Blood Oxygenation Level-dependent fMRI Research Articles

Size of the spatial correlation between ECoG and fMRI activity

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.

The Significance of Echo Time in fMRI BOLD Contrast: A Clinical Study during Motor and Visual Activation Tasks at 1.5 T.

Blood Oxygen Level Dependent (BOLD) is a commonly-used MR imaging technique in studying brain function. The BOLD signal can be strongly affected by specific sequence parameters, especially in small field strengths. Previous small-scale studies have investigated the effect of TE on BOLD contrast. This study evaluates the dependence of fMRI results on echo time (TE) during concurrent activation of the visual and motor cortex at 1.5 T in a larger sample of 21 healthy volunteers. The experiment was repeated using two different TE values (50 and 70 ms) in counterbalanced order. Furthermore, T2* measurements of the gray matter were performed. Results indicated that both peak beta value and number of voxels were significantly higher using TE = 70 than TE = 50 ms in primary motor, primary somatosensory and supplementary motor cortices (p < 0.007). In addition, the amplitude of activation in visual cortices and the dorsal premotor area was also higher using TE = 70 ms (p < 0.001). Gray matter T2* of the corresponding areas did not vary significantly. In conclusion, the optimal TE value (among the two studied) for visual and motor activity is 70 ms affecting both the amplitude and extent of regional hemodynamic activation.

Identification of Autism Subtypes Based on Wavelet Coherence of BOLD FMRI Signals Using Convolutional Neural Network.

The functional connectivity (FC) patterns of resting-state functional magnetic resonance imaging (rs-fMRI) play an essential role in the development of autism spectrum disorders (ASD) classification models. There are available methods in literature that have used FC patterns as inputs for binary classification models, but the results barely reach an accuracy of 80%. Additionally, the generalizability across multiple sites of the models has not been investigated. Due to the lack of ASD subtypes identification model, the multi-class classification is proposed in the present study. This study aims to develop automated identification of autism spectrum disorder (ASD) subtypes using convolutional neural networks (CNN) using dynamic FC as its inputs. The rs-fMRI dataset used in this study consists of 144 individuals from 8 independent sites, labeled based on three ASD subtypes, namely autistic disorder (ASD), Asperger’s disorder (APD), and pervasive developmental disorder not otherwise specified (PDD-NOS). The blood-oxygen-level-dependent (BOLD) signals from 116 brain nodes of automated anatomical labeling (AAL) atlas are used, where the top-ranked node is determined based on one-way analysis of variance (ANOVA) of the power spectral density (PSD) values. Based on the statistical analysis of the PSD values of 3-level ASD and normal control (NC), putamen_R is obtained as the top-ranked node and used for the wavelet coherence computation. With good resolution in time and frequency domain, scalograms of wavelet coherence between the top-ranked node and the rest of the nodes are used as dynamic FC feature input to the convolutional neural networks (CNN). The dynamic FC patterns of wavelet coherence scalogram represent phase synchronization between the pairs of BOLD signals. Classification algorithms are developed using CNN and the wavelet coherence scalograms for binary and multi-class identification were trained and tested using cross-validation and leave-one-out techniques. Results of binary classification (ASD vs. NC) and multi-class classification (ASD vs. APD vs. PDD-NOS vs. NC) yielded, respectively, 89.8% accuracy and 82.1% macro-average accuracy, respectively. Findings from this study have illustrated the good potential of wavelet coherence technique in representing dynamic FC between brain nodes and open possibilities for its application in computer aided diagnosis of other neuropsychiatric disorders, such as depression or schizophrenia.

