in fMRI., (© 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Somatosensation is fundamental to our ability to sense our body and interact with the world. Our body is continuously sampling the environment using a variety of receptors tuned to different features, and this information is routed up to primary somatosensory cortex. Strikingly, the spatial organization of the peripheral receptors in the body are well maintained, with the resulting representation of the body in the brain being referred to as the somatosensory homunculus. Recent years have seen considerable advancements in the field of high-resolution fMRI, which have enabled an increasingly detailed examination of the organization and properties of this homunculus. Here we combined advanced imaging techniques at ultra-high field (7T) with a recently developed Bayesian population receptive field (pRF) modeling framework to examine pRF properties in primary somatosensory cortex. In each subject, vibrotactile stimulation of the fingertips (i.e., the peripheral mechanoreceptors) modulated the fMRI response along the post-central gyrus and these signals were used to estimate pRFs. We found the pRF center location estimates to be in accord with previous work as well as evidence of other properties in line with the underlying neurobiology. Specifically, as expected from the known properties of cortical magnification, we find a larger representation of the index finger compared to the other stimulated digits (middle, index, little). We also show evidence that the little finger is marked by the largest pRF sizes, and that pRF size increases from anterior to posterior regions of S1. The ability to estimate somatosensory pRFs in humans provides an unprecedented opportunity to examine the neural mechanisms underlying somatosensation and is critical for studying how the brain, body, and environment interact to inform perception and action., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Ultra-high field magnetic resonance imaging data obtained using a multi-echo gradient echo sequence has been shown to contain information on tissue microstructure. Quantitative assessment of water fraction, relaxation time and frequency shift using multi-compartment signal modelling may help improve our understanding of diseases and disorders affecting the human brain. In this study, we explored tissue microstructure information by analysing voxel compartment water fraction and frequency shifts derived from 7 T multi-echo gradient recalled echo MRI data. We aimed to test whether the parameters of a three compartment model could distinguish the normal cortex from the cortex affected by focal cortical dysplasia. We compartmentalised normal and dysplastic cortical regions in patients diagnosed with focal cortical dysplasia. We found the frequency shift parameter of the shortest T 2 ⁎ signal compartment to be sensitive to regions of dysplastic tissue. We conclude that mathematical modelling of echo time dependent gradient recalled echo MRI signals in patients with focal cortical dysplasia can potentially delineate cortical areas that have undergone microstructural changes in comparison to normal tissue., (Crown Copyright © 2019. Published by Elsevier Inc. All rights reserved.)

Quantitative susceptibility mapping (QSM) is based on magnetic resonance imaging (MRI) phase measurements and has gained broad interest because it yields relevant information on biological tissue properties, predominantly myelin, iron and calcium in vivo. Thereby, QSM can also reveal pathological changes of these key components in widespread diseases such as Parkinson's disease, Multiple Sclerosis, or hepatic iron overload. While the ill-posed field-to-source-inversion problem underlying QSM is conventionally assessed by the means of regularization techniques, we trained a fully convolutional deep neural network - DeepQSM - to directly invert the magnetic dipole kernel convolution. DeepQSM learned the physical forward problem using purely synthetic data and is capable of solving the ill-posed field-to-source inversion on in vivo MRI phase data. The magnetic susceptibility maps reconstructed by DeepQSM enable identification of deep brain substructures and provide information on their respective magnetic tissue properties. In summary, DeepQSM can invert the magnetic dipole kernel convolution and delivers robust solutions to this ill-posed problem., (Copyright © 2019 Elsevier Inc. All rights reserved.)

