Optimizing the imaging of the monkey auditory cortex: sparse vs. continuous fMRI

The noninvasive imaging of the monkey auditory system with functional magnetic resonance imaging (fMRI) can bridge the gap between electrophysiological studies in monkeys and imaging studies in humans. Some of the recent imaging of monkey auditory cortical and subcortical structures relies on a technique of “sparse imaging,” which was developed in human studies to sidestep the negative influence of scanner noise by adding periods of silence in between volume acquisition. Among the various aspects that have gone into the ongoing optimization of fMRI of the monkey auditory cortex, replacing the more common continuous-imaging paradigm with sparse imaging seemed to us to make the most obvious difference in the amount of activity that we could reliably obtain from awake or anesthetized animals. Here, we directly compare the sparse- and continuous-imaging paradigms in anesthetized animals. We document a strikingly greater auditory response with sparse imaging, both quantitatively and qualitatively, which includes a more expansive and robust tonotopic organization. There were instances where continuous imaging could better reveal organizational properties that sparse imaging missed, such as aspects of the hierarchical organization of auditory cortex. We consider the choice of imaging paradigm as a key component in optimizing the fMRI of the monkey auditory cortex.     

Simultaneous EEG and fMRI in the macaque monkey at 4.7 Tesla

Simultaneous electroencephalography (EEG)/functional magnetic resonance imaging (fMRI) acquisition can identify the brain networks involved in generating specific EEG patterns. Yet, the combination of these methodologies is hampered by strong artifacts that arise due to electromagnetic interference during magnetic resonance (MR) image acquisition. Here, we report corrections of the gradient-induced artifact in phantom measurements and in experiments with an awake behaving macaque monkey during fMRI acquisition at a magnetic field strength of 4.7 T. Ninety-one percent of the amplitude of a 10 microV, 10 Hz phantom signal could successfully be recovered without phase distortions. Using this method, we were able to extract the monkey EEG from scalp recordings obtained during MR image acquisition. Visual evoked potentials could also be reliably identified. In conclusion, simultaneous EEG/fMRI acquisition is feasible in the macaque monkey preparation at 4.7 T and holds promise for investigating the neural processes that give rise to particular EEG patterns.     

Fast T2-weighted MR imaging: impact of variation in pulse sequence parameters on image quality and artifacts

The purpose of this study was to quantitatively evaluate in a phantom model the practical impact of alteration of key imaging parameters on image quality and artifacts for the most commonly used fast T(2)-weighted MR sequences. These include fast spin-echo (FSE), single shot fast spin-echo (SSFSE), and spin-echo echo-planar imaging (EPI) pulse sequences. We developed a composite phantom with different T1 and T2 values, which was evaluated while stationary as well as during periodic motion. Experiments involved controlled variations in key parameters including effective TE, TR, echo spacing (ESP), receive bandwidth (BW), echo train length (ETL), and shot number (SN). Quantitative analysis consisted of signal-to-noise ratio (SNR), image nonuniformity, full-width-at-half-maximum (i.e., blurring or geometric distortion) and ghosting ratio. Among the fast T(2)-weighted sequences, EPI was most sensitive to alterations in imaging parameters. Among imaging parameters that we tested, effective TE, ETL, and shot number most prominently affected image quality and artifacts. Short T(2) objects were more sensitive to alterations in imaging parameters in terms of image quality and artifacts. Optimal clinical application of these fast T(2)-weighted imaging pulse sequences requires careful attention to selection of imaging parameters.     

Concurrent correction of geometric distortion and motion using the map-slice-to-volume method in echo-planar imaging

The accuracy of measuring voxel intensity changes between stimulus and rest images in fMRI echo-planar imaging (EPI) data is severely degraded in the presence of head motion. In addition, EPI is sensitive to susceptibility-induced geometric distortions. Head motion causes image shifts and associated field map changes that induce different geometric distortion at different time points. Conventionally, geometric distortion is "corrected" with a static field map independently of image registration. That approach ignores all field map changes induced by head motion. This work evaluates the improved motion correction capability of mapping slice to volume with concurrent iterative field corrected reconstruction using updated field maps derived from an initial static field map that has been spatially transformed and resampled. It accounts for motion-induced field map changes for translational and in-plane rotation motion. The results from simulated EPI time series data, in which motion, image intensity and activation ground truths are available, show improved accuracy in image registration, field corrected image reconstruction and activation detection.     