Autism Spectrum Disorder Detection Based on Wavelet Transform of BOLD fMRI Signals Using Pre-trained Convolution Neural Network

Autism spectrum disorder (ASD) is a mental disorder and the main problem in ASD treatment has no definite cure, and one possible option is to control its symptoms. Conventional ASD assessment using questionnaires may not be accurate and required evaluation of trained experts. Several attempts to use resting-state functional magnetic resonance imaging (fMRI) as an assisting tool combined with a classifier have been reported for ASD detection. Still, researchers barely reach an accuracy of 70% for replicated models with independent datasets. Most of the ASD studies have used functional connectivity and structural measurements and ignored the temporal dynamics features of fMRI data analysis. This study aims to present several convolutional neural networks as tools for ASD detection based on temporal dynamic features classification and improve the ASD prediction results. The sample size is 82 subjects (41 ASD and 41 normal cases) collected from three different sites of Autism Brain Imaging Data Exchange (ABIDE). The default mode network (DMN) regions are selected for blood-oxygen-level-dependent (BOLD) signals extraction. The extracted BOLD signals' time-frequency components are converted to scalogram images and used as input for pre-trained convolutional neural networks for feature extraction such as GoogLenet, DenseNet201, ResNet18, and ResNet101. The extracted features are trained using two classifiers: support vector machine (SVM) and K-nearest neighbours (KNN). The best prediction results are 85.9% accuracy achieved by extracted the features from DenseNet201 network and classified these features by KNN classifier. Comparison with previous studies, has indicated the good potential of the proposed model for diagnosis of ASD cases. From another perspective, the presented method can be applied for analysis of rs-fMRI data on other type of brain disorders.

Improvement of sensitivity and specificity for laminar BOLD fMRI with double spin-echo EPI in humans at 7 T

Mapping mesoscopic cortical functional units such as columns or laminae is increasingly pursued by ultra-high field (UHF) functional magnetic resonance imaging (fMRI). The most popular approach for high-resolution fMRI is currently gradient-echo (GE) blood oxygenation level-dependent (BOLD) fMRI. However, its spatial accuracy is reduced due to its sensitivity to draining vessels, including pial veins, whereas spin-echo (SE) BOLD signal is expected to have higher spatial accuracy, albeit with lower sensitivity than the GE-BOLD signal. Here, we introduce a new double spin-echo (dSE) echo-planar imaging (EPI) method to improve the sensitivity of SE-BOLD contrast by averaging two spin-echoes using three radiofrequency pulses. Human fMRI experiments were performed with slices perpendicular to the central sulcus between motor and sensory cortices at 7 T during fist-clenching with touching. First, we evaluated the feasibility of single-shot dSE-EPI for BOLD fMRI with 1.5 mm isotropic resolution and found that dSE-BOLD fMRI has higher signal-to-noise ratio (SNR), temporal SNR (tSNR), and higher functional sensitivity than conventional SE-BOLD fMRI. Second, to investigate the laminar specificity of dSE-BOLD fMRI, we implemented a multi-shot approach to achieve 0.8-mm isotropic resolution with sliding-window reconstruction. Unlike GE-BOLD fMRI, the cortical profile of dSE-BOLD fMRI peaked at ~ 1.0 mm from the surface of the primary motor and sensory cortices, demonstrating an improvement of laminar specificity in humans over GE-BOLD fMRI. The proposed multi-shot dSE-EPI method is viable for high spatial resolution UHF-fMRI studies in the pursuit of resolving mesoscopic functional units.

Different cerebral functional segregation in Sjogren's syndrome with or without systemic lupus erythematosus revealed by amplitude of low-frequency fluctuation.

