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.     

Evaluation of preprocessing steps to compensate for magnetic field distortions due to body movements in BOLD fMRI

Blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) is currently the dominant technique for non-invasive investigation of brain functions. One of the challenges with BOLD fMRI, particularly at high fields, is compensation for the effects of spatiotemporally varying magnetic field inhomogeneities (ΔB₀) caused by normal subject respiration and, in some studies, movement of the subject during the scan to perform tasks related to the functional paradigm. The presence of ΔB₀ during data acquisition distorts reconstructed images and introduces extraneous fluctuations in the fMRI time series that decrease the BOLD contrast-to-noise ratio. Optimization of the fMRI data-processing pipeline to compensate for geometric distortions is of paramount importance to ensure high quality of fMRI data. To investigate ΔB₀ caused by subject movement, echo-planar imaging scans were collected with and without concurrent motion of a phantom arm. The phantom arm was constructed and moved by the experimenter to emulate forearm motions while subjects remained still and observed a visual stimulation paradigm. These data were then subjected to eight different combinations of preprocessing steps. The best preprocessing pipeline included navigator correction, a complex phase regressor and spatial smoothing. The synergy between navigator correction and phase regression reduced geometric distortions better than either step in isolation and preconditioned the data to make them more amenable to the benefits of spatial smoothing. The combination of these steps provided a 10% increase in t-statistics compared to only navigator correction and spatial smoothing and reduced the noise and false activations in regions where no legitimate effects would occur.     

Fast frequency selective MR imaging

With the proposed fast frequency selective MR imaging (FFSMRI) method, we focused on the elimination of all off-resonance components from the image of the observed object. To maintain imaging speed and simultaneously achieve good frequency selectivity, MRI was divided into two steps: signal acquisition and postprocessing. After the preliminary phase in which we determine imaging parameters, MRI takes place; the signal from the same object is successively acquired M times. As a result, we obtain M partial signals in k-space, from which we calculate the image of the observed object in postprocessing phase, after signal acquisition has been completed. With proper selection of parameters, it is possible to exclude from the image a majority of off-resonance components present in the observed object. However, we can decide to keep only a chosen off-resonance component in the image and eliminate all other components, including the on-resonance component and thus producing a different image from the same acquisition. The experiments with Fe(OH)(3) and oil showed that signal-to-noise ratio (SNR) can be improved by about a factor of four. The proposed FFSMRI method is suitable for frequency selective MR imaging and quantitative measurements in dynamic MRI where exclusion of off-resonance components can improve the reliability of measurement.     

High-field localized 1H NMR spectroscopy in the anesthetized and in the awake monkey

Localized cerebral in vivo ¹H NMR spectroscopy (MRS) was performed in the anesthetized as well as the awake monkey using a novel vertical 7 T/60 cm MR system. The increased sensitivity and spectral dispersion gained at high field enabled the quantification of up to 16 metabolites in 0.1- to 1-ml volumes. Quantification was accomplished by using simulations of 18 metabolite spectra and a macromolecule (MM) background spectrum consisting of 12 components. Major cerebral metabolites (concentrations >3 mM) such as glutamate (Glu), N-acetylaspartate (NAA), creatine (Cr)/phosphocreatine (PCr) and myo-inositol (Ins) were identified with an error below 3%; most other metabolites were quantified with errors in the order of 10%. Metabolite ratios were 1.39:1 for total NAA, 1.38:1 for glutamate (Glu)/glutamine (Gln) and 0.09:1 for cholines (Cho) relative to total Cr. Taurine (Tau) was detectable at concentrations lower than 1 mM, while lactate (Lac) remained below the detection limit. The spectral dispersion was sufficient to separate metabolites of similar spectral patterns, such as Gln and Glu, N-acetylaspartylglutamate (NAAG) and NAA, and PCr–Cr. MRS in the awake monkey required the development and refinement of acquisition and correction strategies to minimize magnetic susceptibility artifacts induced by respiration and movement of the mouth or body. Periods with major motion artifacts were rejected, while a frequency/phase correction was performed on the remaining single spectra before averaging. In resting periods, both spectral amplitude and line width, that is, the voxel shim, were unaffected permitting reliable measurements. The corrected spectra obtained from the awake monkey afforded the reliable detection of 6–10 cerebral metabolites of 1-ml volumes.     

