Failure to direct detect magnetic field dephasing corresponding to ERP generation

Functional magnetic resonance imaging (fMRI) has become the method of choice for mapping brain activity in human subjects and detects changes in regional blood oxygenation and volume associated with local changes in neuronal activity. While imaging based on blood oxygenation level dependent (BOLD) contrast has good spatial resolution and sensitivity, the hemodynamic signal develops relatively slowly and is only indirectly related to neuronal activity. An alternative approach termed magnetic source magnetic resonance imaging (msMRI) is based on the premise that neural activity may be mapped by magnetic resonance imaging (MRI) with greater temporal resolution by detecting the local magnetic field perturbations associated with local neuronal electric currents. We used a hybrid ms/BOLD MRI method to investigate whether msMRI could detect signal changes that occur simultaneously at the time of the production of well-defined event-related potentials, the P300 and N170, in regions that previously have been identified as generators of these electrical signals. Robust BOLD activations occurred after some seconds, but we were unable to detect any significant changes in the T2*-weighted signal in these locations that correlated temporally with the timings of the evoked response potentials (ERPs).     

Functional phantom for fMRI: a feasibility study

Functional magnetic resonance imaging (fMRI) reveals changes in blood oxygen level-dependent (BOLD) signal after considerable processing. This paper describes the implementation and testing of an fMRI phantom where electric current applied to a thin wire within a proton-rich medium substituted BOLD distortion of the magnetic field; the scanner detects these two distortions as practically identical signal changes. The magnitude of the change depended on the current strength. The phantom has a number of possible applications. Signal changes across sessions, days, instruments and individuals could be monitored. Placing the phantom close to a subject during an fMRI experiment could allow differentiating sensitivity changes in the scanner due to instrumentation from changes in the subject's state and performance during the experiment. The spatial extent of brain activations and effects of various changes in the chain of image formation could be analyzed using current-induced "activations". Furthermore, the phantom could expedite fMRI sequence development by reducing the need to scan human subjects, who introduce uncertainty to the signal. Thus, this fMRI phantom could be useful for both cognitive fMRI studies and scanner calibration.     

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.     

Origins of intersubject variability of blood oxygenation level dependent and arterial spin labeling fMRI: implications for quantification of brain activity

Accurate localization of brain activity using blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) has been challenged because of the large BOLD signal within distal veins. Arterial spin labeling (ASL) techniques offer greater sensitivity to the microvasculature but possess low temporal resolution and limited brain coverage. In this study, we show that the physiological origins of BOLD and ASL depend on whether percent change or statistical significance is being considered. For BOLD and ASL fMRI data collected during a simple unilateral hand movement task, we found that in the area of the contralateral motor cortex the centre of gravity (CoG) of the intersubject coefficient of variation (CV) of BOLD fMRI was near the brain surface for percent change in signal, whereas the CoG of the intersubject CV for Z-score was in close proximity of sites of brain activity for both BOLD and ASL. These findings suggest that intersubject variability of BOLD percent change is vascular in origin, whereas the origin of inter-subject variability of Z-score is neuronal for both BOLD and ASL. For longer duration tasks (12 s or greater), however, there was a significant correlation between BOLD and ASL percent change, which was not evident for short duration tasks (6 s). These findings suggest that analyses directly comparing percent change in BOLD signal between pre-defined regions of interest using short duration stimuli, as for example in event-related designs, may be heavily weighted by large-vessel responses rather than neuronal responses.     

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.     

Illuminating the BOLD signal: combined fMRI-fNIRS studies

Functional magnetic resonance imaging (fMRI) is currently combined with electrophysiological methods to identify the relationship between neuronal activity and the blood oxygenation level-dependent (BOLD) signal. Several processes like neuronal activity, synaptic activity, vascular dilation, blood volume and oxygenation changes underlie both response modalities, that is, the electrophysiological signal and the vascular response. However, accessing single process relationships is absolutely mandatory when aiming at a deeper understanding of neurovascular coupling and necessitates studies on the individual building blocks of the vascular response. Combined fMRI and functional near-infrared spectroscopy studies have been performed to validate the correlation of the BOLD signal to the hemodynamic changes in the brain. Here we review the current status of the integration of both technologies and judge these studies in the light of recent findings on neurovascular coupling.     