The nuclei of the basal ganglia pose a special problem for functional MRI, especially at ultra-high field, because T2* variations between different regions result in suboptimal BOLD sensitivity when using gradient-echo echo-planar imaging (EPI). Specifically, the iron-rich lentiform nucleus of the basal ganglia, including the putamen and globus pallidus, suffers from substantial signal loss when imaging is performed using conventional single-echo EPI with echo times optimized for the cortex. Multi-echo EPI acquires several echoes at different echo times for every imaging slice, allowing images to be reconstructed with a weighting of echo times that is optimized individually for each voxel according to the underlying tissue or T2* properties. Here we show that multi-echo simultaneous multi-slice (SMS) EPI can improve functional activation of iron-rich subcortical regions while maintaining sensitivity within cortical areas. Functional imaging during a motor task known to elicit strong activations in the cortex and the subcortex (basal ganglia) was performed to compare the performance of multi-echo SMS EPI to single-echo SMS EPI. Notably within both the caudate nucleus and putamen of the basal ganglia, multi-echo SMS EPI yielded higher tSNR (an average 84% increase) and CNR (an average 58% increase), an approximate 3-fold increase in supra-threshold voxels, and higher t-values (an average 39% increase). The degree of improvement in the group level t-statistics was negatively correlated to the underlying T2* of the voxels, such that the shorter the T2*, as in the iron-rich nuclei of the basal ganglia, the higher the improvement of t-values in the activated region., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Attention to sensory information has been shown to modulate the neuronal processing of that information. For example, visuospatial attention acts by modulating responses at retinotopically appropriate regions of visual cortex (Puckett and DeYoe, 2015; Tootell et al. 1998). Much less, however, is known about the neuronal processing associated with attending to other modalities of sensory information. One reason for this is that visual cortex is relatively large, and therefore easier to access non-invasively in humans using tools such as functional magnetic resonance imaging (fMRI). With high-resolution fMRI, however, it is now possible to access smaller cortical areas such as primary somatosensory cortex (Martuzzi et al., 2014; Sanchez-Panchuelo et al., 2010; Schweisfurth et al. 2014; Schweizer et al. 2008). Here, we combined a novel experimental design and high-resolution fMRI at ultra-high field (7T) to measure the effects of attention to tactile stimulation in primary somatosensory cortex, S1. We find that attention modulates somatotopically appropriate regions of S1, and importantly, that this modulation can be measured at the level of the cortical representation of individual fingertips., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Purpose: To develop a distortion correction method for echo planar imaging (EPI) that is able to measure dynamic changes in B 0 ., Theory and Methods: The approach we propose is based on single-echo EPI with a jittering of the echo time between two values for alternate time points. Field maps are calculated between phase images from adjacent volumes and are used to remove distortion from corresponding magnitude images. The performance of our approach was optimized using an analytical model and by comparison with field maps from dual-echo EPI. The method was tested in functional MRI experiments at 7T with motor tasks and compared with the conventional static approach., Results: Unwarping using our method was accurate even for head rotations up to 8.2°, where the static approach introduced errors up to 8.2 mm. Jittering the echo time between 19 and 25 ms had no measurable effect on blood oxygenation level-dependent (BOLD) sensitivity. Our approach reduced the distortions in activated regions to <1 mm and repositioned active voxels correctly., Conclusion: This method yields accurate distortion correction in the presence of motion. No reduction in BOLD sensitivity was observed. As such, it is suitable for application in a wide range of functional MRI experiments. Magn Reson Med 76:1388-1399, 2016. © 2015 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited., (© 2015 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.)

