Component structure of event-related fMRI responses in the different neurovascular compartments

In most functional magnetic resonance imaging (fMRI) studies, brain activity is localized by observing changes in the blood oxygenation level-dependent (BOLD) signal that are believed to arise from capillaries, venules and veins in and around the active neuronal population. However, the contribution from veins can be relatively far downstream from active neurons, thereby limiting the ability of BOLD imaging methods to precisely pinpoint neural generators. Hemodynamic measures based on apparent diffusion coefficients (ADCs) have recently been used to identify more upstream functional blood flow changes in the capillaries, arterioles and arteries. In particular, we recently showed that, due to the complementary vascular sensitivities of ADC and BOLD signals, the voxels conjointly activated by both measures may identify the capillary networks of the active neuronal areas. In this study, we first used simultaneously acquired ADC and BOLD functional imaging signals to identify brain voxels activated by ADC only, by both ADC and BOLD and by BOLD only, thereby delineating voxels relatively dominated by the arterial, capillary, and draining venous neurovascular compartments, respectively. We then examined the event-related fMRI BOLD responses in each of these delineated neurovascular compartments, hypothesizing that their event-related responses would show different temporal componentries. In the regions activated by both the BOLD and ADC contrasts, but not in the BOLD-only areas, we observed an initial transient signal reduction (an initial dip), consistent with the local production of deoxyhemoglobin by the active neuronal population. In addition, the BOLD-ADC overlap areas and the BOLD-only areas showed a clear poststimulus undershoot, whereas the compartment activated by only ADC did not show this component. These results indicate that using ADC contrast in conjunction with BOLD imaging can help delineate the various neurovascular compartments, improve the localization of active neural populations, and provide insight into the physiological mechanisms underlying the hemodynamic signals.     

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.     

Simultaneous imaging of total cerebral hemoglobin concentration,oxygenation, and blood flow during functional activation

A simple instrument is demonstrated for high-resolution simultaneous imaging of total hemoglobin concentration and oxygenation and blood flow in the brain by combining rapid multiwavelength imaging with laser speckle contrast imaging. The instrument was used to image changes in oxyhemoglobin and deoxyhemoglobin and blood flow during cortical spreading depression and single whisker stimulation in rats through a thinned skull. The ability to image blood flow and hemoglobin concentration changes simultaneously with high resolution will permit detailed quantitative analysis of the spatiotemporal hemodynamics of functional brain activation, including imaging of oxygen metabolism. This is of significance to the neuroscience community and will lead to a better understanding of the interrelationship of neural, metabolic, and hemodynamic processes in normal and diseased brains.     

Quantification of venous blood signal contribution to BOLD functional activation in the auditory cortex at 3 T

Most modern techniques for functional magnetic resonance imaging (fMRI) rely on blood-oxygen-level-dependent (BOLD) contrast as the basic principle for detecting neuronal activation. However, the measured BOLD effect depends on a transfer function related to neurophysiological changes accompanying electrical neural activation. The spatial accuracy and extension of the region of interest are determined by vascular effect, which introduces incertitude on real neuronal activation maps. Our efforts have been directed towards the development of a new methodology that is capable of combining morphological, vascular and functional information; obtaining new insight regarding foci of activation; and distinguishing the nature of activation on a pixel-by-pixel basis. Six healthy volunteers were studied in a parametric auditory functional experiment at 3 T; activation maps were overlaid on a high-resolution brain venography obtained through a novel technique. The BOLD signal intensities of vascular and nonvascular activated voxels were analyzed and compared: it was shown that nonvascular active voxels have lower values for signal peak (P<10(-7)) and area (P<10(-8)) with respect to vascular voxels. The analysis showed how venous blood influenced the measured BOLD signals, supplying a technique to filter possible venous artifacts that potentially can lead to misinterpretation of fMRI results. This methodology, although validated in the auditory cortex activation, maintains a general applicability to any cortical fMRI study, as the basic concepts on which it relies on are not limited to this cortical region. The results obtained in this study can represent the basis for new methodologies and tools that are capable of adding further characterization to the BOLD signal properties.     