Nonlinear responses of cerebral blood volume, blood flow and blood oxygenation signals during visual stimulation

Hemodynamic-based functional magnetic resonance imaging (fMRI) techniques provide a great utility for noninvasive functional brain mapping. However, because the hemodynamic signals reflect underlying neural activity indirectly, characterization of these signals following brain activation is essential for experimental design and data interpretation. In this report, the linear (or nonlinear) responses to neuronal activation of three hemodynamic parameters based primarily on changes of cerebral blood volume, blood flow and blood oxygenation were investigated by testing these hemodynamic responses' additivity property. Using a recently developed fMRI technique that acquires vascular space occupancy (VASO), arterial spin labeling (ASL) perfusion and blood oxygenation level-dependent (BOLD) signals simultaneously, the additivity property of the three hemodynamic responses in human visual cortex was assessed using various visual stimulus durations. Experiments on healthy volunteers showed that all three hemodynamic-weighted signals responded nonlinearly to stimulus durations less than 4 s, with the degree of nonlinearity becoming more severe as the stimulus duration decreased. Vascular space occupancy and ASL perfusion signals showed similar nonlinearity properties, whereas the BOLD signal was the most nonlinear. These data suggest that caution should be taken in the interpretation of hemodynamic-based signals in fMRI.     

Brain oscillatory activity during motor imagery in EEG-fMRI coregistration

The purpose of the present work was to investigate the correlation between topographical changes in brain oscillatory activity and the blood oxygenation level-dependent (BOLD) signal during a motor imagery (MI) task using electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) coregistration.     

Assessment of spatial BOLD sensitivity variations in fMRI using gradient-echo field maps

Clinical blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) is becoming increasingly valuable in, e.g., presurgical planning, but the commonly used gradient-echo echo-planar imaging (GE-EPI) technique is sometimes hampered by macroscopic field inhomogeneities. This can affect the degree of signal change that will occur in the GE-EPI images as a response to neural activation and the subsequent blood oxygenation changes, i.e., the BOLD sensitivity (BS). In this study, quantitative BS maps were calculated directly from gradient-echo field maps obtainable on most clinical scanners. In order to validate the accuracy of the calculated BS-maps, known shim gradients were applied and field maps and GE-EPI images of a phantom were acquired. Measured GE-EPI image intensity was then compared with the calculated (predicted) image intensity (pII) which was obtained from the field maps using theoretical expressions for image-intensity loss. The validated expressions for pII were used to calculate the corresponding predicted BOLD sensitivity (pBS) maps in healthy volunteers. Since the field map is assumed to be valid throughout an entire fMRI experiment, the influence of subject motion on the pBS maps was also assessed. To demonstrate the usefulness of such maps, pBS was investigated for clinically important functional areas including hippocampus, Broca's area and primary motor cortex. A systematic left/right pBS difference was observed in Broca's area and in the hippocampus, most likely due to magnetic field inhomogeneity of the particular MRI-system used in this study. For all subjects, the hippocampus showed pBS values above unity with a clear anterior–posterior gradient and with an abrupt drop to zero pBS in the anterior parts of hippocampus. It is concluded that GE field maps can be used to accurately predict BOLD sensitivity and that this parameter is useful to assess spatial variations which will influence fMRI experiments.     

In vivo mapping of functional domains and axonal connectivity in cat visual cortex using magnetic resonance imaging

Noninvasive cognitive neuroimaging studies based on functional magnetic resonance imaging (fMRI) are of ever-increasing importance for basic and clinical neurosciences. The explanatory power of fMRI could be greatly expanded, however, if the pattern of the neuronal circuitry underlying functional activation could be made visible in an equally noninvasive manner. In this study, blood oxygenation level-dependent (BOLD)-based fMRI and diffusion tensor imaging (DTI) were performed in the same cat visual cortex, and the foci of fMRI activation utilized as seeding points for 3D DTI fiber reconstruction algorithms, thus providing the map of the axonal circuitry underlying visual information processing. The methods developed in this study will lay the foundation for in vivo neuroanatomy and the ability for noninvasive longitudinal studies of brain development.     

