Hemodynamic scaling of fMRI-BOLD signal: validation of low-frequency spectral amplitude as a scalability factor

Spontaneous Brain Activity Alterations in First-Episode Psychosis: A Meta-analysis of Functional Magnetic Resonance Imaging Studies

BACKGROUND AND HYPOTHESIS

Several studies have shown that spontaneous brain activity, including the total and fractional amplitude of low-frequency fluctuations (LFF) and regional homogeneity (ReHo), is altered in psychosis. Nonetheless, neuroimaging results show a high heterogeneity. For this reason, we gathered the extant literature on spontaneous brain activity in first-episode psychosis (FEP), where the effects of long-term treatment and chronic disease are minimal.

STUDY DESIGN

A systematic research was conducted on PubMed, Scopus, and Web of Science to identify studies exploring spontaneous brain activity and local connectivity in FEP estimated using functional magnetic resonance imaging. 20 LFF and 15 ReHo studies were included. Coordinate-Based Activation Likelihood Estimation Meta-Analyses stratified by brain measures, age (adolescent vs adult), and drug-naïve status were performed to identify spatially-convergent alterations in spontaneous brain activity in FEP.

STUDY RESULTS

We found a significant increase in LFF in FEP compared to healthy controls (HC) in the right striatum and in ReHo in the left striatum. When pooling together all studies on LFF and ReHo, spontaneous brain activity was increased in the bilateral striatum and superior and middle frontal gyri and decreased in the right precentral gyrus and the right inferior frontal gyrus compared to HC. These results were also replicated in the adult and drug-naïve samples.

CONCLUSIONS

Abnormalities in the frontostriatal circuit are present in early psychosis independently of treatment status. Our findings support the view that altered frontostriatal can represent a core neural alteration of the disorder and could be a target of treatment.

Detection and Mitigation of Neurovascular Uncoupling in Brain Gliomas

Functional magnetic resonance imaging (fMRI) with blood oxygen level-dependent (BOLD) technique is useful for preoperative mapping of brain functional networks in tumor patients, providing reliable in vivo detection of eloquent cortex to help reduce the risk of postsurgical morbidity. BOLD task-based fMRI (tb-fMRI) is the most often used noninvasive method that can reliably map cortical networks, including those associated with sensorimotor, language, and visual functions. BOLD resting-state fMRI (rs-fMRI) is emerging as a promising ancillary tool for visualization of diverse functional networks. Although fMRI is a powerful tool that can be used as an adjunct for brain tumor surgery planning, it has some constraints that should be taken into consideration for proper clinical interpretation. BOLD fMRI interpretation may be limited by neurovascular uncoupling (NVU) induced by brain tumors. Cerebrovascular reactivity (CVR) mapping obtained using breath-hold methods is an effective method for evaluating NVU potential.

Correspondence between BOLD fMRI task response and cerebrovascular reactivity across the cerebral cortex

BOLD sensitivity to baseline perfusion and blood volume is a well-acknowledged fMRI confound. Vascular correction techniques based on cerebrovascular reactivity (CVR) might reduce variance due to baseline cerebral blood volume, however this is predicated on an invariant linear relationship between CVR and BOLD signal magnitude. Cognitive paradigms have relatively low signal, high variance and involve spatially heterogenous cortical regions; it is therefore unclear whether the BOLD response magnitude to complex paradigms can be predicted by CVR. The feasibility of predicting BOLD signal magnitude from CVR was explored in the present work across two experiments using different CVR approaches. The first utilized a large database containing breath-hold BOLD responses and 3 different cognitive tasks. The second experiment, in an independent sample, calculated CVR using the delivery of a fixed concentration of carbon dioxide and a different cognitive task. An atlas-based regression approach was implemented for both experiments to evaluate the shared variance between task-invoked BOLD responses and CVR across the cerebral cortex. Both experiments found significant relationships between CVR and task-based BOLD magnitude, with activation in the right cuneus (R ² = 0.64) and paracentral gyrus (R ² = 0.71), and the left pars opercularis (R ² = 0.67), superior frontal gyrus (R ² = 0.62) and inferior parietal cortex (R ² = 0.63) strongly predicted by CVR. The parietal regions bilaterally were highly consistent, with linear regressions significant in these regions for all four tasks. Group analyses showed that CVR correction increased BOLD sensitivity. Overall, this work suggests that BOLD signal response magnitudes to cognitive tasks are predicted by CVR across different regions of the cerebral cortex, providing support for the use of correction based on baseline vascular physiology.