Distortion correction for a double inversion-recovery sequence with an echo-planar imaging readout

A double inversion-recovery (DIR) sequence with an echo-planar imaging (EPI) readout can be used to image selectively the grey matter of the brain, and this has previously been applied to improve the sensitivity of the statistical analysis of functional magnetic resonance imaging (fMRI) data. If a procedure were to be implemented to remove the distortions that are inherent in the EPI-based fMRI data set, then a similar technique would have to be applied to the DIR-EPI image also to ensure that it matches the geometry of the functional data. A comparison of candidate methodologies for correcting distortions in DIR-EPI images, based on the reversed-gradient method, is presented. A corrected image could be calculated from two DIR-EPI images acquired with k-space traversal in opposite directions, but that method was not able to cope with the large regions of low signal intensity corresponding to the nulled white matter. It was found that the optimal procedure to apply the reversed-gradient method to DIR-EPI images was to acquire two additional EPI images (without the two inversion pulses) with opposite-direction k-space traversal; the distortion-correction information calculated from those EPI images was then applied to the DIR-EPI data.     

Semiautomated segmentation of the human spine based on echoplanar images

The number of functional magnetic resonance imaging (fMRI) studies performed on the human spinal cord (SC) has considerably increased in recent years. The lack of a validated processing pipeline is, however, a significant obstacle to the spread of SC fMRI. One component likely to be involved in any such pipeline is the process of SC masking, analogous to brain extraction in cerebral fMRI. In general, SC masking has been performed manually, with the incumbent costs of being very time consuming and operator dependent. To overcome these drawbacks, we have developed a tailored semiautomatic method for segmenting echoplanar images (EPI) of human spine that is able to identify the spinal canal and the SC. The method exploits both temporal and spatial features of the EPI series and was tested and optimized on EPI images of cervical spine acquired at 3 T. The dependence of algorithm performance on the degree of EPI image distortion was assessed by computing the displacement warping field that best matched the EPI to the corresponding high-resolution T(2) images. Segmentation accuracy was above 80%, a significant improvement over values obtained with similar approaches, but not exploiting temporal information. Geometric distortion was found to explain about 50% of the variance of algorithm classification efficiency.     

Brain modifications after acute alcohol consumption analyzed by resting state fMRI

Resting-state functional magnetic resonance imaging (fMRI) is a recent breakthrough in neuroimaging research able to describe “in vivo” the spontaneous baseline neuronal activity characterized by blood oxygen level dependent (BOLD) signal fluctuations at slow frequency (0.01–0.1 Hz) that, in the absence of any task, forms spatially distributed functional connectivity networks, called resting state networks (RSNs). The aim of this study was to investigate, in the young and healthy population, the changing of the RSNs after acute ingestion of an alcohol dose able to determine a blood concentration (0.5 g/L) that barely exceeds the legal limits for driving in the majority of European Countries. Fifteen healthy volunteers underwent two fMRI sessions using a 1.5 T MR scanner before and after alcohol oral consumption. The main sequence acquired was EPI 2D BOLD, one per each session. To prevent the excessive alcohol consumption the subjects underwent the estimation of blood rate by breath test and after the stabilization of blood alcohol level (BAL) at 0.5 g/L the subjects underwent the second fMRI session. Functional data elaboration was carried out using the probabilistic independent component analysis (PICA). Spatial maps so obtained were further organized, with MELODIC multisession temporal concatenation FSL option, in a cluster representing the group of pre-alcohol sessions and the group of post-alcohol sessions, followed by the dual regression approach in order to evaluate the increase or decrease in terms of connectivity in the RSNs between the two sessions at group level.The results we obtained reveal that acute consumption of alcohol reduces in a significant way the BOLD signal fluctuations in the resting brain selectively in the sub-callosal cortex (SCC), in left temporal fusiform cortex (TFC) and left inferior temporal gyrus (ITG), which are cognitive regions known to be part of the reward brain network and the ventral visual system.     