On the origin of respiratory artifacts in BOLD-EPI of the human brain

BOLD-based functional MRI (fMRI) can be used to explicitly measure hemodynamic aspects and functions of human neuro-physiology. As fMRI measures changes in regional cerebral blood flow and volume as well as blood oxygenation, rather than neuronal brain activity directly, other processes that may change the above parameters have to be examined closely to assess sensitivity and specificity of fMRI results. Physiological processes that can cause artifacts include cardiac action, breathing and vasomotion. Although there has been substantial research on physiological artifacts and appropriate compensation methods, controversy still remains on the mechanisms that cause the fMRI signal fluctuations. Respiratory-correlated fluctuations may either be induced by changes of the magnetic field homogeneity due to moving organs, intra-thoracic pressure differences, respiration-dependent vasodilation or oxygenation differences. The aim of this study was to characterize the impact of different breathing patterns by varying respiration frequency and/or tidal volume on EPI time courses of the resting human brain. The amount of respiration-related oscillations during three respiration patterns was quantified, and statistically significant differences were obtained in white matter only: p < 0.03 between 6 vs. 12 ml/kg body weight end tidal volume at a respiration frequency of 15/min, p < 0.03 between 12 vs. 6 ml/kg body weight and 15 vs. 10 respiration cycles/min. There was no significant difference between 15 vs. 10 respiration cycles/min at an end tidal volume of 6 ml/kg body weight (p = 0.917). In addition, the respiration-affected brain regions were very similar with EPI readout in the a-p and l-r direction. Based on our results and published literature we hypothesize that venous oxygenation oscillations due to changing intra-thoracic pressure represent a major factor for respiration-related signal fluctuations and increase significantly with increasing end tidal volume in white matter only.     

A practical approach to in vivo high-resolution diffusion tensor imaging of rhesus monkeys on a 3-T human scanner

The nonhuman primate brain study provides important supplemental means for human brain exploration since the two species share close anatomical and functional similarities. MR diffusion tensor imaging (DTI) in human brain has revealed exquisite details of brain structures especially in the brain white matter. However, most previous monkey brain DTI results lack the spatial resolution in comparison to the conventional tracing and postmortem imaging methods, especially when it is acquired in commonly available human MRI scanners of field strength of 3 T or lower. To meet the increasing demands for nonhuman primate DTI studies, we proposed an in vivo high-resolution monkey DTI acquisition protocol that is practically feasible and combined it with an improved postprocessing procedure for a 3-T human scanner. The acquisition protocol, susceptibility distortion correction method with phase reversal acquisition, and postprocessing steps were proved to be effective in our study of rhesus monkeys. Results from diffusion tensor estimations and fiber tractography at 1 x 1 x 1 mm(3) resolution were found to be comparable to previous ex vivo DTI studies with much longer acquisition times. Effects of image resolution were evaluated and it was confirmed that the partial volume effect due to the larger voxel size in low-resolution data biased the diffusion tensor estimation and produced erroneous fiber tractography. Our results suggest that in vivo high-resolution monkey brain DTI can be achieved within practical time, which allows accurate diffusion tensor estimation and fiber tractography in monkey brains, so that the complex anatomical structures within many small but important anatomic structures can be delineated.     

An integrated head immobilization system and high-performance RF coil for fMRI of visual paradigms at 1.5 T.

A flexible quadrature radiofrequency coil that maximizes the signal-to-noise ratio over the field of view of the human brain has been integrated into a head immobilization and visor system for fMRI at 1.5 T. Head motion is reduced by the visor that incorporates a head clamp and a simple visual sighting system that provides feedback on head position. This system is demonstrated in serial images by correction of deliberate head motions. The sensitivity at the cortical surface of fMRI using blood oxygenation level dependent contrast is increased significantly above that of the commercial rigid volume RF coil under the same acquisition conditions. This improved performance is demonstrated using visual activation and eye movement paradigms.     

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.     

Multi-phase passband balanced SSFP fMRI with 50 ms sampling rate at 7 Tesla enables high precision in resolving 100 ms neuronal events

Passband balanced steady state free precession (b-SSFP) fMRI employs the flat portion of the SSFP off-resonance response to obtain microscopic susceptibility changes elicited by changes in blood oxygenation following enhancement in neuronal activity. This technique can reduce geometric distortion and signal dropout while maintaining rapid acquisition and high signal-to-noise ratio (SNR) compared with traditional fMRI techniques. In the study, we developed a novel multi-phase passband b-SSFP fMRI technique that can achieve a spatial resolution of a few mm³ and a high temporal sampling rate of 50 ms per slice at 7 Tesla. This technique was further applied for an event-related (ER) fMRI paradigm. As a comparison, gradient-echo echo-planar imaging (GE-EPI) with similar spatial resolution and temporal sampling rate was carried out for the same ER-fMRI experiment. Experiments with visual cortex stimulation were carried out at 7 Tesla to demonstrate whether the multi-phase b-SSFP technique and GE-EPI are able to differentiate temporal delays in hemodynamic response function (HRF) separated by 100 ms in stimulus onset. Consistent with ERP results, the upslope of the HRF of both techniques can differentiate 100 ms delay in stimulus onset, with the former showing a lower level of intersubject variability. The present study demonstrated that the multi-phase passband b-SSFP fMRI technique can be applied for resolving neuronal events on the order of 100 ms at ultrahigh magnetic fields.     