Sjögren's syndrome (SjS) associated with systemic lupus erythematosus (SjS-SLE) was considered a standalone but often-overlooked entity. To assess altered spontaneous brain activity in SjS-SLE and SjS using amplitude of low-frequency fluctuation (ALFF). Sixteen patients with SjS-SLE, 17 patients with SjS, and 17 matched controls underwent neuropsychological tests and subsequent resting-state functional magnetic resonance imaging (fMRI) examinations. The ALFF value was calculated based on blood oxygen level dependent (BOLD) fMRI. Statistical parametric mapping was utilized to analyze between-group differences and multiple comparison was corrected with Analysis of Functional NeuroImages 3dClustSim. Then, the ALFFs of brain regions with significant differences among the three groups were correlated to corresponding clinical and neuropsychological variables by Pearson correlation. ALFF differences in the bilateral precuneus/posterior cingulate cortex (PCC), right parahippocampal gyrus/caudate/insula, and left insula were found among the three groups. Both SjS-SLE and SjS displayed decreased ALFF in the right parahippocampal gyrus, right insula, and left insula than HC. Moreover, SjS-SLE showed wider decreased ALFF in the bilateral precuneus and right caudate, while the SjS group exhibited increased ALFF in the bilateral PCC. Additionally, patients with SjS-SLE exhibited lower ALFF values in the bilateral PCC and precuneus than SjS. Moreover, ALFF values in the right parahippocampal gyrus and PCC were negatively correlated to fatigue score and disease duration, respectively, in SjS-SLE. SjS-SLE and SjS exhibited common and different alteration of cerebral functional segregation revealed by AlFF analysis. This result appeared to indicate that SjS-SLE might be different from SjS with a neuroimaging standpoint.

Application of an integrated radio-frequency/shim coil technology for signal recovery in fMRI.

Gradient-echo echo-planar imaging (EPI), which is typically used for blood oxygenation level-dependent (BOLD) functional MRI (fMRI), suffers from distortions and signal loss caused by localized B0 inhomogeneities. Such artifacts cannot be effectively corrected for with the low-order spherical harmonic (SH) shim coils available on most scanners. The integrated parallel reception, excitation, and shimming (iPRES) coil technology allows radiofrequency (RF) and direct currents to flow on each coil element, enabling imaging and localized B0 shimming with one coil array. iPRES was previously used to correct for distortions in spin-echo EPI and is further developed here to also recover signal loss in gradient-echo EPI. The cost function in the shim optimization, which typically uses a single term representing the B0 inhomogeneity, was modified to include a second term representing the signal loss, with an adjustable weight to optimize the trade-off between distortion correction and signal recovery. Simulations and experiments were performed to investigate the shimming performance. Slice-optimized shimming with iPRES and the proposed cost function substantially reduced the signal loss in the inferior frontal and temporal brain regions compared to shimming with iPRES and the original cost function or 2nd -order SH shimming with either cost function. In breath-holding fMRI experiments, the ΔB0 and signal loss root-mean-square errors decreased by -34.3% and -56.2%, whereas the EPI signal intensity and number of activated voxels increased by 60.3% and 174.0% in the inferior frontal brain region. iPRES can recover signal loss in gradient-echo EPI, which is expected to improve BOLD fMRI studies in brain regions suffering from signal loss.

BOLD asynchrony elucidates tumor burden in IDH-mutated gliomas.

Gliomas comprise the most common type of primary brain tumor, are highly invasive, and often fatal. IDH-mutated gliomas are particularly challenging to image and there is currently no clinically accepted method for identifying the extent of tumor burden in these neoplasms. This uncertainty poses a challenge to clinicians who must balance the need to treat the tumor while sparing healthy brain from iatrogenic damage. The purpose of this study was to investigate the feasibility of using resting-state blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) to detect glioma-related asynchrony in vascular dynamics for distinguishing tumor from healthy brain. Twenty-four stereotactically localized biopsies were obtained during open surgical resection from ten treatment-naïve patients with IDH-mutated gliomas who received standard-of-care preoperative imaging as well as echo-planar resting-state BOLD fMRI. Signal intensity for BOLD asynchrony and standard-of-care imaging was compared to cell counts of total cellularity (H&E), tumor density (IDH1 & Sox2), cellular proliferation (Ki67), and neuronal density (NeuN), for each corresponding sample. BOLD asynchrony was directly related to total cellularity (H&E, P = 4 × 10-5), tumor density (IDH1, P = 4 × 10-5; Sox2, P = 3 × 10-5), cellular proliferation (Ki67, P = .002), and inversely related to neuronal density (NeuN, P = 1 × 10-4). Asynchrony in vascular dynamics, as measured by resting-state BOLD fMRI, correlates with tumor burden and provides a radiographic delineation of tumor boundaries in IDH-mutated gliomas.