人脑初级视皮层内事件相关型视觉刺激fMRI BOLD响应特性初步研究

基于脑血氧水平依赖(BOLD)对比的功能磁共振成像（fMRI）方法是研究脑功能活动的一种重要的无损伤探测手段，BOLD的机制及它与脑神经活动关系一直是国际上十分活跃的研究领域，尤其是在实验研究方面. 视觉刺激所引起的脑的初级视皮层(V1) 的BOLD响应的时间特性已有较多的研究，但是在这些研究中，有的结论认为BOLD对视觉刺激的响应是线性的，有的结论却是相反的. 我们采用事件关联型核磁共振功能成像（ER-fMRI）方法，研究不同的短暂视觉刺激持续时间下的BOLD响应，得到了视觉刺激下的脑激活图. 同时找出了视觉刺激时间分别是1、2、3、4、5和6 s的V1区的BOLD响应曲线，并初步显示出BOLD响应与刺激持续时间的线性关系.     

Regional homogeneity of resting-state fMRI contributes to both neurovascular and task activation variations

The task induced blood oxygenation level dependent signal changes observed using functional magnetic resonance imaging (fMRI) are critically dependent on the relationship between neuronal activity and hemodynamic response. Therefore, understanding the nature of neurovascular coupling is important when interpreting fMRI signal changes evoked via task. In this study, we used regional homogeneity (ReHo), a measure of local synchronization of the BOLD time series, to investigate whether the similarities of one voxel with the surrounding voxels are a property of neurovascular coupling. FMRI scans were obtained from fourteen subjects during bilateral finger tapping (FTAP), digit–symbol substitution (DSST) and periodic breath holding (BH) paradigm. A resting-state scan was also obtained for each of the subjects for 4 min using identical imaging parameters. Inter-voxel correlation analyses were conducted between the resting-state ReHo, resting-state amplitude of low frequency fluctuations (ALFF), BH responses and task activations within the masks related to task activations. There was a reliable mean voxel-wise spatial correlation between ReHo and other neurovascular variables (BH responses and ALFF). We observed a moderate correlation between ReHo and task activations (FTAP: r = 0.32; DSST: r = 0.22) within the task positive network and a small yet reliable correlation within the default mode network (DSST: r = − 0.08). Subsequently, a linear regression was used to estimate the contribution of ReHo, ALFF and BH responses to the task activated voxels. The unique contribution of ReHo was minimal. The results suggest that regional synchrony of the BOLD activity is a property that can explain the variance of neurovascular coupling and task activations; but its contribution to task activations can be accounted for by other neurovascular factors such as the ALFF.     

Fast spectroscopic imaging strategies for potential applications in fMRI

Technical aspects of two general fast spectroscopic imaging (SI) strategies, one based on gradient echo trains and the other on spin echo trains, are reviewed within the context of potential applications in the field of functional magnetic resonance imaging (fMRI). Fast spectroscopic imaging of water may prove useful for identifying mechanisms underlying the blood oxygenation level dependence (BOLD) of the water signal during brain activation studies. Reasonably rapid mapping of changes in proton signals from brain metabolites, like lactate, creatine or even neurotransmitter associated metabolites like GABA, is substantially more challenging but technically feasible particularly as higher field strengths become available. Fast spectroscopic methods directed towards the ³¹P signals from phosphocreatine (PCr) and adenosine tri-phosphates (ATP) are also technically feasible and may prove useful for studying cerebral energetics within fMRI contexts.     

Impact of intravenous nicotine on BOLD signal response to photic stimulation

Functional magnetic resonance imaging (fMRI) is increasingly being applied in the study of brain effects of nicotine. In addition, because tobacco smoking is common, many subjects studied with fMRI for other reasons may have appreciable levels of nicotine in plasma and brain during scanning. However, there is concern that the vascular effects of nicotine may alter the coupling between blood oxygen level dependent (BOLD) signal and neuronal activity. The objective of this study was to test for evidence of alteration of BOLD signal response of occipital cortex, a region with a relatively low concentration of neuronal nicotine receptors, to photic stimulation during intravenous infusion of nicotine. Nine nicotine dependent healthy smokers were withdrawn from nicotine under controlled conditions and then scanned while receiving photic stimulation and successive intravenous infusions of saline and nicotine. No evidence for an effect of nicotine on BOLD signal response to photic stimulation was detected at the doses studied. This observation suggests that nicotine does not alter the coupling between BOLD signal and neuronal activity in the visual cortex.     