Surface-based functional magnetic resonance imaging analysis of partial brain echo planar imaging data at 1.5 T

Surface-based functional magnetic resonance imaging (fMRI) analysis is more sensitive and accurate than volume-based analysis for detecting neural activation. However, these advantages are less important in practical fMRI experiments with commonly used 1.5-T magnetic resonance devices because of the resolution gap between the echo planar imaging data and the cortical surface models. We expected high-resolution segmented partial brain echo planar imaging (EPI) data to overcome this problem, and the activation patterns of the high-resolution data could be different from the low-resolution data. For the practical applications of surface-based fMRI analysis using segmented EPI techniques, the effects of some important factors (e.g., activation patterns, registration and local distortions) should be intensively evaluated because the results of surface-based fMRI analyses could be influenced by them. In this study, we demonstrated the difference between activations detected from low-resolution EPI data, which were covering whole brain, and high-resolution segmented EPI data covering partial brain by volume- and surface-based analysis methods. First, we compared the activation maps of low- and high-resolution EPI datasets detected by volume- and surface-based analyses, with the spatial patterns of activation clusters, and analyzed the distributions of activations in occipital lobes. We also analyzed the high-resolution EPI data covering motor areas and fusiform gyri of human brain, and presented the differences of activations detected by volume- and surface-based methods.     

Realignment strategies for awake-monkey fMRI data

Functional magnetic resonance imaging (fMRI) experiments with awake nonhuman primates (NHPs) have recently seen a surge of applications. However, the standard fMRI analysis tools designed for human experiments are not optimal for NHP data collected at high fields. One major difference is the experimental setup. Although real head movement is impossible for NHPs, MRI image series often contain visible motion artifacts. Animal body movement results in image position changes and geometric distortions. Since conventional realignment methods are not appropriate to address such differences, algorithms tailored specifically for animal scanning become essential. We have implemented a series of high-field NHP specific methods in a software toolbox, fMRI Sandbox (http://kyb.tuebingen.mpg.de/~stoewer/), which allows us to use different realignment strategies. Here we demonstrate the effect of different realignment strategies on the analysis of awake-monkey fMRI data acquired at high field (7 T). We show that the advantage of using a nonstandard realignment algorithm depends on the amount of distortion in the dataset. While the benefits for less distorted datasets are minor, the improvement of statistical maps for heavily distorted datasets is significant.     

Accurate and sensitive measurements of magnetic susceptibility using echo planar imaging

Susceptibility differences are common causes for artifacts in magnetic resonance (MR); therefore, it is important to choose phantom materials in a way that these artifacts are kept at a minimum. In this study, a previously proposed MR imaging (MRI) method [Beuf O, Briguet A, Lissac M, Davis R. Magnetic resonance imaging for the determination of magnetic susceptibility of materials. J Magn Reson 1996; Series B(112):111-118] was improved to facilitate sensitive in-house measurements of different phantom materials so that such artifacts can more easily be minimized. Using standard MRI protocols and distilled water as reference, we measured magnetic volume susceptibility differences with a clinical MR system. Two imaging techniques, echo planar imaging (EPI) and spin echo, were compared using liquid samples whose susceptibilities were verified by MR spectroscopy. The EPI sequence has a very narrow bandwidth in the phase-encoding direction, which gives an increased sensitivity to magnetic field inhomogeneities. All MRI measurements were evaluated in two ways: (1) manual image analysis and (2) model fitting. The narrow bandwidth of the EPI made it possible to detect very small susceptibility differences (equivalent susceptibility difference, Deltachi(e)> or =0.02 ppm), and even plastics could be measured. Model fitting yielded high accuracy and high sensitivity and was less sensitive to other image artifacts as compared with manual image analysis.     

EEG quality during simultaneous functional MRI of interictal epileptiform discharges

This article concerns the evaluation of the quality of interictal epileptiform EEG discharges recorded throughout simultaneous echo planar imaging (EPI). BOLD (blood oxygen level dependent) functional MRI (fMRI) images were acquired continuously on a patient with intractable epilepsy. EEG was sampled simultaneously, during and after imaging, with removal of pulse and imaging artifacts by subtraction of channel-specific running averages. Contiguous EEG epochs recorded with and without fMRI (fMRI+ve vs. fMRI−ve) were next randomized and presented to two blinded observers. Epileptiform discharges were identified retrospectively, and comparison was made in terms of the number of identified events, their amplitude, and spatiotemporal distribution. A spectral analysis was also performed on the EEG. In the randomized comparison of EEG segments, 80 (fMRI+ve) vs. 69 (fMRI−ve) discharges were noted with good interobserver agreement (69%). There were no significant differences in amplitude or spatio-temporal distribution. Comparison of the events detected and measured by two expert observers demonstrated that the Interictal Epileptiform Discharge (IED) characteristics were indistinguishable with and without scanning. We review briefly the existing literature on EEG recording quality for combined EEG/fMRI.     