Special designed RF-antenna with integrated non-invasive carbon electrodes for simultaneous magnetic resonance imaging and electroencephalography acquisition at 7T

The construction of a high quality MR RF-antenna with incorporated EEG electrodes for simultaneous MRI and EEG acquisition is presented. The antenna comprises an active decoupled surface coil for receiving the MR signal and a whole body coil for transmitting the excitation RF pulses. The surface coil offers a high signal-to-noise ratio required for fMRI application and the whole body coil has a good B(1) excitation profile, which enables the application of homogeneous RF pulses. Non-invasive carbon electrodes are used in order to minimise the magnetic susceptibility artefacts that occur upon application of conductive materials. This dedicated set-up is compared to a standard set-up being a linear birdcage coil and commercially available Ag/AgCl electrodes. As the acquired EEG signals are heavily disturbed by the gradient switching, intelligent filtering is applied to obtain a clean EEG signal.     

Evaluation and optimization of fMRI single-subject processing pipelines with NPAIRS and second-level CVA

In functional magnetic resonance imaging (fMRI) analysis, although the univariate general linear model (GLM) is currently the dominant approach to brain activation detection, there is growing interest in multivariate approaches such as principal component analysis, canonical variate analysis (CVA), independent component analysis and cluster analysis, which have the potential to reveal neural networks and functional connectivity in the brain. To understand the effect of processing options on performance of multivariate model-based fMRI processing pipelines with real fMRI data, we investigated the impact of commonly used fMRI preprocessing steps and optimized the associated multivariate CVA-based, single-subject processing pipelines with the NPAIRS (nonparametric prediction, activation, influence and reproducibility resampling) performance metrics [prediction accuracy and statistical parametric image (SPI) reproducibility] on the Fiswidgets platform. We also compared the single-subject SPIs of univariate GLM with multivariate CVA-based processing pipelines from SPM, FSL.FEAT, NPAIRS.GLM and NPAIRS.CVA software packages (or modules) using a novel second-level CVA. We found that for the block-design data, (a) slice timing correction and global intensity normalization have little consistent impact on the fMRI processing pipeline, but spatial smoothing, temporal detrending or high-pass filtering, and motion correction significantly improved pipeline performance across all subjects; (b) the combined optimization of spatial smoothing, temporal detrending and CVA model parameters on average improved between-subject reproducibility; and (c) the most important pipeline choices include univariate or multivariate statistical models and spatial smoothing. This study suggests that considering options other than simply using GLM with a fixed spatial filter may be of critical importance in determining activation patterns in BOLD fMRI studies.     

Effects of RF pulse profile and intra-voxel phase dispersion on MR fingerprinting with balanced SSFP readout

PurposeTo investigate possible errors in T1 and T2 quantification via MR fingerprinting with balanced steady-state free precession readout in the presence of intra-voxel phase dispersion and RF pulse profile imperfections, using computer simulations based on Bloch equations.Materials and methodsA pulse sequence with TR changing in a Perlin noise pattern and a nearly sinusoidal pattern of flip angle following an initial 180-degree inversion pulse was employed. Gaussian distributions of off-resonance frequency were assumed for intra-voxel phase dispersion effects. Slice profiles of sinc-shaped RF pulses were computed to investigate flip angle profile influences. Following identification of the best fit between the acquisition signals and those established in the dictionary based on known parameters, estimation errors were reported. In vivo experiments were performed at 3 T to examine the results.ResultsSlight intra-voxel phase dispersion with standard deviations from 1 to 3 Hz resulted in prominent T2 under-estimations, particularly at large T2 values. T1 and off-resonance frequencies were relatively unaffected. Slice profile imperfections led to under-estimations of T1, which became greater as regional off-resonance frequencies increased, but could be corrected by including slice profile effects in the dictionary. Results from brain imaging experiments in vivo agreed with the simulation results qualitatively.ConclusionMR fingerprinting using balanced SSFP readout in the presence of intra-voxel phase dispersion and imperfect slice profile leads to inaccuracies in quantitative estimations of the relaxation times.     