Distinct Neurophysiological Correlates of the fMRI BOLD Signal in the Hippocampus and Neocortex.

Functional magnetic resonance imaging (fMRI) is among the foremost methods for mapping human brain function but provides only an indirect measure of underlying neural activity. Recent findings suggest that the neurophysiological correlates of the fMRI blood oxygenation level-dependent (BOLD) signal might be regionally specific. We examined the neurophysiological correlates of the fMRI BOLD signal in the hippocampus and neocortex, where differences in neural architecture might result in a different relationship between the respective signals. Fifteen human neurosurgical patients (10 female, 5 male) implanted with depth electrodes performed a verbal free recall task while electrophysiological activity was recorded simultaneously from hippocampal and neocortical sites. The same patients subsequently performed a similar version of the task during a later fMRI session. Subsequent memory effects (SMEs) were computed for both imaging modalities as patterns of encoding-related brain activity predictive of later free recall. Linear mixed-effects modeling revealed that the relationship between BOLD and gamma-band SMEs was moderated by the lobar location of the recording site. BOLD and high gamma (70-150 Hz) SMEs positively covaried across much of the neocortex. This relationship was reversed in the hippocampus, where a negative correlation between BOLD and high gamma SMEs was evident. We also observed a negative relationship between BOLD and low gamma (30-70 Hz) SMEs in the medial temporal lobe more broadly. These results suggest that the neurophysiological correlates of the BOLD signal in the hippocampus differ from those observed in the neocortex.SIGNIFICANCE STATEMENT The BOLD signal forms the basis of fMRI but provides only an indirect measure of neural activity. Task-related modulation of BOLD signals are typically equated with changes in gamma-band activity; however, relevant empirical evidence comes largely from the neocortex. We examined neurophysiological correlates of the BOLD signal in the hippocampus, where the differing neural architecture might result in a different relationship between the respective signals. We identified a positive relationship between encoding-related changes in BOLD and gamma-band activity in the frontal and parietal cortices. This effect was reversed in the hippocampus, where BOLD and gamma-band effects negatively covaried. These results suggest regional variability in the transfer function between neural activity and the BOLD signal in the hippocampus and neocortex.

Mapping Cerebrovascular Reactivity Impairment in Patients With Symptomatic Unilateral Carotid Artery Disease.

BackgroundComprehensive hemodynamic impairment mapping using blood oxygenation‐level dependent (BOLD) cerebrovascular reactivity (CVR) can be used to identify hemodynamically relevant symptomatic unilateral carotid artery disease.Methods and ResultsThis prospective cohort study was conducted between February 2015 and July 2020 at the Clinical Neuroscience Center of the University Hospital Zurich, Zurich, Switzerland. One hundred two patients with newly diagnosed symptomatic unilateral internal carotid artery (ICA) occlusion or with 70% to 99% ICA stenosis were included. An age‐matched healthy cohort of 12 subjects underwent an identical BOLD functional magnetic resonance imaging examination. Using BOLD functional magnetic resonance imaging with a standardized CO2 stimulus, CVR impairment was evaluated. Moreover, embolic versus hemodynamic ischemic patterns were evaluated on diffusion‐weighted imaging. Sixty‐seven patients had unilateral ICA occlusion and 35 patients unilateral 70% to 99% ICA stenosis. Patients with ICA occlusion exhibited lower whole‐brain and ipsilateral hemisphere mean BOLD‐CVR values as compared with healthy subjects (0.12±0.08 versus 0.19±0.04, P=0.004 and 0.09±0.09 versus 0.18±0.04, P<0.001) and ICA stenosis cohort (0.12±0.08 versus 0.16±0.05, P=0.01 and 0.09±0.09 versus 0.15±0.05, P=0.01); however, only 40 (58%) patients of the cohort showed significant BOLD‐CVR impairment. Conversely, there was no difference in mean BOLD‐CVR values between healthy patients and patients with ICA stenosis, although 5 (14%) patients with ICA stenosis showed a significant BOLD‐CVR impairment. No significant BOLD‐CVR difference was discernible between patients with hemodynamic ischemic infarcts versus those with embolic infarct distribution (0.11±0.08 versus 0.13±0.06, P=0.12).ConclusionsComprehensive BOLD‐CVR mapping allows for identification of hemodynamically relevant symptomatic unilateral carotid artery stenosis or occlusion.