BOLD signal compartmentalization based on the apparent diffusion coefficient

Functional MRI (fMRI) can detect blood oxygenation level dependent (BOLD) hemodynamic responses secondary to neuronal activity. The most commonly used method for detecting fMRI signals is the gradient-echo echo-planar imaging (EPI) technique because of its sensitivity and speed. However, it is generally believed that a significant portion of these signals arises from large veins, with additional contribution from the capillaries and parenchyma. Early experiments using diffusion-weighted gradient-echo EPI have suggested that intra-voxel incoherent motion (IVIM) weighting inherent in the sequence can selectively attenuate contributions from different vessels based on the differences in the mobility of the blood within them. In the present study, we used similar approach to characterize the apparent diffusion coefficient (ADC) distribution within the activated areas of BOLD contrast. It is shown that the voxel values of the ADCs obtained from this technique can infer various vascular contributions to the BOLD signal.     

Functional MR imaging in the awake monkey: effects of motion on dynamic off-resonance and processing strategies

Functional MR imaging of the alert, behaving monkey is being used more and more often to detect activation patterns and guide electrophysiological research investigating the neural basis of behavior. Several labs have reported fMRI data from the awake monkey, but none of them has studied and systematically corrected the effects of monkeys' motion on fMRI time series. In this study, a significant refinement of acquisition and correction strategies is reported that can be used to minimize magnetic susceptibility artifacts induced by respiration and by jaw and body movement. Real-time acquisition of sensor signals (e.g., signals induced by jaw and body movement) and MR navigator data were combined to optimize fMRI signal-correction strategies. Within trials, the artifact-induced off-resonance changes were small and mainly reflected the effects of respiration; between trials, movements caused major changes of global frequency and shim (>20 Hz/cm). Several methods were used to assess the stability of the fMRI series: k-space analysis ('dynamic intensity and off-resonance changes in k-space', dubbed DICK and DORK) and image analysis using a Laplace operator and a center-of-mass metric. The variability between trials made it essential to correct for inter-trial variations. On the other hand, images were sufficiently stable with our approach to perform fMRI evaluations on single trials before averaging of trials. Different motion correction strategies were compared: DORK, McFLIRT (rigid body model with three translations and three rotations) and 2D image alignment based on a center-of-mass detection (in-plane translation). The latter yielded the best results and proved to be fast and robust for intra- and inter-trial alignment. Finally, fMRI in the behaving monkey was tested for spatial and temporal reproducibility on a trial-to-trial basis. Highly activated voxels also displayed good reproducibility between trials. On average, the BOLD amplitude response to a short 3-s visual stimulus was close to 2%.     

Image reconstruction of sequentially sampled echo-planar data

For echo-planar imaging (EPI), failure to time-reverse alternate echoes results in aliasing in the image. We encountered image artifacts in EPI acquired on a system with sequential sampling. After examining the source of these image artifacts, we concluded that the artifacts were a result of the type of sampling method used in data acquisition and the way the time-reversal of alternate echoes was carried out prior to Fourier transformation. Two methods are demonstrated to obtain artifact-free EPI with sequential data sampling.     