Assessment of scanner performance and normalization of estimated relaxation rate values

The purpose of this study was to develop and test a method for the assessment of Magnetic Resonance (MR) scanner performance suitable for routine brain MR studies and for normalization of calculated relaxation times. We hypothesized that regular monitoring of machine performance changes could provide a helpful normalization tool for calculating tissue MR parameters, thus contributing to support their use for longitudinal and comparative studies of both normal and diseased tissues.The method is based on the acquisition of phantom images during routine brain studies with standard spin-echo sequences. MR phantom and brain tissue parameters were used to assess the influence of machine related changes on relaxation parameter estimates. Experimental results showed that scanner performance may affect relaxation rate estimates. Phantom and in vivo results indicate that the correction method yields a reduction in variability of estimated phantom R1 values up to 29% and of R1 for different brain structures up to 17%. These findings support the validity of using brain coil phantoms for routine system monitoring and correction of tissue relaxation rates.     

Respiratory noise correction using phase information

Respiratory noise is a confounding factor in functional magnetic resonance imaging (MRI) data analysis. A novel method called Respiratory noise Correction using Phase information is proposed to retrospectively correct for the respiratory noise in functional MRI (fMRI) time series. It is demonstrated that the respiratory movement and the phase of functional MRI images are highly correlated in time. The signal fluctuation due to respiratory movements can be effectively estimated from the phase variation and removed from the functional MRI time series using a Wiener filtering technique. In our experiments, this new method is compared with RETROICOR, which requires recording respiration signal simultaneously in an fMRI experiment. The two techniques show comparable performance with respect to the respiratory noise correction for fMRI time series. However, this technique is more advantageous because there is no need for monitoring the subjects’ respiration or changing functional MRI protocols. This technique is also potentially useful for correcting respiratory noise from abnormal breathing or when the respiration is not periodic.     

Functional magnetic resonance imaging of awake monkeys: some approaches for improving imaging quality

Functional magnetic resonance imaging (fMRI) at high magnetic field strength can suffer from serious degradation of image quality because of motion and physiological noise, as well as spatial distortions and signal losses due to susceptibility effects. Overcoming such limitations is essential for sensitive detection and reliable interpretation of fMRI data. These issues are particularly problematic in studies of awake animals. As part of our initial efforts to study functional brain activations in awake, behaving monkeys using fMRI at 4.7 T, we have developed acquisition and analysis procedures to improve image quality with encouraging results.We evaluated the influence of two main variables on image quality. First, we show how important the level of behavioral training is for obtaining good data stability and high temporal signal-to-noise ratios. In initial sessions, our typical scan session lasted 1.5 h, partitioned into short (<10 min) runs. During reward periods and breaks between runs, the monkey exhibited movements resulting in considerable image misregistrations. After a few months of extensive behavioral training, we were able to increase the length of individual runs and the total length of each session. The monkey learned to wait until the end of a block for fluid reward, resulting in longer periods of continuous acquisition. Each additional 60 training sessions extended the duration of each session by 60 min, culminating, after about 140 training sessions, in sessions that last about 4 h. As a result, the average translational movement decreased from over 500 μm to less than 80 μm, a displacement close to that observed in anesthetized monkeys scanned in a 7-T horizontal scanner.Another major source of distortion at high fields arises from susceptibility variations. To reduce such artifacts, we used segmented gradient-echo echo-planar imaging (EPI) sequences. Increasing the number of segments significantly decreased susceptibility artifacts and image distortion. Comparisons of images from functional runs using four segments with those using a single-shot EPI sequence revealed a roughly twofold improvement in functional signal-to-noise-ratio and 50% decrease in distortion. These methods enabled reliable detection of neural activation and permitted blood-oxygenation-level-dependent-based mapping of early visual areas in monkeys using a volume coil.In summary, both extensive behavioral training of monkeys and application of segmented gradient-echo EPI sequence improved signal-to-noise ratio and image quality. Understanding the effects these factors have is important for the application of high field imaging methods to the detection of submillimeter functional structures in the awake monkey brain.     

Hemodynamic response (BOLD/fMRI) in focal epilepsy with reference to benzodiazepine effect

We studied a new procedure of BOLD/fMRI acquisition in epilepsy. They use the benzodiazepine effect to achieve a more reliable baseline for statistical analysis. The method works only in the MR domain without EEG correlation. It compares the EPI images during interictal epileptic discharges and the images “inactivated” by benzodiazepine.

The results in five out of eight patients show that this procedure in comparison with the EEG/fMRI method gives a net improvement of spatial definition of BOLD areas. These preliminary results seem to confirm the hypothesis that the better BOLD/fMRI procedure in epilepsy is to make use of physical features of MR that, unlike EEG, is not influenced by the distance of intercerebral sources and consequently allows a more complete and undistorted display of BOLD areas.     