A multiband multi-echo (MBME) sequence is implemented and compared to a matched standard multi-echo (ME) protocol to investigate the potential improvement in sensitivity and spatial specificity at 7 T for resting state and task fMRI. ME acquisition is attractive because BOLD sensitivity is less affected by variation in T2*, and because of the potential for separating BOLD and non-BOLD signal components. MBME further reduces TR thus increasing the potential reduction in physiological noise. In this study we used FSL-FIX to clean ME and MBME resting state and task fMRI data (both 3.5mm isotropic). After noise correction, the detection of resting state networks improves with more non-artifactual independent components being observed. Additional activation clusters for task data are discovered for MBME data (increased sensitivity) whereas existing clusters become more localized for resting state (improved spatial specificity). The results obtained indicate that MBME is superior to ME at high field strengths., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Due to the availability of ultra-high field scanners and novel imaging methods, high resolution, whole brain functional MR imaging (fMRI) has become increasingly feasible. However, it is common to use extensive spatial smoothing to account for inter-subject anatomical variation when pooling over subjects. This reduces the spatial details of group level functional activation considerably, even when the original data was acquired with high resolution. In our study we used an accelerated 3D EPI sequence at 7 Tesla to acquire whole brain fMRI data with an isotropic spatial resolution of 1.1mm which shows clear gray/white matter contrast due to the stronger T1 weighting of 3D EPI. To benefit from the high spatial resolution on the group level, we develop a study specific, high resolution anatomical template which is facilitated by the good anatomical contrast that is present in the average functional EPI images. Different template generations with increasing accuracy were created by using a hierarchical linear and stepwise non-linear registration approach. As the template is based on the functional data themselves no additional co-registration step with the usual T1-weighted anatomical data is necessary which eliminates a potential source of misalignment. To test the improvement of functional localization and spatial details we performed a group level analysis of a finger tapping experiment in eight subjects. The most accurate template shows better spatial localization--such as a separation of somatosensory and motor areas and of single digit activation--compared to the simple linear registration. The number of activated voxels is increased by a factor of 1.2, 2.5, and 3.1 for somatosensory, supplementary motor area, and dentate nucleus, respectively, for the functional contrast between left versus right hand. Similarly, the number of activated voxels is increased 1.4- and 2.4-fold for right little versus right index finger and left little versus left index finger, respectively. The Euclidian distance between the activation (center of gravity) of the respective fingers was found to be 13.90 mm using the most accurate template., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Visual attention is used to selectively filter relevant information depending on current task demands and goals. Visual attention is called object-based attention when it is directed to coherent forms or objects in the visual field. This study used real-time functional magnetic resonance imaging for moment-to-moment decoding of attention to spatially overlapped objects belonging to two different object categories. First, a whole-brain classifier was trained on pictures of faces and places. Subjects then saw transparently overlapped pictures of a face and a place, and attended to only one of them while ignoring the other. The category of the attended object, face or place, was decoded on a scan-by-scan basis using the previously trained decoder. The decoder performed at 77.6% accuracy indicating that despite competing bottom-up sensory input, object-based visual attention biased neural patterns towards that of the attended object. Furthermore, a comparison between different classification approaches indicated that the representation of faces and places is distributed rather than focal. This implies that real-time decoding of object-based attention requires a multivariate decoding approach that can detect these distributed patterns of cortical activity., (© 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

With the advent of sophisticated acquisition and analysis techniques, decoding the contents of someone's experience has become a reality. We propose a straightforward linear Gaussian approach, where decoding relies on the inversion of properly regularized encoding models, which can still be solved analytically. In order to test our approach we acquired functional magnetic resonance imaging data under a rapid event-related design in which subjects were presented with handwritten characters. Our approach is shown to yield state-of-the-art reconstructions of perceived characters as estimated from BOLD responses. This even holds for previously unseen characters. We propose that this framework serves as a baseline with which to compare more sophisticated models for which analytical inversion is infeasible., (© 2013.)

An ultrafast functional magnetic resonance imaging (fMRI) technique, called generalized inverse imaging (GIN), is proposed, which combines inverse imaging with a phase constraint-leading to a less underdetermined reconstruction-and physiological noise correction. A single 3D echo planar imaging (EPI) prescan is sufficient to obtain the necessary coil sensitivity information and reference images that are used to reconstruct standard images, so that standard analysis methods are applicable. A moving dots stimulus paradigm was chosen to assess the performance of GIN. We find that the spatial localization of activation for GIN is comparable to an EPI protocol and that maximum z-scores increase significantly. The high temporal resolution of GIN (50 ms) and the acquisition of the phase information enable unaliased sampling and regression of physiological signals. Using the phase time courses obtained from the 32 channels of the receiver coils as nuisance regressors in a general linear model results in significant improvement of the functional activation, rendering the acquisition of external physiological signals unnecessary. The proposed physiological noise correction can in principle be used for other fMRI protocols, such as simultaneous multislice acquisitions, which acquire the phase information sufficiently fast and sample physiological signals unaliased., (Copyright © 2012 Wiley Periodicals, Inc.)

With combined EEG-fMRI a powerful combination of methods was developed in the last decade that seems promising for answering fundamental neuroscientific questions by measuring functional processes of the human brain simultaneously with two complementary modalities. Recently, resting state networks (RSNs), representing brain regions of coherent BOLD fluctuations, raised major interest in the neuroscience community. Since RSNs are reliably found across subjects and reflect task related networks, changes in their characteristics might give insight to neuronal changes or damage, promising a broad range of scientific and clinical applications. The question of how RSNs are linked to electrophysiological signal characteristics becomes relevant in this context. In this combined EEG-fMRI study we investigated the relationship of RSNs and their correlated electrophysiological signals [electrophysiological correlation patterns (ECPs)] using a long (34 min) resting state scan per subject. This allowed us to study ECPs on group as well as on single subject level, and to examine the temporal stability of ECPs within each subject. We found that the correlation patterns obtained on group level show a large inter-subject variability. During the long scan the ECPs within a subject show temporal fluctuations, which we interpret as a result of the complex temporal dynamic of the RSNs.