Comparison of multi-echo spiral and echo planar imaging in functional MRI

Multi-echo spiral and echo-planar (EPI) imaging sequences were compared in functional imaging experiments at 3 Tesla. Both sequence types allow calculation of the effective transversal relaxation time T(2)* and the initial signal intensity I(0). These parameters can be used in evaluation of the functional signal with respect to inflow effects and other vascular sources. Prior to functional magnetic resonance imaging (fMRI) experiments T(2)* measurements in the human brain were performed with single- and multi-echo FLASH (fast low angle shot) and compared with EPI und spiral imaging sequences. These experiments resulted in T(2)* values ranging from 42.9 to 53.8 ms in a ROI including white and gray matter and CSF in a prefrontal brain region, and allowed validation of the quantitative results of the fast single-shot techniques. In functional experiments with motor stimulation mean absolute T(2)* increases during stimulation of 1.1 +/- 0.6 ms and 1.4 +/- 0.9 ms were found with multi-echo EPI and spiral imaging, respectively, averaged over the activated pixels. In addition, absolute T(2)* values and the size of activated areas obtained with both sequences are comparable. In these investigations spiral imaging allowed higher spatial resolution due to more efficient use of available gradient performance.     

Bone marrow imaging using STIR at 0.5 and 1.5 T.

We retrospectively examined MR images in 82 patients to evaluate the usefulness of short inversion time inversion recovery (STIR) in bone marrow imaging at 0.5 and 1.5 T. The study included 56 patients at 1.5 T and 26 patients at 0.5 T with a variety of pathologic bone marrow lesions (principally oncological), and compared the contrast and image quality of STIR imaging with spin-echo short repetition time/echo time (TR/TE), long TR/TE, and gradient-echo sequences. The pulse sequences were adjusted for optimal image quality, contrast, and fat nulling. STIR appears especially useful for the evaluation of red marrow (e.g., spine), where contrast between normal and infiltrated marrow is greater than with either gradient-echo or T1-weighted images. STIR is also extremely sensitive for evaluation of osteomyelitis, including soft tissue extent. In more peripheral (yellow) marrow, T1-weighted images are usually as sensitive as STIR. Limitations of STIR include artifacts, in particular motion artifact that at high field strength necessitates motion compensation. At 0.5 T, however, motion compensation is usually not necessary. Also, because of extreme sensitivity to water content, STIR may overstate the margins of a marrow lesion. With these limitations in mind, STIR is a very effective pulse sequence at both 0.5 and 1.5 T for evaluation of marrow abnormalities.     

An unsupervised deep learning technique for susceptibility artifact correction in reversed phase-encoding EPI images

Echo planar imaging (EPI) is a fast and non-invasive magnetic resonance imaging technique that supports data acquisition at high spatial and temporal resolutions. However, susceptibility artifacts, which cause the misalignment to the underlying structural image, are unavoidable distortions in EPI. Traditional susceptibility artifact correction (SAC) methods estimate the displacement field by optimizing an objective function that involves one or more pairs of reversed phase-encoding (PE) images. The estimated displacement field is then used to unwarp the distorted images and produce the corrected images. Since this conventional approach is time-consuming, we propose an end-to-end deep learning technique, named S-Net, to correct the susceptibility artifacts the reversed-PE image pair. The proposed S-Net consists of two components: (i) a convolutional neural network to map a reversed-PE image pair to the displacement field; and (ii) a spatial transform unit to unwarp the input images and produce the corrected images. The S-Net is trained using a set of reversed-PE image pairs and an unsupervised loss function, without ground-truth data. For a new image pair of reversed-PE images, the displacement field and corrected images are obtained simultaneously by evaluating the trained S-Net directly. Evaluations on three different datasets demonstrate that S-Net can correct the susceptibility artifacts in the reversed-PE images. Compared with two state-of-the-art SAC methods (TOPUP and TISAC), the proposed S-Net runs significantly faster: 20 times faster than TISAC and 369 times faster than TOPUP, while achieving a similar correction accuracy. Consequently, S-Net accelerates the medical image processing pipelines and makes the real-time correction for MRI scanners feasible. Our proposed technique also opens up a new direction in learning-based SAC.     