Massively parallel functional photoacoustic computed tomography of the human brain.

Blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging of the human brain requires bulky equipment for the generation of magnetic fields. Photoacoustic computed tomography obviates the need for magnetic fields by using light and sound to measure deoxyhaemoglobin and oxyhaemoglobin concentrations to then quantify oxygen saturation and blood volumes. Yet, the available imaging speeds, fields of view (FOV), sensitivities and penetration depths have been insufficient for functional imaging of the human brain. Here, we show that massively parallel ultrasonic transducers arranged hemispherically around the human head can produce tomographic images of the brain with a 10-cm-diameter FOV and spatial and temporal resolutions of 350 µm and 2 s, respectively. In patients who had a hemicraniectomy, a comparison of functional photoacoustic computed tomography and 7 T BOLD functional magnetic resonance imaging showed a strong spatial correspondence in the same FOV and a high temporal correlation between BOLD signals and photoacoustic signals, with the latter enabling faster detection of functional activation. Our findings establish the use of photoacoustic computed tomography for human brain imaging.

Pictorial essay: How co-registered BOLD fMRI and DTI data can improve diffusion tensor tractography

Diffusion tensor tractography (DTT) and blood oxygen level dependent fMRI are tools frequently used in the preoperative evaluation of patients with brain tumors. A major limitation of DTT is difficulty in obtaining a relatively complete, useful representation of a white matter tract of interest due to challenges with artificial truncation of tracts. This pictorial essay will illustrate how coregistration of fMRI and DTI can be performed in clinical practice to obtain better, more complete tractograms of the pyramidal tract and arcuate fasciculus in patients with brain tumors.

Prefrontal Cortex Activation During Motor Sequence Learning Under Interleaved and Repetitive Practice: A Two-Channel Near-Infrared Spectroscopy Study.

Training under high interference conditions through interleaved practice (IP) results in performance suppression during training but enhances long-term performance relative to repetitive practice (RP) involving low interference. Previous neuroimaging work addressing this contextual interference effect of motor learning has relied heavily on the blood-oxygen-level-dependent (BOLD) response using functional magnetic resonance imaging (fMRI) methodology resulting in mixed reports of prefrontal cortex (PFC) recruitment under IP and RP conditions. We sought to clarify these equivocal findings by imaging bilateral PFC recruitment using functional near-infrared spectroscopy (fNIRS) while discrete key pressing sequences were trained under IP and RP schedules and subsequently tested following a 24-h delay. An advantage of fNIRS over the fMRI BOLD response is that the former measures oxygenated and deoxygenated hemoglobin changes independently allowing for assessment of cortical hemodynamics even when there is neurovascular decoupling. Despite slower sequence performance durations under IP, bilateral PFC oxygenated and deoxygenated hemoglobin values did not differ between practice conditions. During test, however, slower performance from those previously trained under RP coincided with hemispheric asymmetry in PFC recruitment. Specifically, following RP, test deoxygenated hemoglobin values were significantly lower in the right PFC. The present findings contrast with previous behavioral demonstrations of increased cognitive demand under IP to illustrate a more complex involvement of the PFC in the contextual interference effect. IP and RP incur similar levels of bilateral PFC recruitment, but the processes underlying the recruitment are dissimilar. PFC recruitment during IP supports action reconstruction and memory elaboration while RP relies on PFC recruitment to maintain task variation information in working memory from trial to trial. While PFC recruitment under RP serves to enhance immediate performance, it does not support long-term performance.