This article demonstrates the application of spin-echo EPI for resting state fMRI at 7 T. A short repetition time of 1860 ms was made possible by the use of slice multiplexing which permitted whole brain coverage at high spatial resolution (84 slices of 1.6 mm thickness). Radiofrequency power deposition was kept within regulatory limits by use of the power independent of number of slices (PINS) technique. A high in-plane spatial resolution of 1.5 mm was obtained, while image distortion was ameliorated by the use of in-plane parallel imaging techniques. Data from six subjects were obtained with a measurement time of just over 15 min per subject. A group level independent component (IC) analysis revealed 24 non-artefactual resting state networks, including those commonly found in standard acquisitions, as well as plausible networks for a broad range of regions. Signal was measured from regions commonly rendered inaccessible due to signal voids in gradient echo acquisitions. Dual regression was used to obtain spatial IC maps at the single subject level revealing exquisite localisation to grey matter that is consistent with a high degree of T(2)-weighting in the acquisition sequence. This technique hence holds great promise for both resting state and activation studies at 7 T., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Structural connectivity research in the human brain in vivo relies heavily on fiber tractography in diffusion-weighted MRI (DWI). The accurate mapping of white matter pathways would gain from images with a higher resolution than the typical ~2mm isotropic DWI voxel size. Recently, high field gradient echo MRI (GE) has attracted considerable attention for its detailed anatomical contrast even within the white and gray matter. Susceptibility differences between various fiber bundles give a contrast that might provide a useful representation of white matter architecture complementary to that offered by DWI. In this paper, Structure Tensor Informed Fiber Tractography (STIFT) is proposed as a method to combine DWI and GE. A data-adaptive structure tensor is calculated from the GE image to describe the morphology of fiber bundles. The structure tensor is incorporated in a tractography algorithm to modify the DWI-based tracking direction according to the contrast in the GE image. This GE structure tensor was shown to be informative for tractography. From closely spaced seedpoints (0.5mm) on both sides of the border of 1) the optic radiation and inferior longitudinal fasciculus 2) the cingulum and corpus callosum, STIFT fiber bundles were clearly separated in white matter and terminated in the anatomically correct areas. Reconstruction of the optic radiation with STIFT showed a larger anterior extent of Meyer's loop compared to a standard tractography alternative. STIFT in multifiber voxels yielded a reduction in crossing-over of streamlines from the cingulum to the adjacent corpus callosum, while tracking through the fiber crossings of the centrum semiovale was unaffected. The STIFT method improves the anatomical accuracy of tractography of various fiber tracts, such as the optic radiation and cingulum. Furthermore, it has been demonstrated that STIFT can differentiate between kissing and crossing fiber configurations. Future investigations are required to establish the applicability in more white matter pathways., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Early elementary schooling in 2nd and 3rd grades (ages 7-9) is an important period for the acquisition and mastery of basic mathematical skills. Yet, we know very little about neurodevelopmental changes that might occur over a year of schooling. Here we examine behavioral and neurodevelopmental changes underlying arithmetic problem solving in a well-matched group of 2nd (n = 45) and 3rd (n = 45) grade children. Although 2nd and 3rd graders did not differ on IQ or grade- and age-normed measures of math, reading and working memory, 3rd graders had higher raw math scores (effect sizes = 1.46-1.49) and were more accurate than 2nd graders in an fMRI task involving verification of simple and complex two-operand addition problems (effect size = 0.43). In both 2nd and 3rd graders, arithmetic complexity was associated with increased responses in right inferior frontal sulcus and anterior insula, regions implicated in domain-general cognitive control, and in left intraparietal sulcus (IPS) and superior parietal lobule (SPL) regions important for numerical and arithmetic processing. Compared to 2nd graders, 3rd graders showed greater activity in dorsal stream parietal areas right SPL, IPS and angular gyrus (AG) as well as ventral visual stream areas bilateral lingual gyrus (LG), right lateral occipital cortex (LOC) and right parahippocampal gyrus (PHG). Significant differences were also observed in the prefrontal cortex (PFC), with 3rd graders showing greater activation in left dorsal lateral PFC (dlPFC) and greater deactivation in the ventral medial PFC (vmPFC). Third graders also showed greater functional connectivity between the left dlPFC and multiple posterior brain areas, with larger differences in dorsal stream parietal areas SPL and AG, compared to ventral stream visual areas LG, LOC and PHG. No such between-grade differences were observed in functional connectivity between the vmPFC and posterior brain regions. These results suggest that even the narrow one-year interval spanning grades 2 and 3 is characterized by significant arithmetic task-related changes in brain response and connectivity, and argue that pooling data across wide age ranges and grades can miss important neurodevelopmental changes. Our findings have important implications for understanding brain mechanisms mediating early maturation of mathematical skills and, more generally, for educational neuroscience., (Copyright © 2011 Elsevier Inc. All rights reserved.)