Improved functional mapping of the human amygdala using a standard functional magnetic resonance imaging sequence with simple modifications

As the amygdala is involved in various aspects of emotional processing, its characterization using neuroimaging modalities, such as functional magnetic resonance imaging (fMRI), is of great interest. However, in fMRI, the amygdala region suffers from susceptibility artifacts that are composed of signal dropouts and image distortions. Various technically demanding approaches to reduce these artifacts have been proposed, and most require alterations beyond a mere change of the acquisition parameters and cannot be easily implemented by the user without changing the MR sequence code. In the present study, we therefore evaluated the impact of simple alterations of the acquisition parameters of a standard gradient-echo echo-planar imaging technique at 3 T composed of echo times (TEs) of 27 and 36 ms as well as section thicknesses of 2 and 4 mm while retaining a section orientation parallel to the intercommissural plane and an in-plane resolution of 2x2 mm(2). In contrast to previous studies, we based our evaluation on the resulting activation maps using an emotional stimulation paradigm rather than on MR raw image quality only. Furthermore, we tested the effects of spatial smoothing of the functional raw data in the course of postprocessing using spatial filters of 4 and 8 mm. Regarding MR raw image quality, a TE of 27 ms and 2-mm sections resulted in the least susceptibility artifacts in the anteromedial aspect of the temporal lobe. The emotional stimulation paradigm resulted in robust bilateral amygdala activation for the approaches with 2-mm sections only -- but with larger activation volumes for a TE of 36 ms as compared with that of 27 ms. Moderate smoothing with a 4-mm spatial filter represented a good compromise between increased sensitivity and preserved specificity. In summary, we showed that rather than applying advanced modifications of the MR sequence, a simple increase in spatial resolution (i.e., the reduction of section thickness) is sufficient to improve the detectability of amygdala activation.     

Reduced susceptibility effects in perfusion fMRI with single-shot spin-echo EPI acquisitions at 1.5 Tesla

Arterial spin labeling (ASL) perfusion contrast is not based on susceptibility effects and can therefore be used to study brain function in regions of high static inhomogeneity. As a proof of concept, single-shot spin-echo echo-planar imaging (EPI) acquisition was carried out with a multislice continuous ASL (CASL) method at 1.5T. A bilateral finger tapping paradigm was used in the presence of an exogenously induced susceptibility artifact over left motor cortex. The spin-echo CASL technique was compared with a regular gradient-echo EPI sequence with the same slice thickness, as well as other imaging methods using thin slices and spin-echo acquisitions. The results demonstrate improved functional sensitivity and efficiency of the spin-echo CASL approach as compared with gradient-echo EPI techniques, and a trend of improved sensitivity as compared with spin-echo EPI approach in the brain regions affected by the susceptibility artifact. ASL images, either with or without subtraction of the control, provide a robust alternative to blood oxygenation level dependant (BOLD) methods for activation imaging in regions of high static field inhomogeneity.     

The effect of artifacts on dependence measurement in fMRI

The study of effective connectivity by means of neuroimaging depends on the measurement of similarity between activity patterns at different locations in the brain, without necessarily presupposing a particular model for this dependence. When these interactions are measured using functional magnetic resonance imaging (fMRI) techniques, however, imaging and physiological artifacts create patterns of dependence that may be unrelated to cortical activity. We demonstrate some of these effects through the measurement of short-range dependencies present in fMRI scans of the primary visual cortex (V1) in the anaesthetized macaque monkey. High-field (4.7 T) fMRI scans were conducted to measure responses based on the blood oxygen level-dependent contrast mechanism, during periods of no sensory stimulation and of visual stimulation with rotating polar-transformed checkerboard gratings. Dependence between the haemodynamic activity at different spatial locations (i.e., different voxels) was measured using correlation, mutual information and functional covariance. Particular attention was paid to understanding the sources of spurious dependence that may be observed during such investigations. Two main effects were detected: (a) short-range correlations introduced by the process of image reconstruction and (b) perturbations in the haemodynamic response caused by breathing. The image reconstruction artifacts were shown to create an artificially high short-range dependence in the readout direction of the scan, and the breathing artifacts caused enhanced short-range dependence in both the readout and phase-encode directions. Additional dependence in the phase-encode direction due to image-ghosting is also possible but will not be discussed in this report, as it can be alleviated by fine adjustment of preemphasis (elimination of eddy currents). A technique is described for removing breathing artifacts, and the effect of breathing on the apparent dependence between voxels is illustrated. The correlation of haemodynamic activity with the stimulus was found to be affected by breathing, although this effect can be neutralised by averaging the haemodynamic responses over many repetitions of the stimulus. Nonetheless, patterns of dependent activity between voxels may be lost in this averaging process, which makes the removal of breathing artifacts necessary if statistical dependence and the study of effective connectivity is the primary aim of an investigation.