Computational approaches to predicting treatment response to obesity using neuroimaging

Obesity is a worldwide disease associated with multiple severe adverse consequences and comorbid conditions. While an increased body weight is the defining feature in obesity, etiologies, clinical phenotypes and treatment responses vary between patients. These variations can be observed within individual treatment options which comprise lifestyle interventions, pharmacological treatment, and bariatric surgery. Bariatric surgery can be regarded as the most effective treatment method. However, long-term weight regain is comparably frequent even for this treatment and its application is not without risk. A prognostic tool that would help predict the effectivity of the individual treatment methods in the long term would be essential in a personalized medicine approach. In line with this objective, an increasing number of studies have combined neuroimaging and computational modeling to predict treatment outcome in obesity. In our review, we begin by outlining the central nervous mechanisms measured with neuroimaging in these studies. The mechanisms are primarily related to reward-processing and include "incentive salience" and psychobehavioral control. We then present the diverse neuroimaging methods and computational prediction techniques applied. The studies included in this review provide consistent support for the importance of incentive salience and psychobehavioral control for treatment outcome in obesity. Nevertheless, further studies comprising larger sample sizes and rigorous validation processes are necessary to answer the question of whether or not the approach is sufficiently accurate for clinical real-world application.

The Cerebrovascular Reactivity-Adjusted Spontaneous Brain Activity Abnormalities in White Matter Hyperintensities Related Cognitive Impairment: A Resting-State Functional MRI Study

BACKGROUND

The BOLD signal is regulated by neuronal activity and vascular physiology. The evolution pattern of brain activities after modulating the vascular factors in white matter hyperintensities (WMHs) related cognitive impairment (CI) was unknown.

OBJECTIVE

To explore the "pure" low-frequency fluctuation (ALFF) alterations after adjusting the cerebrovascular reactivity (CVR) factor.

METHODS

In this study, 111 WMHs subjects including 55 with CI (WMH-CI) and 56 without CI (WMH-no-CI), and 72 normal controls (NCs) underwent resting-state fMRI. The CVR and ALFF maps were derived using BOLD data. A voxel-wise Pearson analysis was performed to detect the relationship between CVR and ALFF maps. The ANCOVA analysis with and without CVR as a covariate was conducted to explore the effect of CVR on ALFF analysis. Correlation between the ALFF alterations and cognitive performance was conducted in WMH-CI subjects. The receiver operating characteristic curve was constructed to assess the diagnostic performance of ALFF indexes to determine the occurrence of CI.

RESULTS

There was a significant widespread correlation between the CVR and ALFF maps. The ALFF alterations between the WMH groups and NC group with CVR as covariate were more than those without CVR as covariate. WMH-CI subjects showed further ALFF alterations when compared with WMH-no-CI subjects. The abnormal ALFF values were significantly associated with poor performance. The combination of inferior frontal gyrus and middle frontal gyrus to PCC provided an incremental contribution to the occurrence of CI.

CONCLUSION

More areas with abnormal ALFF values which were specific to the WMHs related cognitive dysfunction were detected when considering the impact of CVR.

Effects of Thresholding on Voxel-Wise Correspondence of Breath-Hold and Resting-State Maps of Cerebrovascular Reactivity

Functional magnetic resonance imaging for presurgical brain mapping enables neurosurgeons to identify viable tissue near a site of operable pathology which might be at risk of surgery-induced damage. However, focal brain pathology (e.g., tumors) may selectively disrupt neurovascular coupling while leaving the underlying neurons functionally intact. Such neurovascular uncoupling can result in false negatives on brain activation maps thereby compromising their use for surgical planning. One way to detect potential neurovascular uncoupling is to map cerebrovascular reactivity using either an active breath-hold challenge or a passive resting-state scan. The equivalence of these two methods has yet to be fully established, especially at a voxel level of resolution. To quantitatively compare breath-hold and resting-state maps of cerebrovascular reactivity, we first identified threshold settings that optimized coverage of gray matter while minimizing false responses in white matter. When so optimized, the resting-state metric had moderately better gray matter coverage and specificity. We then assessed the spatial correspondence between the two metrics within cortical gray matter, again, across a wide range of thresholds. Optimal spatial correspondence was strongly dependent on threshold settings which if improperly set tended to produce statistically biased maps. When optimized, the two CVR maps did have moderately good correspondence with each other (mean accuracy of 73.6%). Our results show that while the breath-hold and resting-state maps may appear qualitatively similar they are not quantitatively identical at a voxel level of resolution.