Asynchrony in Peritumoral Resting-State Blood Oxygen Level-Dependent fMRI Predicts Meningioma Grade and Invasion.

Meningioma grade is determined by histologic analysis, with detectable brain invasion resulting in a diagnosis of grade II or III tumor. However, tissue undersampling is a common problem, and invasive parts of the tumor can be missed, resulting in the incorrect assignment of a lower grade. Radiographic biomarkers may be able to improve the diagnosis of grade and identify targets for biopsy. Prior work in patients with gliomas has shown that the resting-state blood oxygen level-dependent fMRI signal within these tumors is not synchronous with normal brain. We hypothesized that blood oxygen level-dependent asynchrony, a functional marker of vascular dysregulation, could predict meningioma grade. We identified 25 patients with grade I and 11 patients with grade II or III meningiomas. Blood oxygen level-dependent time-series were extracted from the tumor and the radiographically normal control hemisphere and were included as predictors in a multiple linear regression to generate a blood oxygen level-dependent asynchrony map, in which negative values signify synchronous and positive values signify asynchronous activity relative to healthy brain. Masks of blood oxygen level-dependent asynchrony were created for each patient, and the fraction of the mask that extended beyond the contrast-enhancing tumor was computed. The spatial extent of blood oxygen level-dependent asynchrony was greater in high (grades II and III) than in low (I) grade tumors (P < 0.001) and could discriminate grade with high accuracy (area under the curve = 0.88). Blood oxygen level-dependent asynchrony radiographically discriminates meningioma grade and may provide targets for biopsy collection to aid in histologic diagnosis.

Prediction of response to Certolizumab-Pegol in rheumatoid arthritis (PreCePRA) by functional MRI of the brain – Study protocol for a randomized double-blind controlled study

BackgroundTumor necrosis factor inhibitors (TNFi) signify a major advance in the treatment of rheumatoid arthritis (RA). However, treatment success initially remains uncertain as approximately half of the patients do not respond adequately to TNFi. Thus, an unmet need exists to better predict therapeutic outcome of biologicals. ObjectivesWe investigated whether brain activity associated with arthritis measured by functional magnetic resonance imaging (fMRI) of the brain can serve as a predictor of response to TNFi in RA patients. MethodsPreCePRA is a multi-center, randomized, double-blind, placebo-controlled fMRI trial on patients with RA [1] [2]. Active RA patients failing csDMARDs therapy with a DAS28 > 3.2 and at least three tender and/or swollen joints underwent a brain BOLD (blood-oxygen-level dependent) fMRI scan upon joint compression at screening. Patients were then randomized into a 12-week double-blinded treatment phase with 200 mg Certolizumab Pegol (CZP) every two weeks (arm 1: fMRI BOLD signal activated volume > 2000 voxel, i.e. 2 cm3; arm 2: fMRI BOLD signal activated volume <2000 voxel) or placebo (arm 3). DAS28 low disease activity at 12 weeks was assigned as primary endpoint. A 12-week follow-up phase in which patients were switched from the placebo to the treatment arm followed the blinded phase. fMRI was carried out at screening as well as after 12 and 24 weeks of receiving CZP or placebo. ConclusionWe hypothesize that high-level central nervous representation of pain in patients with rheumatoid arthritis predicts response to the TNFi CZP which we further investigate in the PreCePRA trial.

Altered Temporal Dynamics of Brain Activity in Multiple-Frequency Bands in Non-Neuropsychiatric Systemic Lupus Erythematosus Patients with Inactive Disease.