GRAPPA-based susceptibility-weighted imaging of normal volunteers and patients with brain tumor at 7 T

Susceptibility-weighted imaging (SWI) is a valuable technique for high-resolution imaging of brain vasculature that greatly benefits from the emergence of higher field strength MR scanners. Autocalibrating partially parallel imaging techniques can be employed to reduce lengthy acquisition times as long as the decrease in signal-to-noise ratio does not significantly affect the contrast between vessels and brain parenchyma. This study assessed the feasibility of a Generalized Autocalibrating Partially Parallel Acquisition (GRAPPA)-based SWI technique at 7 T in both healthy volunteers and brain tumor patients. GRAPPA-based SWI allowed a twofold or more reduction in scan time without compromising vessel contrast and small vessel detection. Postprocessing parameters for the SWI needed to be modified for patients where the tumor causes high-frequency phase wrap artifacts but did not adversely affect vessel contrast. GRAPPA-based SWI at 7 T revealed regions of microvascularity, hemorrhage and calcification within heterogeneous brain tumors that may aid in characterizing active or necrotic tumor and monitoring treatment effects.     

Decreases in ADC observed in tissue areas during activation in the cat visual cortex at 9.4 T using high diffusion sensitization

Recent studies in the human visual cortex using diffusion-weighted functional magnetic resonance imaging (fMRI) have suggested that the apparent diffusion coefficient (ADC) decreases, in contrast to earlier studies that consistently reported ADC increases during neuronal activation. The changes, in either case, are hypothesized to provide the ability to improve the spatial specificity of fMRI over conventional blood-oxygenation-level-dependent (BOLD) methods. Most recently, the ADC decreases have been suggested as originating from transient cell swelling caused by either shrinkage of the extracellular space or some intracellular neuronal process that precedes the hemodynamic response. All of these studies have been conducted in humans and at lower magnetic fields, which can be limited by the signal-to-noise ratio (SNR). The low SNR can lead to significant partial-volume effects because of the lower spatial resolutions required to attain sufficient SNR in diffusion-weighted images. Human studies also have the potential confound of motion. At high magnetic fields and in animal model studies, these limitations are alleviated. At high fields, SNR increases, tissue signals are enhanced and signal changes inside the blood are significantly reduced compared to lower fields. In this work, we were able to measure a small but significant ADC decrease in tissue areas, in conjunction with brain activation in the cat visual cortex at 9.4 T when using highly diffusion-weighted images (b>1200 s/mm2) where intravascular effects are minimal. When using low b-values, delayed increases in the tissue ADC during activation were observed. No significant changes in ADC were observed in surface vessels for any diffusion weighting. Furthermore, we did not observe any temporal differences in the highly diffusion-weighted data compared to BOLD; however, although the changes may likely be vascular in nature, they are highly localized to the tissue areas.     

Functional MRI of the motor cortex using a conventional gradient system: comparison of FLASH and EPI techniques

Gradient echo (GE) and echo planar imaging (EPI) techniques are two different approaches to functional MRI (fMRI). In contrast to GE sequences, the ultra short EPI technique facilitates fMRI experiments with high spatial and temporal resolution or mapping of the whole brain. Although it has become the method of choice for fMRI, EPI is generally restricted to modern scanners with a strong gradient system. The aim of our study was to evaluate the applicability of EPI for fMRI of the motor cortex using a 1.5 T scanner with a conventional gradient system of 10 mT/m (rise time: 1 ms). Therefore, EPI was compared with a well-established high resolution fast low angle shot (FLASH) technique (matrix size 128²). The FLASH technique was applied additionally with a 64² matrix size to exclude influences caused by different spatial resolution, because the EPI sequence was restricted to a 64² matrix size. A total of 35 healthy volunteers were included in this study. The task consisted of clenching and spreading of the right hand. FLASH and EPI techniques were compared regarding geometric distortions as well as qualitative and quantitative fMRI criteria: Mean signal increase between activation and rest and the area of activation were measured within the contralateral, ipsilateral, and supplementary motor cortex. The quality of subtraction images between activation and rest, as well as the quality of z-maps and time course within activated regions of interest, was evaluated visually. EPI revealed significant distortions of the anterior and postior brain margins; lateral distortions (relevant for the motor cortex) could be neglected in most cases. The mean signal increase was significantly higher using FLASH 128² compared to FLASH 64² and EPI 64², whereas the activated areas proved to be smaller in FLASH 128² functional images. Both results can be explained by well-documented partial volume effects, caused by different voxel size. Similar quality of the subtraction images and of the time courses in different regions of interest were found for all techniques under investigation, but slightly reduced quality of z-map in FLASH 128². Within the limits of reproducibility and measurement accuracy, the location of contralateral activation was similar using FLASH and EPI sequences. In conclusion, EPI proved to be a reliable technique for fMRI of the motor cortex, even on an MR scanner with a conventional gradient system.     

