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Cerebrovascular reactivity (CVR), an important indicator of cerebrovascular health, is commonly studied with the Blood Oxygenation Level Dependent functional MRI (BOLD-fMRI) response to a vasoactive stimulus. Theoretical and empirical evidence suggests that baseline cerebral blood flow (CBF) modulates BOLD signal amplitude and may influence BOLD-CVR estimates. We address how acquisition and modeling choices affect the relationship between baseline cerebral blood flow (bCBF) and BOLD-CVR: whether BOLD-CVR is modeled with the inclusion of a breathing task, and whether BOLD-CVR amplitudes are optimized for hemodynamic lag effects. We assessed between-subject correlations of average GM values and within-subject spatial correlations across cortical regions. Our results suggest that a breathing task addition to a resting-state acquisition, alongside lag-optimization within BOLD-CVR modeling, can improve BOLD-CVR correlations with bCBF, both between- and within-subjects, likely because these CVR estimates are more physiologically accurate. We report positive correlations between bCBF and BOLD-CVR, both between- and within-subjects. The physiological explanation of this positive correlation is unclear; research with larger samples and tightly controlled vasoactive stimuli is needed. Insights into what drives variability in BOLD-CVR measurements and related measurements of cerebrovascular function are particularly relevant when interpreting results in populations with altered vascular and/or metabolic baselines or impaired cerebrovascular reserve. [ABSTRACT FROM AUTHOR]

Abstract The ultimate goal of calibrated fMRI is the quantitative imaging of oxygen metabolism (CMRO 2), and this has been the focus of numerous methods and approaches. However, one underappreciated aspect of this quest is that in the drive to measure CMRO 2 , many other physiological parameters of interest are often acquired along the way. This can significantly increase the value of the dataset, providing greater information that is clinically relevant, or detail that can disambiguate the cause of signal variations. This can also be somewhat of a double-edged sword: calibrated fMRI experiments combine multiple parameters into a physiological model that requires multiple steps, thereby providing more opportunity for error propagation and increasing the noise and error of the final derived values. As with all measurements, there is a trade-off between imaging time, spatial resolution, coverage, and accuracy. In this review, we provide a brief overview of the benefits and pitfalls of extracting multiparametric measurements of cerebral physiology through calibrated fMRI experiments. Highlights • Calibrated fMRI experiments produce multiple physiological parameter maps. • Combining multiparametric physiological data provides useful clinical information. • Image acquisition schemes and model assumptions must be carefully considered. [ABSTRACT FROM AUTHOR]

Abstract: Negative BOLD signals that are synchronous with resting state fluctuations have been observed in large vessels in the cortical sulci and surrounding the ventricles. In this study, we investigated the origin of these negative BOLD signals by applying a Cued Deep Breathing (CDB) task to create transient hypocapnia and a resultant global fMRI signal decrease. We hypothesized that a global stimulus would amplify the effect in large vessels and that using a global negative (vasoconstrictive) stimulus would test whether these voxels exhibit either inherently negative or simply anti-correlated BOLD responses. Significantly anti-correlated, but positive, BOLD signal changes during respiratory challenges were identified in voxels primarily located near edges of brain spaces containing CSF. These positive BOLD responses occurred earlier than the negative CDB response across most of gray matter voxels. These findings confirm earlier suggestions that in some brain regions, local, fractional changes in CSF volume may overwhelm BOLD-related signal changes, leading to signal anti-correlation. We show that regions with CDB anti-correlated signals coincide with most, but not all, of the regions with negative BOLD signal changes observed during a visual and motor stimulus task. Thus, the addition of a physiological challenge to fMRI experiments can help identify which negative BOLD signals are passive physiological anti-correlations and which may have a putative neuronal origin. [Copyright &y& Elsevier]