Percept-related activity in the human somatosensory system: functional magnetic resonance imaging studies

In this paper, we review blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) studies addressing the neural correlates of touch, thermosensation, pain and the mechanisms of their cognitive modulation in healthy human subjects. There is evidence that fMRI signal changes can be elicited in the parietal cortex by stimulation of single mechanoceptive afferent fibers at suprathreshold intensities for conscious perception. Positive linear relationships between the amplitude or the spatial extents of BOLD fMRI signal changes, stimulus intensity and the perceived touch or pain intensity have been described in different brain areas. Some recent fMRI studies addressed the role of cortical areas in somatosensory perception by comparing the time course of cortical activity evoked by different kinds of stimuli with the temporal features of touch, heat or pain perception. Moreover, parametric single-trial functional MRI designs have been adopted in order to disentangle subprocesses within the nociceptive system.

Available evidence suggest that studies that combine fMRI with psychophysical methods may provide a valuable approach for understanding complex perceptual mechanisms and top-down modulation of the somatosensory system by cognitive factors specifically related to selective attention and to anticipation. The brain networks underlying somatosensory perception are complex and highly distributed. A deeper understanding of perceptual-related brain mechanisms therefore requires new approaches suited to investigate the spatial and temporal dynamics of activation in different brain regions and their functional interaction.     

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.     

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.     

Comparison of functional MR-venography and EPI-BOLD fMRI at 1.5 t

Functional magnetic resonance imaging (fMRI) of the brain using blood oxygenation level dependent (BOLD) contrast relies on the changes of paramagnetic deoxyhemoglobin concentration, which affects brain parenchyma and draining venous vessels. These changes in deoxyhemoglobin concentration in venous vessels can also be monitored using a high-resolution susceptibility-based MR-venography technique. Four volunteers participated in the study in which functional MR-venograms were compared with conventional echo-planar imaging (EPI)-BOLD-fMRI. In all cases, small venous vessels could be identified close to the areas of activation detected by conventional fMRI. In the venograms, task performance (finger tapping) resulted in a loss of venous vessel contrast compared to the resting state, which is consistent with a local decrease of deoxyhemoglobin concentration. MR-venography allows a direct visualization of the BOLD-effect at high spatial resolution. In combination with conventional fMRI, this technique may help to separate the contribution of brain parenchyma and venous vessels in fMRI studies.     

Activation mapping as a percentage of local excitation: fMRI stability within scans, between scans and across field strengths

Functional magnetic resonance imaging (fMRI) does not typically yield highly reproducible maps of brain activation. Maps can vary significantly even with constant scanning parameters and consistent task performance conditions (Liu et al., Magn. Reson. Med., 2004, 52:751-760). Reproducibility is even more of a problem when comparing fMRI signal magnitude and spatial extent of activation across scans involving different task performance levels, scan durations, pulse sequences or magnetic field strengths. In this report, the consistency of fMRI was reexamined by considering the relative spatial and temporal distribution of fMRI blood oxygen level dependent (BOLD) activation signals separately from the absolute magnitude of the activation signal in each brain area. Subjects repeatedly performed the same simple motor task but under a variety of imaging conditions, using both spiral and standard echo-planar pulse sequences and at 1.5- and 4.0-T magnetic field strengths. The results demonstrate that the absolute amplitude of BOLD statistical activation signals varied significantly across time and scanning conditions, but the relative spatial pattern of BOLD activation was highly reproducible across all conditions. Analysis of realistic simulated fMRI data sets indicates that stability of relative activation patterns could provide a useful tool for assessing the accuracy of fMRI maps.     

A two-compartment gel phantom for optimization and quality assurance in clinical BOLD fMRI

Clinical applications of blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) depend heavily on robust paradigms, imaging methods and analysis procedures. In this work, as a means to optimize and perform quality assurance of the entire imaging and analysis chain, a phantom that provides a well known and reproducible signal change similar to a block type fMRI experiment is presented. It consists of two gel compartments with slightly different T2 that dynamically enter and leave the imaged volume. The homogeneous gel in combination with a cylindrical geometry results in a well-defined T*2 difference causing a signal difference between the two compartments in T*2-weighted MR images. From time series data obtained with the phantom, maps of percent signal change (PSC) and t-values are calculated. As an example of image parameter optimisation, the phantom is demonstrated to be useful for accurate determination of the influence of echo time (TE) on BOLD fMRI results, taking the t-value as a measure of sensitivity. In addition, the phantom is proposed as a tool for quality assurance (QA) since reproducible time series and t-maps are obtained in a series of independent repeat experiments. The phantom is relatively simple to build and can therefore be used by any clinical fMRI center.