Synchronized detection of minute electrical currents with MRI using Lorentz effect imaging

The blood oxygenation level-dependent (BOLD) effect is the most commonly used contrast mechanism in functional magnetic resonance imaging (fMRI), due to its relatively high spatial resolution and sensitivity. However, the ability of BOLD fMRI to accurately localize neuronal activation in space and time is limited by the inherent hemodynamic modulation. There is hence a need to develop alternative MRI methods that can directly image neuroelectric activity, thereby achieving both a high temporal resolution and spatial specificity as compared to conventional BOLD fMRI. In this paper, we extend the Lorentz effect imaging technique, which can detect spatially incoherent yet temporally synchronized minute electrical activity in a strong magnetic field, and demonstrate its feasibility for imaging randomly oriented electrical currents on the order of microamperes with a temporal resolution on the order of milliseconds in gel phantoms. This constitutes a promising step towards its application to direct imaging of neuroelectric activity in vivo, which has the same order of current density and temporal synchrony.     

Fast functional brain signal changes detected by diffusion weighted fMRI

Functional magnetic resonance imaging (fMRI) has become the method of choice in the study of system neuroscience, as evidenced by an explosion of such literature in the past decade. Contrast mechanisms based on the blood oxygenation level, volume, and flow changes have been used to non-invasively detect brain activation secondary to the neuronal activity. However, because of the hemodynamic modulations inherent in these signals, their spatial and temporal characteristics are influenced by the complex geometry and varying delivery speed of the brain vasculature. Consequently, spatial dispersions and temporal delays are commonly seen in the brain activity using fMRI. It is thus of critical importance to investigate alternative contrast mechanisms that may offer shorter temporal delays and more direct spatial localization. In light of a recent phantom study which demonstrated the possibility to detect the destructive phase addition from the spatially incoherent, yet temporally synchronized, displacements caused by the Lorentz force experienced during electrical conduction within a strong magnetic field, we seek to apply similar imaging technique to investigate the functional signal changes that may provide alternative temporal and spatial characteristics. It is found that by using heavy diffusion weighting, which is one form of displacement encoding strategies, to remove the vascular signal and sensitize the minute and incoherent displacement, one can detect fast dynamic signal changes synchronized to the task. This finding may help take an initial step toward direct non-invasive MRI detection of the neuronal activity with improved temporal accuracy.     

Real-time animal functional magnetic resonance imaging and its application to neuropharmacological studies

In pharmacological magnetic resonance imaging (phMRI) with anesthetized animals, there is usually only a single time window to observe the dynamic signal change to an acute drug administration since subsequent drug injections are likely to result in altered response properties (e.g., tolerance). Unlike the block-design experiments in which fMRI signal can be elicited with multiple repetitions of a task, these single-event experiments require stable baseline in order to reliably identify drug-induced signal changes. Such factors as subject motion, scanner instability and/or alterations in physiological conditions of the anesthetized animal could confound the baseline signal. The unique feature of such functional MRI (fMRI) studies necessitates a technique that is able to monitor MRI signal in a real-time fashion and to interactively control certain experimental procedures. In the present study, an approach for real-time MRI on a Bruker scanner is presented. The custom software runs on the console computer in parallel with the scanner imaging software, and no additional hardware is required. The utility of this technique is demonstrated in manganese-enhanced MRI (MEMRI) with acute cocaine challenge, in which temporary disruption of the blood-brain barrier (BBB) is a critical step for MEMRI experiments. With the aid of real-time MRI, we were able to assess the outcome of BBB disruption following bolus injection of hyperosmolar mannitol in a near real-time fashion prior to drug administration, improving experimental success rate. It is also shown that this technique can be applied to monitor baseline physiological conditions in conventional fMRI experiments using blood oxygenation level-dependent (BOLD) contrast, further demonstrating the versatility of this technique.     

增强低场下脑功能磁共振成像显著性的研究

实现了基于低场0.35 T磁共振成像系统的大脑功能磁共振成像（functional Magnetic Resonance Imaging,fMRI）的研究. 基于质子密度加权的快速自旋回波(Turbo Spin Echo,TSE)图像,重点研究增强低场fMRI显著性的方法,目的在于提高低场fMRI的可用性. 结果表明：健康受试者在执行手动任务期间,大脑运动区的信号强度变化可以由基于血管外质子信号增强 (Signal Enhancement by Extravascular water Protons,EEP)的对比机制探测. 优化TSE序列参数能提高图像SNR和扫描速度,并在统计分析中增加外在屏蔽图像,可以有效地提高低场下fMRI研究结果的显著性.     

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.     

