Imaging brain function with simultaneous BOLD and viscoelasticity contrast: fMRI/fMRE

Activation volume vs BOLD signal change as measures of fMRI activation – Its impact on GABA – fMRI activation correlation

Functional magnetic resonance imaging (fMRI) is a unique window to the brain, enabling scientists to follow changes in brain activity in response to hormones, ageing, environment, drugs of abuse and other stimuli. There are two features that make fMRI unique when compared with other imaging modalities used in behavioural neuroscience. First, it can be entirely noninvasive: each animal can serve as its own control over the natural course of its life, vital for following neuroadaptation and other developmental processes critical to understanding behaviour. Second, fMRI has the spatial and temporal resolution to observe patterns of neuronal activity across the entire brain in less than a minute. Although fMRI does not have the cellular spatial resolution of immunostaining, nor the millisecond temporal resolution of electrophysiology, synchronised changes in neuronal activity across multiple brain areas seen with functional MRI can be viewed as functional neuroanatomical circuits coordinating the thoughts, memories and emotions for particular behaviours. Thus, fMRI affords a systems approach to the study of the brain, complementing and building from other neurobiological techniques to understand how behaviour is organised across multiple brain regions. In this review, we present a general background to fMRI and the different imaging modalities that can be used in fMRI studies. Included are examples of the application of fMRI in behavioural neuroscience research, along with discussion of the advantages and disadvantages of this technology.

In this study, the extravascular (EV) contribution to blood oxygenation level-dependent (BOLD) signal changes was evaluated, based on a numerical analysis of the nondimensional Bloch-Torrey equation for a vascular network model of randomly oriented paramagnetic vessels. From a statistical point of view, the susceptibility-induced EV BOLD signal changes for both gradient- and spin-echoes are shown to be proportional to cerebral blood volume (CBV). These changes can be expressed by a function of two nondimensional parameters: one represents the characteristic phase change of the signal induced by the deoxyhemoglobin-containing vessels, and the other represents a diffusion effect relative to the vessel radius. The numerical results showed excellent agreement with the analytical solutions obtained previously for the regimes of small and large diffusion effects. Based on the numerical results for gradient- and spin-echoes, it is possible to show the dependence of the EV BOLD contribution on the echo time, the static magnetic field strength, and the stimulation-induced CBV change. This dependence can be demonstrated for vessels of small, intermediate, and large radii, which correspond respectively to the slow, intermediate, and fast diffusion regimes. A more realistic functional MRI (fMRI) simulation which includes an intravascular (IV) contribution is presented, with emphasis on the field strength dependence of the BOLD signal changes.

The most widely-used functional magnetic resonance imaging (fMRI) technique is based on the blood oxygenation level dependent (BOLD) effect, which requires at least partial uncoupling between cerebral blood flow (CBF) and oxygen consumption changes during increased mental activity. To compare BOLD and CBF effects during tasking, BOLD and flow-sensitive alternating inversion recovery (FAIR) images were acquired during visual stimulation with red goggles at a frequency of 8 Hz in an interleaved fashion. With the FAIR technique, absolute and relative CBF changes were determined. Relative oxygen consumption changes can be estimated using the BOLD and relative CBF changes. In gray matter areas in the visual cortex, absolute and relative CBF changes in humans during photic stimulation were 31 +/- 11 SD ml/100 g tissue/min and 43 +/- 16 SD % (n = 12), respectively, while the relative oxygen consumption change was close to zero. These findings agree extremely well with previous results using positron emission tomography. The BOLD signal change is not linearly correlated with the relative CBF increase across subjects and negatively correlates with the oxygen consumption change. Caution should be exercised when interpreting the BOLD percent change as a quantitative index of the CBF change, especially in inter-subject comparisons.

In simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), increased neuronal activity from epileptiform spikes commonly elicits positive blood oxygenation level-dependent (BOLD) responses. Negative responses are also occasionally seen and have not been explained. Recent studies describe BOLD signal changes before focal EEG spikes. We aimed to systematically study if the undershoot of a preceding positive response might explain the negative BOLD seen in the focus. Eighty-two patients with focal epilepsy who underwent EEG-fMRI at 3T were retrospectively studied. Studies with a focal negative BOLD response in the region of the spike field were reanalyzed using models with hemodynamic response functions (HRFs) peaking from -9 to +9 s around the spike. Eight patients met the inclusion criteria, showing negative BOLD responses in the spike field on standard analysis. None had positive BOLD responses immediately adjacent to the areas of deactivation. Regions of deactivation were found to have congruent preceding positive responses in two cases. These early activations were seen at the combined maps of -5 to -9 s. This study indicates that in a small proportion of patients with focal epilepsy in whom the standard analysis reveals focal negative responses, an earlier positive BOLD response is probably the cause. The origin of negative BOLD signal changes in the focus as a result of an epileptic event remains, however, unexplained in most of the patients in whom it occurs.

Comment on “The physiology of developmental changes in BOLD functional imaging signals” by Harris, Reynell, and Attwell

Cerebrovascular reactivity measured with arterial spin labeling and blood oxygen level dependent techniques

Introduction: Fetal brain growth is altered in congenital heart disease (CHD). The role of disturbed placental and fetal blood flow/oxygenation remains poorly understood. We compared the effect of maternal hyperoxia on cerebral and placental oxygenation in CHD vs control fetuses using blood oxygenation level dependent (BOLD) functional MRI (fMRI). Methods: We studied 85 pregnant women (51 healthy /34 CHD fetuses) at 22-39 weeks gestational age (GA), using MRI and Doppler. After 2min baseline recording at normoxia (NO), we made BOLD fMRI measurements in 4 phases, (1) early hyperoxia (HO; 100% O2) for 2min (2) late HO (2min), (3) early return NO (1.75min), (4) late return NO (1.75min). We measured % BOLD signal changes in fetal brain and placenta and correlated these with umbilical artery (UA) pulsatility index (PI) obtained at baseline. Results: Mean GA of CHD vs control fetuses was 32 4/7 and 32 2/7 (p=0.77). 41.2% had 1-ventricle (1V; all HLHS) vs 2-ventricle (2V) physiology. In controls, brain BOLD signal increased in phase 1 HO and remained elevated through phase 4. In CHD fetuses, the BOLD signal increased in phase 1 and continued to rise through phase 4. Differences in brain BOLD elevation in CHD vs controls (3.1% vs 0.9%, p=0.04) was significant in phase 4 (Fig. 1). Brain BOLD differed between 1V (3.4%, p=0.04) and 2V (0.9%, p=0.15) in phases 3 & 4. Placental BOLD signal increased during HO in control (4.4%, p<0.001) and CHD fetuses (6.4%, p<0.001). UA PI in CHD fetuses was higher than controls (1.11 vs 1.03, p=0.03). UA PI correlated with placental BOLD during HO in healthy and CHD fetuses (p<0.05). Conclusions: In this first report of placental and fetal brain responses to maternal HO, we show a significantly increased brain BOLD response in CHD fetuses, specifically 1V. These data suggest that maternal HO improves brain oxygenation in CHD fetuses in the short-term. Studies evaluating the prolonged effects of HO are needed to determine the role of HO management in select CHD fetuses.

Neuroimaging activation maps typically color voxels to indicate whether the blood oxygen level-dependent (BOLD) signals measured among two or more experimental conditions differ significantly at that location. This data presentation, however, omits information critical for interpretation of experimental results. First, no information is represented about trends at voxels that do not pass the statistical test. Second, no information is given about the range of probable effect sizes at voxels that do pass the statistical test. This leads to a fundamental error in interpreting activation maps by naïve viewers, where it is assumed that colored, “active” voxels are reliably different from uncolored “inactive” voxels. In other domains, confidence intervals have been added to data graphics to reduce such errors. Here, we first document the prevalence of the fundamental error of interpretation, and then present a method for solving it by depicting confidence intervals in fMRI activation maps. Presenting images where the bounds of confidence intervals at each voxel are coded as color allows readers to visually test for differences between “active” and “inactive” voxels, and permits for more proper interpretation of neuroimaging data. Our specific graphical methods are intended as initial proposals to spur broader discussion of how to present confidence intervals for fMRI data.