A kernel machine-based fMRI physiological noise removal method

Functional magnetic resonance imaging (fMRI) technique with blood oxygenation level dependent (BOLD) contrast is a powerful tool for noninvasive mapping of brain function under task and resting states. The removal of cardiac- and respiration-induced physiological noise in fMRI data has been a significant challenge as fMRI studies seek to achieve higher spatial resolutions and characterize more subtle neuronal changes. The low temporal sampling rate of most multi-slice fMRI experiments often causes aliasing of physiological noise into the frequency range of BOLD activation signal. In addition, changes of heartbeat and respiration patterns also generate physiological fluctuations that have similar frequencies with BOLD activation. Most existing physiological noise-removal methods either place restrictive limitations on image acquisition or utilize filtering or regression based post-processing algorithms, which cannot distinguish the frequency-overlapping BOLD activation and the physiological noise. In this work, we address the challenge of physiological noise removal via the kernel machine technique, where a nonlinear kernel machine technique, kernel principal component analysis, is used with a specifically identified kernel function to differentiate BOLD signal from the physiological noise of the frequency. The proposed method was evaluated in human fMRI data acquired from multiple task-related and resting state fMRI experiments. A comparison study was also performed with an existing adaptive filtering method. The results indicate that the proposed method can effectively identify and reduce the physiological noise in fMRI data. The comparison study shows that the proposed method can provide comparable or better noise removal performance than the adaptive filtering approach.     

Reproducibility of MRI-derived measurements of right ventricular volumes and myocardial mass

Magnetic resonance (MR) imaging has been shown to provide accurate measurements of right ventricular (RV) volumes and myocardial mass. The purpose of this study was to evaluate the reproducibility of MR imaging, which in clinical practice may be as important as its absolute accuracy. The reproducibility of MR imaging measurements of the right ventricle was assessed by analyzing 40 serial functional MR imaging examinations of the right ventricle with variance component analysis. Standard deviations and 95% ranges for change were: for RV myocardial mass, 5.9 and 16 g; and for RV ejection fraction, 6.0% and 16%, respectively. Reproducibility was similar for cine and spin-echo MR imaging. The intraobserver and interobserver errors were especially large, indicating that observer subjectivity is the limiting factor in the interpretation of the MR images. This study suggests that the reproducibility of RV measurements is adequate to detect RV hypertrophy and a low ejection fraction in the individual patient. For accurate follow-up examinations, whereby smaller changes are to be detected, the reproducibility of MR imaging measurements may not be sufficient. More effort is needed to improve the reproducibility of MR imaging measurements.     

Accuracy of image registration between MRI and light microscopy in the ex vivo brain

A multistep procedure was developed to register magnetic resonance imaging (MRI) and histological data from the same sample in the light microscopy image space, with the ultimate goal of allowing quantitative comparisons of the two datasets. The fixed brain of an owl monkey was used to develop and test the procedure. In addition to the MRI and histological data, photographic images of the brain tissue block acquired during sectioning were assembled into a blockface volume to provide an intermediate step for the overall registration process. The MR volume was first registered to the blockface volume using a combination of linear and nonlinear registration, and two dimensional (2D) blockface sections were registered to corresponding myelin-stained sections using a combination of linear and nonlinear registration. Before this 2D registration, two major types of tissue distortions were corrected: tissue tearing and independent movement of different parts of the brain, both introduced during histological processing of the sections. The correction procedure utilized a 2D method to close tissue tears and a multiple iterative closest point (ICP) algorithm to reposition separate pieces of tissue in the image. The accuracy of the overall MR to micrograph registration procedure was assessed by measuring the distance between registered landmarks chosen in the MR image space and the corresponding landmarks chosen in the micrograph space. The average error distance of the MR data registered to micrograph data was 0.324±0.277 mm, only 8% larger than the width of the MRI voxel (0.3 mm).     

Multi-frequency interpolation in spiral magnetic resonance fingerprinting for correction of off-resonance blurring

Magnetic resonance fingerprinting (MRF) pulse sequences often employ spiral trajectories for data readout. Spiral k-space acquisitions are vulnerable to blurring in the spatial domain in the presence of static field off-resonance. This work describes a blurring correction algorithm for use in spiral MRF and demonstrates its effectiveness in phantom and in vivo experiments. Results show that image quality of T1 and T2 parametric maps is improved by application of this correction. This MRF correction has negligible effect on the concordance correlation coefficient and improves coefficient of variation in regions of off-resonance relative to uncorrected measurements.