The consolidation of declarative memories benefits from sleep. The neural mechanisms involved in sleep-dependent consolidation, however, are largely unknown. Here, we used a combination of functional magnetic resonance imaging, polysomnography and a face-location associative memory task to target neural connectivity of a face sensitive area during an afternoon nap. Fusiform connectivity was substantially greater during sleep stage 1 than in wake in a network extending from early visual areas bilaterally to the fusiform gyrus, ventrally and into the posterior parietal cortices, dorsally. In sleep stage 2, fusiform connectivity was found to be larger in the precuneus, bilateral middle temporal gyrus and medial prefrontal cortex. Specific functional connectivity increases observed during light sleep were positively correlated with memory performance for face-location associations. A distinction could be made between fusiform-medial prefrontal connectivity during sleep stage 1 and 2 that was positively correlated with retention of associations learned prior to sleep and fusiform-hippocampal connectivity during sleep stage 1 that was correlated with better acquisition of new associations learned after sleep. Our results suggest that fusiform-medial prefrontal connectivity during sleep has a stabilizing effect on recently learned associative memories, possibly due to the existence of a task-related schema that allows rapid consolidation of related information. Our data further indicate that sleep-dependent connectivity between the fusiform gyrus and hippocampus correlated with new learning after sleep. Thus, our study provides correlational evidence for the behavioral relevance of specific medial prefrontal and hippocampal interactions with the fusiform gyrus during light sleep., (Copyright © 2011 Elsevier Inc. All rights reserved.)

The neocortex is known to have a distinct laminar structure which has previously been probed in animals using high-resolution fMRI. Detection of layer-specific activation in humans has however to date proven elusive. In this study we demonstrate for the first time such layer-specific activation, specifically at a depth corresponding to layer IV of human primary visual cortex (V1). We used a gradient-echo (GE) sequence at 3T with an isotropic resolution of 0.75 mm, in which a stria at the depth of layer IV was visible in the averaged time series, and could be used as an anatomical landmark. Upon visual stimulation (7.5 Hz flickering checkerboard) the signal increase of 3% in layer IV was significantly higher than in the neighboring laminae. The width of this activation peak was 0.8-1 mm. Based on this result and known laminar organization of the intracortical vasculature we conclude that in the direction perpendicular to the cortical surface the intrinsic spatial resolution of the GE-BOLD fMRI signal is in the submillimetre range. Human laminar fMRI is a significant development which may improve our understanding of intracortical activation patterns and of the way in which different cortical regions interact., (Hum Brain Mapp, 2010. © 2010 Wiley-Liss, Inc.)

Functional MRI (fMRI) most commonly employs 2D echo-planar imaging (EPI). The advantages for fMRI brought about by the increasingly popular ultra-high field strengths are best exploited in high-resolution acquisitions, but here 2D EPI becomes impractical for several reasons, including the very long volume acquisitions times. In this study at 7 T, a 3D EPI sequence with full parallel and partial Fourier imaging capability along both phase encoding axes was implemented and used to evaluate the sensitivity of 3D and corresponding 2D EPI acquisitions at four different spatial resolutions ranging from small to typical voxel sizes (1.5-3.0 mm isotropic). Whole-brain resting state measurements (N=4) revealed a better, or at least comparable sensitivity of the 3D method for gray and white matter. The larger vulnerability of 3D to physiological effects was outweighed by the much shorter volume TR, which moreover allows whole-brain coverage at high resolution within fully acceptable limits for event-related fMRI: TR was only 3.07 s for 1.5 mm, 1.88 s for 2.0 mm, 1.38 s for 2.5 mm and 1.07 s for 3.0 mm isotropic resolution. In order to investigate the ability to detect and spatially resolve BOLD activation in the visual cortex, functional 3D EPI experiments (N=8) were performed at 1 mm isotropic resolution with parallel imaging acceleration of 3x3, resulting in a TR of only 3.2 s for whole-brain coverage. From our results, and several other practical advantages of 3D over 2D EPI found in the present study, we conclude that 3D EPI provides a useful alternative for whole-brain fMRI at 7 T, not only when high-resolution data are required., (Copyright (c) 2010 Elsevier Inc. All rights reserved.)