Electrocorticography (ECoG) is typically employed to accurately identify the seizure focus as well as the location of brain functions to be spared during surgical resection in participants with drug-resistant epilepsy. Increasingly, this technique has become a powerful tool to map cognitive functions onto brain regions. Cortical mapping is more commonly investigated with functional MRI (fMRI), which measures blood-oxygen level dependent (BOLD) changes induced by neuronal activity. The multimodal integration between typical 3T fMRI activity maps and ECoG measurements can provide unique insight into the spatiotemporal aspects of cognition. However, the optimal integration of fMRI and ECoG requires fundamental insight into the spatial smoothness of the BOLD signal under each electrode.Here we use ECoG as ground truth for the extent of activity, as each electrode is thought to record from the cortical tissue directly underneath the contact, to estimate the spatial smoothness of the associated BOLD response at 3T fMRI. We compared the high-frequency broadband (HFB) activity recorded with ECoG while participants performed a motor task. Activity maps were obtained with fMRI at 3T for the same task in the same participant prior to surgery. We then correlated HFB power with the fMRI BOLD signal change in the area around each electrode. This latter measure was quantified by applying a 3D Gaussian kernel of varying width (sigma between 1 mm and 20 mm) to the fMRI maps including only gray-matter.We found that the correlation between HFB and BOLD activity increased sharply up to the point when the kernel width was set to 4 mm, which we defined as the kernel width of maximal spatial specificity. After this point, as the kernel width increased, the highest level of explained variance was reached at a kernel width of 9 mm for most participants. Intriguingly, maximal specificity was also limited to 4 mm for low-frequency bands, such as alpha and beta, but the kernel width with the highest explained variance was less spatially limited than the HFB.In summary, spatial specificity is limited to a kernel width of 4 mm but explained variance keeps on increasing as you average over more and more voxels containing the relatively noisy BOLD signal. Future multimodal studies should choose the kernel width based on their research goal. For maximal spatial specificity, ECoG electrodes are best compared to 3T fMRI with a kernel width of 4 mm. When optimizing the correlation between modalities, highest explained variance can be obtained at larger kernel widths of 9 mm, at the expense of spatial specificity. Finally, we release the complete pipeline so that researchers can estimate the most appropriate kernel width from their multimodal datasets.

Resting-state brain activity has been widely investigated using blood oxygenation level dependent (BOLD) contrast techniques. However, BOLD signal changes reflect a combination of the effects of cerebral blood flow (CBF), cerebral blood volume (CBV), as well as the cerebral metabolic rate of oxygen (CMRO2). In this study, resting-state brain activation was detected and compared using the following techniques: (a) BOLD, using a gradient-echo echo planar imaging (GE-EPI) sequence; (b) CBV-weighted signal, acquired using gradient and spin echo (GRASE) based vascular space occupancy (VASO); and (c) CBF, using pseudo-continuous arterial spin labeling (pCASL). Reliable brain networks were detected using VASO and ASL, including sensorimotor, auditory, primary visual, higher visual, default mode, salience and left/right executive control networks. Differences between the resting-state activation detected with ASL, VASO and BOLD could potentially be due to the different temporal signal-to-noise ratio (tSNR) and the short post-labeling delay (PLD) in ASL, along with differences in the spin-echo readout of VASO. It is also possible that the dynamics of spontaneous fluctuations in BOLD, CBV and CBF could differ due to biological reasons, according to their location within the brain.

Functional MRI (fMRI) generally employs gradient-echo echo-planar imaging (GE-EPI) to measure blood oxygen level-dependent (BOLD) signal changes that result from changes in tissue relaxation time T(*) (2) between activation and rest. Since T(*) (2) strongly varies across the brain and BOLD contrast is maximal only where the echo time (TE) equals the local T(*) (2), imaging at a single TE is a compromise in terms of overall sensitivity. Furthermore, the long echo train makes EPI very sensitive to main field inhomogeneities, causing strong image distortion. A method is presented that uses accelerated parallel imaging to reduce image artifacts and acquire images at multiple TEs following a single excitation, with no need to increase TR. Sensitivity gains from the broadened T(*) (2) coverage are optimized by pixelwise weighted echo summation based on local T(*) (2) or contrast-to-noise ratio (CNR) measurements. The method was evaluated using an approach that allows differential BOLD CNR to be calculated without stimulation, as well as with a Stroop experiment. Results obtained at 3 T showed that BOLD sensitivity improved by 11% or more in all brain regions, with larger gains in areas typically affected by strong susceptibility artifacts. The use of parallel imaging markedly reduces image distortion, and hence the method should find widespread application in functional brain imaging.

