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.     

To smooth or not to smooth? ROC analysis of perfusion fMRI data

Blood oxygenation level dependent (BOLD) contrast has been widely used for visualizing regional neural activation. Temporal filtering and parameter estimation algorithms are generally used to account for the intrinsic temporal autocorrelation present in BOLD data. Arterial spin labeling perfusion imaging is an emerging methodology for visualizing regional brain function both at rest and during activation. Perfusion contrast manifests different noise properties compared with BOLD contrast, represented by the even distribution of noise power and spatial coherence across the frequency spectrum. Consequently, different strategies are expected to be employed in the statistical analysis of functional magnetic resonance imaging (fMRI) data based on perfusion contrast. In this study, the effect of different analysis methods upon signal detection efficacy, as assessed by receiver operator characteristic (ROC) measures, was examined for perfusion fMRI data. Simulated foci of neural activity of varying amplitude and spatial extent were added to resting perfusion data, and the accuracy of each analysis was evaluated by comparing the results with the known distribution of pseudo-activation. In contrast to the BOLD fMRI, temporal smoothing or filtering reduces the power of perfusion fMRI data analyses whereas spatial smoothing is beneficial to the efficacy of analyses.     

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.     

Effects of hypoglycemia on human brain activation measured with fMRI

Functional magnetic resonance imaging (fMRI) was used to measure the effects of acute hypoglycemia caused by passive sensory stimulation on brain activation. Visual stimulation was used to generate blood-oxygen-level-dependent (BOLD) contrast, which was monitored during hyperinsulinemic hypoglycemic and euglycemic clamp studies. Hypoglycemia (50 +/- 1 mg glucose/dl) decreased the fMRI signal relative to euglycemia in 10 healthy human subjects: the fractional signal change was reduced by 28 +/- 12% (P < .05). These changes were reversed when euglycemia was restored. These data provide a basis of comparison for studies that quantify hypoglycemia-related changes in fMRI activity during cognitive tasks based on visual stimuli and demonstrate that variations in blood glucose levels may modulate BOLD signals in the healthy brain.     

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.     

Multimodal imaging: an evaluation of univariate and multivariate methods for simultaneous EEG/fMRI

The combination of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) has been proposed as a tool to study brain dynamics with both high temporal and high spatial resolution. Multimodal imaging techniques rely on the assumption of a common neuronal source for the different recorded signals. In order to maximally exploit the combination of these techniques, one needs to understand the coupling (i.e., the relation) between electroencephalographic (EEG) and fMRI blood oxygen level-dependent (BOLD) signals.     

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.     

Mapping of the cerebral response to acetazolamide using graded asymmetric spin echo EPI

Cerebral vascular reactivity in different regions of the rat brain was quantitatively characterized by spatial and temporal measurements of blood oxygenation level-dependent (BOLD)-fMRI signals following intravenous administration of the carbonic anhydrase inhibitor acetazolamide: this causes cerebral vasodilatation through a cerebral extracellular acidosis that spares neuronal metabolism and vascular smooth muscle function, thus separating vascular and cerebral metabolic events. An asymmetric spin echo-echo planar imaging (ASE-EPI) pulse sequence sensitised images selectively to oxygenation changes in the microvasculature; use of a surface coil receiver enhanced image signal-to-noise ratios (SNRs). Image SNRs and hardware integrity were verified by incorporating quality assurance procedures; cardiorespiratory stability in the physiological preparations were monitored and maintained through the duration of the experiments. These conditions made it possible to apply BOLD contrast fMRI to map regional changes in cerebral perfusion in response to acetazolamide administration. Thus, fMRI findings demonstrated cerebral responses to acetazolamide that directly paralleled the known physiological actions of acetazolamide and whose time courses were similar through all regions of interest, consistent with acetazolamide's initial distribution in brain plasma, where it affects cerebral haemodynamics by acting at cerebral capillary endothelial cells. However, marked variations in the magnitude of the responses suggested relative perfusion deficits in the hippocampus and white matter regions correlating well with their relatively low vascularity and the known vulnerability of the hippocampus to ischaemic damage.     

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.     

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.     

High spatial resolution BOLD fMRI using simultaneous multislice excitation with echo-shifting gradient echo at 7 Tesla

We introduce an accelerated gradient echo (GRE) sequence combining simultaneous multislice excitation (SMS) with echo-shifting technique for high spatial resolution blood oxygen level dependent (BOLD) functional MRI (fMRI). The simulation was conducted to optimize scan parameters. To validate the feasibility of the proposed technique, the visual and motor task experiments were performed at 7.0 Tesla (T). The single-shot EPI sequence was also applied in comparison with the proposed technique. The simulation results showed that an optimized flip angle of 9° provided maximal BOLD contrast for our scanning scheme, allowing low power deposition and SMS acceleration factor of 5. Additionally, parallel acquisition imaging with acceleration factor of 2 was utilized, which allowed a total acceleration factor of 10 in volunteer study. The experiment results showed that geometric distortion-free BOLD images with voxel size of 1.0 × 1.0 × 2.5 mm³ were obtained. Significant brain activation was identified in both visual and motor task experiments, which were in accordance with previous investigations. The proposed technique has potential for high spatial resolution fMRI at ultra-high field because of its sufficient BOLD sensitivity as well as improved acquisition speed over conventional GRE-based techniques.     