In this study, the sensitivity of the S(2)-steady-state free precession (SSFP) signal for functional MRI at 7 T was investigated. In order to achieve the necessary temporal resolution, a three-dimensional acquisition scheme with acceleration along two spatial axes was employed. Activation maps based on S(2)-steady-state free precession data showed similar spatial localization of activation and sensitivity as spin-echo echo-planar imaging (SE-EPI), but data can be acquired with substantially lower power deposition. The functional sensitivity estimated by the average z-values was not significantly different for SE-EPI compared to the S(2)-signal but was slightly lower for the S(2)-signal (6.74 +/- 0.32 for the TR = 15 ms protocol and 7.51 +/- 0.78 for the TR = 27 ms protocol) compared to SE-EPI (7.49 +/- 1.44 and 8.05 +/- 1.67) using the same activated voxels, respectively. The relative signal changes in these voxels upon activation were slightly lower for SE-EPI (2.37% +/- 0.18%) compared to the TR = 15 ms S(2)-SSFP protocol (2.75% +/- 0.53%) and significantly lower than the TR = 27 ms protocol (5.38% +/- 1.28%), in line with simulations results. The large relative signal change for the long TR SSFP protocol can be explained by contributions from multiple coherence pathways and the low intrinsic intensity of the S(2) signal. In conclusion, whole-brain T(2)-weighted functional MRI with negligible image distortion at 7 T is feasible using the S(2)-SSFP sequence and partially parallel imaging.

Objective: We investigate the implications of high magnetic field strength on MR venography based on susceptibility-weighted imaging (SWI) and estimate the optimum echo time to obtain maximum contrast between blood and brain tissue., Materials and Methods: We measured tissue contrast and T2* relaxation times at 7 T of gray matter, white matter, and venous blood in vivo., Results: T2* relaxation times of gray matter, white matter, and venous blood in vivo yielded 32.9 +/- 2.3, 27.7 +/- 4.3, and 7.4 +/- 1.4 ms, respectively. Optimum TE was found to be 15 ms which is supported by theoretical considerations. Using this optimum TE, we acquired 3D high resolution datasets with a large volume coverage in a short measurement time that show very detailed microanatomical structures of the human brain such as intracortical veins and laminar cortical substructures., Conclusions: By applying optimised vessel filters (vesselness filter and vessel enhancing diffusion) whole brain MR venograms can be obtained at 7 T with a significantly reduced measurement time compared to 3 T.

Functional magnetic resonance imaging (fMRI) performed by echo-planar imaging (EPI) is often highly distorted, and it is therefore necessary to coregister the functional to undistorted anatomical images, especially for clinical applications. This pilot study provides an evaluation of human and automatic coregistration results in the human motor cortex of normal and pathological brains. Ten healthy right-handed subjects and ten right-handed patients performed simple right hand movements during fMRI. A reference point chosen at a characteristic anatomical location within the fMRI sensorimotor activations was transferred to the high resolution anatomical MRI images by three human fMRI experts and by three automatic coregistration programs. The 3D distance between the median localizations of experts and programs was calculated and compared between patients and healthy subjects. Results show that fMRI localization on anatomical images was better with the experts than software in 70% of the cases and that software performance was worse for patients than healthy subjects (unpaired t-test: P = 0.040). With 45.6 mm the maximum disagreement between experts and software was quite large. The inter-rater consistency was better for the fMRI experts compared to the coregistration programs (ANOVA: P = 0.003). We conclude that results of automatic coregistration should be evaluated carefully, especially in case of clinical application.