Blood oxygenation-level dependent (BOLD) MRI has gained particular attention in functional brain imaging studies, where it can be used to localize areas of brain activation with high temporal resolution. To a higher degree than in the brain, skeletal muscles show extensive but transient alterations of blood flow between resting and activation state. Thus, there has been interest in the application of the BOLD effect in studying the physiology of skeletal muscles (healthy and diseased) and its possible application to clinical practice. This review outlines the potential of skeletal muscle BOLD MRI as a diagnostic tool for the evaluation of physiological and pathological alterations in the peripheral limb perfusion, such as in peripheral arterial occlusive disease. Moreover, current knowledge is summarized regarding the complex mechanisms eliciting BOLD effect in skeletal muscle. We describe technical fundaments of the procedure that should be taken into account when performing skeletal muscle BOLD MRI, including the most often applied paradigms to provoke BOLD signal changes and key parameters of the resulting time courses. Possible confounding effects in muscle BOLD imaging studies, like age, muscle fiber type, training state, and drug effects are also reviewed in detail.

Dynamic metabolic changes were investigated by functional magnetic resonance spectroscopy (fMRS) during sustained stimulation of human primary visual cortex. Two established paradigms, consisting of either a full-field or a small-circle flickering checkerboard, were employed to generate wide-spread areas of positive or negative blood oxygenation level-dependent (BOLD) responses, respectively. Compared to baseline, the glutamate concentration increased by 5.3% (p = 0.007) during activation and decreased by −3.8% (p = 0.017) during deactivation. These changes were positively correlated with the amplitude of the BOLD response (R = 0.60, p = 0.002) and probably reflect changes of tricarboxylic acid cycle activity. During deactivation, the glucose concentration decreased by −7.9% (p = 0.025) presumably suggesting increased consumption or reduced glucose supply. Other findings included an increased concentration of glutathione (4.2%, p = 0.023) during deactivation and a negative correlation of glutathione and BOLD signal changes (R = −0.49, p = 0.012) as well as positive correlations of aspartate (R = 0.44, p = 0.035) and N-acetylaspartylglutamate (R = 0.42, p = 0.035) baseline concentrations with the BOLD response. It remains to be shown in future work if the observed effects on glutamate and glucose levels deviate from the assumption of a direct link between glucose utilization and regulation of blood flow or support previous suggestions that the hemodynamic response is mainly driven by feedforward release of vasoactive messengers.

Electroencephalography-functional magnetic resonance imaging (EEG-fMRI) coregistration has recently revealed that several brain structures are involved in generalized spike and wave discharges (GSWDs) in idiopathic generalized epilepsies (IGEs). In particular, deactivations and activations have been observed within the so-called brain default mode network (DMN) and thalamus, respectively. In the present study we analyzed the dynamic time course of blood oxygen level-dependent (BOLD) changes preceding and following 3 Hz GSWDs in a group of adolescent and adult patients with IGE who presented with absence seizures (AS). Our aim was to evaluate cortical BOLD changes before, during, and after GSWD onset. Twenty-one patients with IGE underwent EEG-fMRI coregistration. EEG-related analyses were run both at the single-subject and at group level (random effect). The time-course analysis was conducted for 3 s time windows before, during, and after GSWDs, and they were included until no further BOLD signal changes were observed. Fifteen patients (nine female, mean age 28 years) had GSWDs during EEG-fMRI coregistration (262 total events, mean duration 4 s). Time-course group analysis showed BOLD increments starting approximately 10 s before GSWD onset located in frontal and parietal cortical areas, and especially in the precuneus-posterior cingulate region. At GSWD onset, BOLD increments were located in thalamus, cerebellum, and anterior cingulate gyrus, whereas BOLD decrements were observed in the DMN regions persisting until 9 s after onset. Hemodynamic changes (BOLD increments) occurred in specific cortical areas, namely the precuneus/posterior cingulate, lateral parietal, and frontal cortices, several seconds before EEG onset of GSWD. A dysfunction of these brain regions, some of which belongs to the DMN, may be crucial in generating GSWDs in patients with IGE.