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.     

Nonlinear statistical properties of fMRI signals in human visual cortex during resting-state

The purpose of the current work is to study nonlinear dynamics in neuronal activity within human brain visual cortex based on blood-oxygen-level dependent (BOLD) contrast imaging. In particular, based on functional magnetic resonance imaging (fMRI) signals, measures of fractality, complexity, and state disorder are estimated from central and peripheral eccentricity bands across three visual areas. Statistical results from analysis of 48750 resting-state fMRI signals show evidence that nonlinear dynamics of neuronal activity in resting-state in central and peripheral eccentricity bands of human visual cortex are persistent. However, they exhibit heterogeneous variability across eccentricity bands and visual areas. Also, information content in first visual area is more ordered than in the second one, whilst information content in the third visual area is the least ordered. These interesting nonlinear statistical properties are a further step toward understanding neuronal activity and nonlinear dynamics in human brain visual cortex.     

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.     

An investigation of the relationship between BOLD and perfusion signal changes during epileptic generalised spike wave activity

In pathological conditions interpretation of functional magnetic resonance imaging (fMRI) results can be difficult. This is due to a reliance on the assumed coupling between neuronal activity and changes in cerebral blood flow (CBF) and oxygenation. We wanted to investigate the coupling between blood oxygen level dependant contrast (BOLD) and CBF time courses in epilepsy patients with generalised spike wave activity (GSW) to better understand the underlying mechanisms behind the EEG-fMRI signal changes observed, especially in regions of negative BOLD response (NBR). Four patients with frequent GSW were scanned with simultaneous electroencephalographic (EEG)-fMRI with BOLD and arterial spin labeling (ASL) sequences. We examined the relationship between simultaneous CBF and BOLD measurements by looking at the correlation of the two signals in terms of percentage signal change on a voxel-by-voxel basis. This method is not reliant on coincident activation. BOLD and CBF were positively correlated in patients with epilepsy during background EEG activity and GSW. The subject average value of the Delta CBF/Delta BOLD slope lay between +19 and +36 and also showed spatial variation which could indicate areas with altered vascular response. There was not a significant difference between Delta CBF/Delta BOLD during GSW, suggesting that neurovascular coupling to BOLD signal is generally maintained between states and, in particular, within areas of NBR.     

Functional magnetic resonance imaging reference phantom

Functional magnetic resonance imaging (fMRI) is widely used to pinpoint active brain areas. Changes in neuronal activity modulate the local blood oxygenation level, and the associated modulation of the magnetic field homogeneity can be detected with magnetic resonance imaging. Thus, the blood oxygenation level-dependent (BOLD) fMRI indirectly measures neuronal activity. Similar modulation of magnetic field homogeneity was here elicited by other means to generate a BOLD-like change in a new phantom constructed to provide reference activations during fMRI. Magnetic inhomogeneities were produced by applying current to coils located near the phantom containing 1.5 ml of Gd-doped water. The signal-to-noise ratio of the images, produced by gradient-recalled echo-planar imaging, varied between 104 and 107 at a selected voxel when the field was and was not inhomogenized, respectively. The contrast of signals between homogeneous and inhomogeneous conditions was generally stable, except in 3% of time points. During the periods of greatest deviations an observable change would have been detected in a simultaneously measured BOLD signal. Such changes could result from the imaging method or occur through glitches in hardware or alterations in the measurement environment. With identical measurement setups, the phantom could allow comparing intersession or intersubject brain activations.     

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.     

Dissecting cognitive stages with time-resolved fMRI data: a comparison of fuzzy clustering and independent component analysis

In combination with cognitive tasks entailing sequences of sensory and cognitive processes, event-related acquisition schemes allow using functional MRI to examine not only the topography but also the temporal sequence of cortical activation across brain regions (time-resolved fMRI). In this study, we compared two data-driven methods--fuzzy clustering method (FCM) and independent component analysis (ICA)--in the context of time-resolved fMRI data collected during the performance of a newly devised visual imagery task. We analyzed a multisubject fMRI data set using both methods and compared their results in terms of within- and between-subject consistency and spatial and temporal correspondence of obtained maps and time courses. Both FCM and spatial ICA allowed discriminating the contribution of distinct networks of brain regions to the main cognitive stages of the task (auditory perception, mental imagery and behavioural response), with good agreement across methods. Whereas ICA worked optimally on the original time series, averaging with respect to the task onset (and thus introducing some a priori information on the stimulation protocol) was found to be indispensable in the case of FCM. On averaged time series, FCM led to a richer decomposition of the spatio-temporal patterns of activation and allowed a finer separation of the neurocognitive processes subserving the mental imagery task. This study confirms the efficacy of the two examined methods in the data-driven estimation of hemodynamic responses in time-resolved fMRI studies and provides empirical guidelines to their use.     

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.     

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).