On the nature of the BOLD fMRI contrast mechanism

Since its development about 15 years ago, functional magnetic resonance imaging (fMRI) has become the leading research tool for mapping brain activity. The technique works by detecting the levels of oxygen in the blood, point by point, throughout the brain. In other words, it relies on a surrogate signal, resulting from changes in oxygenation, blood volume and flow, and does not directly measure neural activity. Although a relationship between changes in brain activity and blood flow has long been speculated, indirectly examined and suggested and surely anticipated and expected, the neural basis of the fMRI signal was only recently demonstrated directly in experiments using combined imaging and intracortical recordings. In the present paper, we discuss the results obtained from such combined experiments. We also discuss our current knowledge of the extracellularly measured signals of the neural processes that they represent and of the structural and functional neurovascular coupling, which links such processes with the hemodynamic changes that offer the surrogate signal that we use to map brain activity. We conclude by considering applications of invasive MRI, including injections of paramagnetic tracers for the study of connectivity in the living animal and simultaneous imaging and electrical microstimulation.     

Postprocessing of functional MRI data of motor cortex stimulation measured with a standard 1.5 T imager

Functional magnetic resonance imaging (fMRI) is usually based on acquisition of alternating series of images under rest and an activation task (stimulus). Brain activation maps can be generated from fMRI data sets by applying several mathematical methods. Two methods of image postprocessing have been compared: (i) simple difference of mean values between rest and stimulation, and (ii) Student's t-test. The comparison shows that the difference method is very sensitive to arbitrary signal fluctuations as seen mainly in large vessels (e.g., in the sagittal sinus), leading to insignificantly activated spots in brain activation maps. In contrary, Student's t-test maps show strongly reduced sensitivity for fluctuations and have the advantage of giving activation thresholds by setting significance levels. This allows the comparison of activation strength between patient collectives by using a grid overlay technique leading to an observer independent quantification of the stimulation effects. The method was able to reproduce previous findings of activation differences between healthy volunteers and schizophrenic patients. Moreover, a simple algorithm for the correction of slight head movements during the functional imaging task is presented. The algorithm is based on shifting the fMRI data set relative to a reference image by maximizing the linear correlation coefficients. This leads to a further reduction of insignificant brain activation and to an improvement in brain activation map quality.     

A method for determining venous contribution to BOLD contrast sensory activation

While BOLD contrast reflects hemodynamic changes within capillaries serving neural tissue, it also has a venous component. Studies that have determined the relation of large blood vessels to the activation map indicate that veins are the source of the largest response, and the most delayed in time. It would be informative if the location of these large veins could be extracted from the properties of the functional responses, since vessels are not visible in BOLD contrast images. The present study describes a method for investigating whether measures taken from the functional response can reliably predict vein location, or at least be useful in down-weighting the venous contribution to the activation response, and illustrates this method using data from one subject. We combined fMRI at 3 Tesla with high-resolution anatomic imaging and MR venography to test whether the intrinsic properties of activation time courses corresponded to tissue type. Measures were taken from a gamma fit to the functional response. Mean magnitude showed a significant effect of tissue type (p < 0.001) where CSF > veins ≈ gray matter > white matter. Mean delays displayed the same ranking across tissue types (p < 0.001), except that veins > gray matter. However, measures for all tissue types were distributed across an overlapping range. A logistic regression model correctly discriminated 72% of the veins from gray matter in the absence of independent information of macroscopic vessels (ROC = 0.72). While tissue classification was not perfect for this subject, weighting the T contrast by the predicted probabilities materially reduced the venous component to the activation map.     

The role of voxel aspect ratio in determining apparent vascular phase behavior in susceptibility weighted imaging

Susceptibility weighted imaging (SWI) uses apparent phase contrast to enhance the contrast-to-noise ratio (CNR) in the magnitude image. In theory, the apparent phase will depend on the aspect ratio when both venous blood and parenchyma occupy the same voxel. To demonstrate the maximal expected effect of the external field from a vein, we model the vein as an infinitely long cylinder perpendicular to the main magnetic field. The results show that the apparent phase of a voxel in the image is a function of resolution, vessel size and, to a lesser degree, vessel center within the voxel. The simulations explain why a negative-phase mask has worked in SWI processing of high-resolution images collected in the transverse direction, despite the expected positive-phase behavior for vessels perpendicular to the main field. The predicted phase behavior from the simulations is in good agreement with that observed from human brain datasets.     

Detection of early venous filling in gliomas on MRI: preliminary study by 2D time-resolved dynamic contrast-enhanced MR angiography with echo-sharing technique.