Purpose: To evaluate the impact of data quality on the localization of brain activation in functional magnetic resonance imaging (fMRI) and to explore whether the temporal contrast-to-noise-ratio (CNR) provides a quantitative parameter to estimate fMRI quality., Materials and Methods: We investigated two methods for defining the CNR by comparing them on a single-run, single session, as well as on a group-wise basis. The CNRs of healthy subjects and a group of patients with brain lesions were calculated using two different strategies: one based on a general linear model (GLM) analysis (CNR&#95;SPM), and one that acts as an adaptive low-pass filter and assumes that the high-frequency components contain the temporal noise (CNR&#95;SG). Runs with low CNR were identified as outliers using a common exclusion criterion (2 x standard deviation (SD))., Results: The results of the two CNR methods are highly correlated. Both between and within subjects and patients the CNR showed quite large variations, but the average CNR did not differ between a group of healthy subjects and a patient group. In total, seven of 213 runs (3.3% of all runs) had to be excluded when CNR&#95;SG was used, and 14 of 213 (6.6%) runs had to be excluded when CNR&#95;SPM was used., Conclusion: Calculating the CNR using an adaptive low-pass filter gives similar results to a GLM-based approach and could be advantageous for cases in which the hemodynamic response function (HRF) differs significantly from common assumptions. The CNR can be used to identify and exclude runs with suboptimal CNR, and to identify sessions with insufficient data quality. The CNR may serve as a quantitative and intuitive parameter to assess the performance and quality of clinical fMRI investigations, including information on both functional performance (contrast) and data quality (noise caused by the system and physiology)., ((c) 2007 Wiley-Liss, Inc.)

Objectives: We sought to determine the optimal dose of a contrast agent with known high relaxivity on 1.5 and 3 Tesla scanners that would achieve the best compromise between image quality and scan time for the clinical application of contrast-enhanced susceptibility-weighted imaging (CE-SWI)., Methods: Pre- and postcontrast SWI was performed with different contrast agent doses (0.05, 0.1, and 0.2 mmol/kg gadobenate dimeglumine) at both 1.5 and 3 T in 6 healthy volunteers, resulting in 72 examinations. Venograms were created from minimum intensity projection reconstructions over specified deep white matter volumes to enhance the visual appearance of connected venous structures. Three independent radiologists blindly rated the visibility of the veins on a continuous scale of 1 to 10. A general linear model was used for statistical evaluation, with fixed effects of the contrast agent dose, the field strength, the rater and the patients as a random effect., Results: With CE-SWI, we found significant differences in the visibility of the deep veins dependent on the contrast media dose (P=0.02). At 3 T, the visibility of deep venous vessels, with regard to susceptibility effect, image quality, and scan time reduction after a standard contrast agent dose 0.1 mmol/kg was significantly better than that achieved with 0.05 mmol/kg. The visibility was considered equal with 0.1 mmol/kg of the contrast agent to the precontrast images and a dose of 0.2 mmol/kg. At 1.5 T, no significant difference was found between the 4 contrast agent doses. We found no difference in the visibility of the veins with the shorter sequences at 3 T compared with the sequences at 1.5 T., Conclusions: Only a standard dose (0.1 mmol/kg) of gadobenate dimeglumine is required to achieve the optimum susceptibility effect and image quality at 3 T, together with a reduced scan time. This result can be attributed to the higher relaxivity of gadobenate dimeglumine, compared with conventional gadolinium chelates.

Objectives: The validity of 3 Tesla motor functional magnetic resonance imaging (fMRI) in patients with gliomas involving the primary motor cortex was investigated by intraoperative navigated motor cortex stimulation (MCS)., Methods: Twenty two patients (10 males, 12 females, mean age 39 years, range 10-65 years) underwent preoperative fMRI studies, performing motor tasks including hand, foot, and mouth movements. A recently developed high field clinical fMRI technique was used to generate pre-surgical maps of functional high risk areas defining a motor focus. Motor foci were tested for validity by intraoperative motor cortex stimulation (MCS) employing image fusion and neuronavigation. Clinical outcome was assessed using the Modified Rankin Scale., Results: FMRI motor foci were successfully detected in all patients preoperatively. In 17 of 22 patients (77.3%), a successful stimulation of the primary motor cortex was possible. All 17 correlated patients showed 100% agreement on MCS and fMRI motor focus within 10 mm. Technical problems during stimulation occurred in three patients (13.6%), no motor response was elicited in two (9.1%), and MCS induced seizures occurred in three (13.6%). Combined fMRI and MCS mapping results allowed large resections in 20 patients (91%) (gross total in nine (41%), subtotal in 11 (50%)) and biopsy in two patients (9%). Pathology revealed seven low grade and 15 high grade gliomas. Mild to moderate transient neurological deterioration occurred in six patients, and a severe hemiparesis in one. All patients recovered within 3 months (31.8% transient, 0% permanent morbidity)., Conclusions: The validation of clinically optimised high magnetic field motor fMRI confirms high reliability as a preoperative and intraoperative adjunct in glioma patients selected for surgery within or adjacent to the motor cortex.