PurposeIn this study, we seek to investigate dynamic changes of brain activity in non-neuropsychiatric systemic lupus erythematosus (non-NPSLE) patients with inactive disease.Patients and MethodsThirty-one non-NPSLE patients with inactive disease and 20 matched healthy controls underwent the blood oxygenation level-dependent fMRI examination. Dynamic regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuations (fALFF) were used to analyze the brain activity in typical band (0.01–0.08 Hz), slow-4 (0.027–0.073 Hz) and slow-5 (0.01–0.027 Hz). Pearson’s correlation analysis was performed to correlate dynamic regional homogeneity (dReHo) and dynamic fractional amplitude of low-frequency fluctuations (dfALFF) values for clusters of voxels where significant group differences were found with clinical variables in non-NPSLE patients with inactive disease.ResultsIn typical band, non-NPSLE patients showed increased dReHo in left middle occipital gyrus (MOG) compared to healthy controls. Meanwhile, patients showed decreased dfALFF in right superior frontal gyrus (SFG) and bilateral middle frontal gyrus (MFG) in typical band. In slow-4, increased dReHo in left MOG was found in non-NPSLE patients. In slow-5, non-NPSLE patients showed increased dReHo in left MOG, left calcarine fissure and surrounding cortex, right precentral gyrus (PreCG) and left postcentral gyrus (PoCG). Meanwhile, non-NPSLE patients showed decreased dfALFF in left SFG, right MFG, and right PreCG in slow-5. Moreover, the glucocorticoid dose showed significantly negative correlations with dReHo values in right PreCG in slow-5, left PoCG in slow-5, and left MOG in typical band.ConclusiondReHo and dfALFF abnormalities in different frequency bands may be the key characteristics in the pathogenesis mechanism of non-NPSLE.

Dopaminergic modulation of regional cerebral blood flow: An arterial spin labelling study of genetic and pharmacological manipulation of COMT activity

Dopamine has direct and complex vasoactive effects on cerebral circulation. Catechol-O-methyltransferase (COMT) regulates cortical dopamine, and its activity can be influenced both genetically and pharmacologically. COMT activity influences the functional connectivity of the PFC at rest, as well as its activity during task performance, determined using blood oxygen level-dependent (BOLD) fMRI. However, its effects on cerebral perfusion have been relatively unexplored. Here, 76 healthy males, homozygous for the functional COMT Val158Met polymorphism, were administered either the COMT inhibitor tolcapone or placebo in a double-blind, randomised design. We then assessed regional cerebral blood flow at rest using pulsed arterial spin labelling. Perfusion was affected by both genotype and drug. COMT genotype affected frontal regions (Val158 > Met158), whilst tolcapone influenced parietal and temporal regions (placebo > tolcapone). There was no genotype by drug interaction. Our data demonstrate that lower COMT activity is associated with lower cerebral blood flow, although the regions affected differ between those affected by genotype compared with those altered by acute pharmacological inhibition. The results extend the evidence for dopaminergic modulation of cerebral blood flow. Our findings also highlight the importance of considering vascular effects in functional neuroimaging studies, and of exercising caution in ascribing group differences in BOLD signal solely to altered neuronal activity if information about regional perfusion is not available.

The Role of Cerebrovascular-Reactivity Mapping in Functional MRI: Calibrated fMRI and Resting-State fMRI.

Task and resting-state functional MRI (fMRI) is primarily based on the same blood-oxygenation level-dependent (BOLD) phenomenon that MRI-based cerebrovascular reactivity (CVR) mapping has most commonly relied upon. This technique is finding an ever-increasing role in neuroscience and clinical research as well as treatment planning. The estimation of CVR has unique applications in and associations with fMRI. In particular, CVR estimation is part of a family of techniques called calibrated BOLD fMRI, the purpose of which is to allow the mapping of cerebral oxidative metabolism (CMRO2) using a combination of BOLD and cerebral-blood flow (CBF) measurements. Moreover, CVR has recently been shown to be a major source of vascular bias in computing resting-state functional connectivity, in much the same way that it is used to neutralize the vascular contribution in calibrated fMRI. Furthermore, due to the obvious challenges in estimating CVR using gas challenges, a rapidly growing field of study is the estimation of CVR without any form of challenge, including the use of resting-state fMRI for that purpose. This review addresses all of these aspects in which CVR interacts with fMRI and the role of CVR in calibrated fMRI, provides an overview of the physiological biases and assumptions underlying hypercapnia-based CVR and calibrated fMRI, and provides a view into the future of non-invasive CVR measurement.