We evaluated the detection of early venous filling of gliomas by 2D time resolved dynamic contrast enhanced MR digital subtraction angiography (MR-DSA) with echo-sharing technique and compared the results with those of conventional contrast digital subtraction angiography (C-DSA). C-DSA and MR-DSA examinations were performed in eight patients with malignant gliomas and compared with regard to the visualization of early filling veins; time intensity curves of arteries, early filling veins and normal veins were made, and rise time and time to peak were evaluated. MR-DSA visualized 12 out of 17 early filling veins depicted on C-DSA. The failure of five veins to be depicted may be due to the overlapping of other structures, such as other vessels and tumor stain. On time intensity curves, the mean difference in rise time was 0.9 sec between the artery and early filling vein, and the mean difference of time to peak was 1.6 sec. C-DSA has been the modality of choice in demonstrating early venous filling, a useful finding in the differential diagnosis of gliomas. However the high temporal resolution of MR-DSA with echo-sharing technique provides sufficient visualization of early venous filling of gliomas. Additional information for precise differential diagnosis may be obtained by adding MR-DSA to the imaging protocol for gliomas.     

On the use of information theory for the analysis of the relationship between neural and imaging signals

Functional magnetic resonance imaging (fMRI) is a widely used method for studying the neural basis of cognition and of sensory function. A potential problem in the interpretation of fMRI data is that fMRI measures neural activity only indirectly, as a local change of deoxyhemoglobin concentration due to the metabolic demands of neural function. To build correct sensory and cognitive maps in the human brain, it is thus crucial to understand whether fMRI and neural activity convey the same type of information about external correlates. While a substantial experimental effort has been devoted to the simultaneous recordings of hemodynamic and neural signals, so far, the development of analysis methods that elucidate how neural and hemodynamic signals represent sensory information has received less attention. In this article, we critically review why the analytical framework of information theory, the mathematical theory of communication, is ideally suited to this purpose. We review the principles of information theory and explain how they could be applied to the analysis of fMRI and neural signals. We show that a critical advantage of information theory over more traditional analysis paradigms commonly used in the fMRI literature is that it can elucidate, within a single framework, whether an empirically observed correlation between neural and fMRI signals reflects either a similar stimulus tuning or a common source of variability unrelated to the external stimuli. In addition, information theory determines the extent to which these shared sources of stimulus signal and of variability lead fMRI and neural signals to convey similar information about external correlates. We then illustrate the formalism by applying it to the analysis of the information carried by different bands of the local field potential. We conclude by discussing the current methodological challenges that need to be addressed to make the information-theoretic approach more robustly applicable to the simultaneous recordings of neural and imaging data.     

BOLD signal and vessel dynamics: a hierarchical cluster analysis

The aim of the present study was to analyze blood oxygenation level-dependent (BOLD) signal variation during an apnea-based task in order to assess the capability of a functional magnetic resonance imaging (fMRI) procedure to estimate cerebral vascular dynamic effects. We measured BOLD contrast by hierarchical cluster analysis in healthy subjects undergoing an fMRI experiment, in which the task paradigm was one phase of inspirational apnea (IA). By processing the time courses of the fMRI experiment, analysis was performed only on a subclass of all the possible signal patterns; basically, root mean square and absolute variation differences have been calculated. Considering the baseline value obtained by computing the mean value of the initial rest period as reference, particular voxels showed relative important variations during the IA task and during the recovery phase following the IA. We focused our interest on the signal response of voxels that would correspond mainly to white and gray matter regions and that also may be affected by the proximity of large venous vessels. The results are presented as maps of space-temporal distribution of time series variations with two levels of hierarchical clustering among voxels with low to high initial response. Furthermore, we have presented a clustering of the signal response delay, conducting to a partition and identification of specified brain sites.     

Quantitative NumART2* mapping in functional MRI studies at 1.5 T

Quantitative mapping of the effective transverse relaxation time, T₂* and proton density was performed in a motor activation functional MRI (fMRI) study using multi-echo, echo planar imaging (EPI) and NumART₂* (Numerical Algorithm for Real time T₂*). Comparisons between NumART₂* and conventional single echo EPI with an echo time of 64 ms were performed for five healthy participants examined twice. Simulations were also performed to address specific issues associated with the two techniques, such as echo time-dependent signal variation. While the single echo contrast varied with the baseline T₂* value, relative changes in T₂* remained unaffected. Statistical analysis of the T₂* maps yielded fMRI activation patterns with an improved statistical detection relative to conventional EPI but with less activated voxels, suggesting that NumART₂* has superior spatial specificity. Two effects, inflow and dephasing, that may explain this finding were investigated. Particularly, a statistically significant increase in proton density was found in a brain area that was detected as activated by conventional EPI but not by NumART₂* while no such changes were observed in brain areas that showed stimulus correlated signal changes on T₂* maps.