Objectives: The intracarotid amobarbital test (Wada test) currently represents the gold standard for preoperative lateralization of hemispheric dominance. Here, we report an epileptic patient with a longstanding extended lesion of the left hemisphere showing absence of motor and speech dysfunction with left carotid amobarbital injection, but tetraplegia and speech arrest with right carotid injection interpreted as a neuroplastic shift of motor and language functions to the right hemisphere. In contrast to the Wada results, motor functional magnetic resonance imaging (fMRI) showed a strong left hemispheric activation with right hand movements., Methods: Right and left hand motor fMRI was performed. FMRI results and neurophysiological information obtained by motor and sensory evoked potential measurements were compared with the Wada test results., Results: Initial interpretation of neuroplastic shifts of intrinsic left hemisphere functions to the right brain was revised after fMRI results which were confirmed by motor and sensory evoked potentials., Conclusion: As motor inactivation usually is thought to be the most robust feature of the Wada test, this case demonstrates that fMRI may reveal residual functional cortex in cases of inconclusive Wada results.

Purpose: To establish a fast and robust technique for generating magnetic field maps for the correction of geometric distortions in echo-planar magnetic resonance (MR) images., Materials and Methods: Multislice gradient-echo (GE) images were acquired at echo times of 6, 6.5, and 7.5 msec in order to cover a field shift range of +/-666 Hz in the resulting B0 maps. To account for possible phase wrap scenarios, seven phase triples were calculated for each pixel. Linear regression of the phase vs. echo time was performed for each set. The slope of the set with the minimum fitting error was taken as the true magnetic field in the respective pixel., Results: Based on the fitting error distribution, the technique is shown to be feasible and effective for assessing the field distribution in the brain at 3 T, especially in inferior brain areas (amygdalae, hippocampus). Examples of echo-planar images distortion corrected using the calculated field maps are shown., Conclusion: The approach presented yields robust estimation of magnetic field maps and requires under a minute of additional acquisition time and only seconds of computational time. As such, it is easily possible to apply image distortion correction in routine functional MR imaging (fMRI) studies, enabling improved coregistration of brain activation maps with structures on anatomical images., (Copyright 2004 Wiley-Liss, Inc.)

The aim of this work is to compare the efficiency and power of several cluster analysis techniques on fully artificial (mathematical) and synthesized (hybrid) functional magnetic resonance imaging (fMRI) data sets. The clustering algorithms used are hierarchical, crisp (neural gas, self-organizing maps, hard competitive learning, k-means, maximin-distance, CLARA) and fuzzy (c-means, fuzzy competitive learning). To compare these methods we use two performance measures, namely the correlation coefficient and the weighted Jaccard coefficient (wJC). Both performance coefficients (PCs) clearly show that the neural gas and the k-means algorithm perform significantly better than all the other methods using our setup. For the hierarchical methods the ward linkage algorithm performs best under our simulation design. In conclusion, the neural gas method seems to be the best choice for fMRI cluster analysis, given its correct classification of activated pixels (true positives (TPs)) whilst minimizing the misclassification of inactivated pixels (false positives (FPs)), and in the stability of the results achieved.

A multiple gradient echo, high resolution imaging method is proposed to better visualize different sources of activation in functional magnetic resonance imaging (fMRI) experiments. Eight echoes are collected from 30 ms to 205 ms with an echo spacing of 25 ms. All echoes show significant activation, but each echo reveals its own pattern of activation. From this variability, it appears that large vessel contributions can be separated from small vessel contributions using a fuzzy cluster analysis across echo times. The results demonstrate the importance of a multiple gradient echo data acquisition approach in localizing various vascular contributions to brain activation in fMRI.