Point-spread function of the BOLD response across columns and cortical depth in human extra-striate cortex.

Columns and layers are fundamental organizational units of the brain. Well known examples of cortical columns are the ocular dominance columns (ODCs) in primary visual cortex and the column-like stripe-based arrangement in the second visual area V2. The spatial scale of columns and layers is beyond the reach of conventional neuroimaging, but the advent of high field magnetic resonance imaging (MRI) scanners (UHF, 7 T and above) has opened the possibility to acquire data at this spatial scale, in-vivo and non-invasively in humans. The most prominent non-invasive technique to measure brain function is blood oxygen level dependent (BOLD) fMRI, measuring brain activity indirectly, via changes in hemodynamics. A key determinant of the ability of high-resolution BOLD fMRI to accurately resolve columns and layers is the point-spread function (PSF) of the BOLD response in relation to the spatial extent of neuronal activity. In this study we take advantage of the stripe-based arrangement present in visual area V2, coupled with sub-millimetre anatomical and gradient-echo BOLD (GE BOLD) acquisition at 7 T to obtain PSF estimates and along cortical depth in human participants. Results show that the BOLD PSF is maximal in the superficial part of the cortex (1.78 mm), and it decreases with increasing cortical depth (0.83 mm close to white matter).

Cerebrovascular Reactivity Mapping Using Resting-State BOLD Functional MRI in Healthy Adults and Patients with Moyamoya Disease.

Background Cerebrovascular reserve, the potential capacity of brain tissue to receive more blood flow when needed, is a desirable marker in evaluating ischemic risk. However, current measurement methods require acetazolamide injection or hypercapnia challenge, prompting a clinical need for resting-state (RS) blood oxygen level-dependent (BOLD) functional MRI data to measure cerebrovascular reactivity (CVR). Purpose To optimize and evaluate an RS CVR MRI technique and demonstrate its relationship to neurosurgical treatment. Materials and Methods In this HIPAA-compliant study, RS BOLD functional MRI data collected in 170 healthy controls between December 2008 and September 2010 were retrospectively evaluated to identify the optimal frequency range of temporal filtering on the basis of spatial correlation with the reference standard CVR map obtained with CO2 inhalation. Next, the optimized RS method was applied in a new, prospective cohort of 50 participants with Moyamoya disease who underwent imaging between June 2014 and August 2019. Finally, CVR values were compared between brain hemispheres with and brain hemispheres without revascularization surgery by using Mann-Whitney U test. Results A total of 170 healthy controls (mean age ± standard deviation, 51 years ± 20; 105 women) and 100 brain hemispheres of 50 participants with Moyamoya disease (mean age, 41 years ± 12; 43 women) were evaluated. RS CVR maps based on a temporal filtering frequency of [0, 0.1164 Hz] yielded the highest spatial correlation (r = 0.74) with the CO2 inhalation CVR results. In patients with Moyamoya disease, 77 middle cerebral arteries (MCAs) had stenosis. RS CVR in the MCA territory was lower in the group that did not undergo surgery (n = 30) than in the group that underwent surgery (n = 47) (mean, 0.407 relative units [ru] ± 0.208 vs 0.532 ru ± 0.182, respectively; P = .006), which is corroborated with the CO2 inhalation CVR data (mean, 0.242 ru ± 0.273 vs 0.437 ru ± 0.200; P = .003). Conclusion Cerebrovascular reactivity mapping performed by using resting-state blood oxygen level-dependent functional MRI provided a task-free method to measure cerebrovascular reserve and depicted treatment effect of revascularization surgery in patients with Moyamoya disease comparable to that with the reference standard of CO2 inhalation MRI. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Wolf and Ware in this issue.