Abstract: Differing noise variance across study populations has been shown to cause artifactual group differences in functional connectivity measures. In this study, we investigate the use of short echo time functional MRI data to correct for these noise sources in blood oxygenation level dependent (BOLD)-weighted time series. A dual‐echo sequence was used to simultaneously acquire data at both a short (TE=3.3ms) and a BOLD-weighted (TE=35ms) echo time. This approach is effectively “free,” using dead-time in the pulse sequence to collect an additional echo without affecting overall scan time or temporal resolution. The proposed correction method uses voxelwise regression of the short TE data from the BOLD-weighted data to remove noise variance. In addition to a typical resting state scan, non-compliant behavior associated with patient groups was simulated via increased head motion or physiological fluctuations in 10 subjects. Short TE data showed significant correlations with the traditional motion-related and physiological noise regressors used in current connectivity analyses. Following traditional preprocessing, the extent of significant additional variance explained by the short TE data regressors was significantly correlated with the average head motion across the scan in the resting data (r 2 =0.93, p <0.0001). The reduction in data variance following the inclusion of short TE regressors was also correlated with scan head motion (r 2 =0.48, p =0.027). Task-related data were used to demonstrate the effects of the short TE correction on BOLD activation time series with known temporal structure; the size and strength of the activation were significantly decreased, but it is not clear whether this reflects BOLD contamination in the short TE data or correlated changes in blood volume. Finally, functional connectivity maps of the default mode network were constructed using a seed correlation approach. The effects of short TE correction and low-pass filtering on the resulting correlations maps were compared. Results suggest that short TE correction more accurately differentiates artifactual correlations from the correlations of interest in conditions of amplified noise. [Copyright &y& Elsevier]

Abstract: We offer a new method for characterizing the magnitude and dynamics of the vascular response to changes in arterial gas tensions using non-invasive blood oxygenation level-dependent functional magnetic resonance imaging (BOLD fMRI) and paradigms appropriate for clinical settings. A novel respiratory task, “Cued Deep Breathing” (CDB), consisting of two consecutive cycles of cued breaths, has been developed to cause transient hypocapnia, and consequently a strong, short-lived BOLD signal decrease. Data from CDB hypocapnia paradigms and traditional breath-holding hypercapnia paradigms were analyzed on a voxel-wise basis to map regional heterogeneity in magnitude and timing parameters. The tasks caused comparable absolute BOLD percent signal changes (∼0.5–3.0% in gray matter) and both datasets suggested consistent regional heterogeneity in the response timing: parts of the basal ganglia, particularly the putamen, and bilateral areas of medial cortex reached their maximum signal change several seconds earlier than remaining cortical gray matter voxels. This phenomenon and a slightly delayed response in posterior cortical regions were present in group-maps of ten healthy subjects. An auxiliary experiment in different subjects measured end-tidal CO2 changes associated with the new CDB task and quantitatively compared the resulting reactivity maps with those acquired using a traditional hypercapnia challenge of 4% CO2 gas inspiration. The CDB task caused average end-tidal CO2 decreases between 6.0±1.1 and 10.5±2.6 mm Hg, with levels returning to baseline after approximately three breaths, giving evidence that the task indeed causes transient mild hypocapnia. Similarity between resulting reactivity maps suggest CDB offers an alternative method for mapping cerebrovascular reactivity. [Copyright &y& Elsevier]

We present the first evidence for vascular regulation driving fMRI signals in specific functional brain networks. Using concurrent neuronal and vascular stimuli, we collected 30 BOLD fMRI datasets in 10 healthy individuals: a working memory task, flashing checkerboard stimulus, and CO 2 inhalation challenge were delivered in concurrent but orthogonal paradigms. The resulting imaging data were averaged together and decomposed using independent component analysis, and three "neuronal networks" were identified as demonstrating maximum temporal correlation with the neuronal stimulus paradigms: Default Mode Network, Task Positive Network, and Visual Network. For each of these, we observed a second network component with high spatial overlap. Using dual regression in the original 30 datasets, we extracted the time-series associated with these network pairs and calculated the percent of variance explained by the neuronal or vascular stimuli using a normalized R2 parameter. In each pairing, one network was dominated by the appropriate neuronal stimulus, and the other was dominated by the vascular stimulus as represented by the end-tidal CO 2 time-series recorded in each scan. We acquired a second dataset in 8 of the original participants, where no CO 2 challenge was delivered and CO 2 levels fluctuated naturally with breathing variations. Although splitting of functional networks was not robust in these data, performing dual regression with the network maps from the original analysis in this new dataset successfully replicated our observations. Thus, in addition to responding to localized metabolic changes, the brain's vasculature may be regulated in a coordinated manner that mimics (and potentially supports) specific functional brain networks. Multi-modal imaging and advances in fMRI acquisition and analysis could facilitate further study of the dual nature of functional brain networks. It will be critical to understand network-specific vascular function, and the behavior of a coupled vascular-neural network, in future studies of brain pathology. • Using neural and vascular stimuli we find pairs of spatially similar brain networks. • One network timeseries reflects a neural stimulus, the other a vascular stimulus. • The brain's vasculature may be regulated to support specific functional networks. • Understanding network-specific vascular function is critical to interpreting fMRI. [ABSTRACT FROM AUTHOR]