A practical modification to a resting state fMRI protocol for improved characterization of cerebrovascular function

Cerebrovascular reactivity (CVR), defined here as the Blood Oxygenation Level Dependent (BOLD) response to a CO₂ pressure change, is a useful metric of cerebrovascular function. Both the amplitude and the timing (hemodynamic lag) of the CVR response can bring insight into the nature of a cerebrovascular pathology and aid in understanding noise confounds when using functional Magnetic Resonance Imaging (fMRI) to study neural activity. This research assessed a practical modification to a typical resting-state fMRI protocol, to improve the characterization of cerebrovascular function. In 9 healthy subjects, we modelled CVR and lag in three resting-state data segments, and in data segments which added a 2–3 minute breathing task to the start of a resting-state segment. Two different breathing tasks were used to induce fluctuations in arterial CO₂ pressure: a breath-hold task to induce hypercapnia (CO₂ increase) and a cued deep breathing task to induce hypocapnia (CO₂ decrease). Our analysis produced voxel-wise estimates of the amplitude (CVR) and timing (lag) of the BOLD-fMRI response to CO₂ by systematically shifting the CO₂ regressor in time to optimize the model fit. This optimization inherently increases gray matter CVR values and fit statistics. The inclusion of a simple breathing task, compared to a resting-state scan only, increases the number of voxels in the brain that have a significant relationship between CO₂ and BOLD-fMRI signals, and improves our confidence in the plausibility of voxel-wise CVR and hemodynamic lag estimates. We demonstrate the clinical utility and feasibility of this protocol in an incidental finding of Moyamoya disease, and explore the possibilities and challenges of using this protocol in younger populations. This hybrid protocol has direct applications for CVR mapping in both research and clinical settings and wider applications for fMRI denoising and interpretation.

Altered spontaneous neural activity in the precuneus, middle and superior frontal gyri, and hippocampus in college students with subclinical depression

BACKGROUND

Subclinical depression (ScD) is a prevalent condition associated with relatively mild depressive states, and it poses a high risk of developing into major depressive disorder (MDD). However, the neural pathology of ScD is still largely unknown. Identifying the spontaneous neural activity involved in ScD may help clarify risk factors for MDD and explore treatment strategies for mild stages of depression.

METHODS

A total of 34 ScD subjects and 40 age-, sex-, and education-matched healthy controls were screened from 1105 college students. The amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) of resting-state fMRI were calculated to reveal neural activity. Strict statistical strategies, including Gaussian random field (GRF), false discovery rate (FDR), and permutation test (PT) with threshold-free cluster enhancement (TFCE), were conducted. Based on the altered ALFF and ReHo, resting-state functional connectivity (RSFC) was further analyzed using a seed-based approach.

RESULTS

The right precuneus and left middle frontal gyrus (MFG) both showed significantly increased ALFF and ReHo in ScD subjects. Moreover, the left hippocampus and superior frontal gyrus (SFG) showed decreased ALFF and increased ReHo, respectively. In addition, ScD subjects showed increased RSFC between MFG and hippocampus compared to healthy controls, and significant positive correlation was found between the Beck Depression Inventory-II (BDI-II) score and RSFC from MFG to hippocampus in ScD group.

CONCLUSION

Spontaneous neural activities in the right precuneus, left MFG, SFG, and hippocampus were altered in ScD subjects. Functional alterations in these dorsolateral prefrontal cortex and default mode network regions are largely related to abnormal emotional processing in ScD, and indicate strong associations with brain impairments in MDD, which provide insight into potential pathophysiology mechanisms of subclinical depression.

Distinct effects of prematurity on MRI metrics of brain functional connectivity, activity, and structure: Univariate and multivariate analyses

Premature birth affects the developmental trajectory of the brain during a period of intense maturation with possible lifelong consequences. To better understand the effect of prematurity on brain structure and function, we performed blood‐oxygen‐level dependent (BOLD) and anatomical magnetic resonance imaging (MRI) at 40 weeks of postmenstrual age on 88 newborns with variable gestational age (GA) at birth and no evident radiological alterations. We extracted measures of resting‐state functional connectivity and activity in a set of 90 cortical and subcortical brain regions through the evaluation of BOLD correlations between regions and of fractional amplitude of low‐frequency fluctuation (fALFF) within regions, respectively. Anatomical information was acquired through the assessment of regional volumes. We performed univariate analyses on each metric to examine the association with GA at birth, the spatial distribution of the effects, and the consistency across metrics. Moreover, a data‐driven multivariate analysis (i.e., Machine Learning) framework exploited the high dimensionality of the data to assess the sensitivity of each metric to the effect of premature birth. Prematurity was associated with bidirectional alterations of functional connectivity and regional volume and, to a lesser extent, of fALFF. Notably, the effects of prematurity on functional connectivity were spatially diffuse, mainly within cortical regions, whereas effects on regional volume and fALFF were more focal, involving subcortical structures. While the two analytical approaches delivered consistent results, the multivariate analysis was more sensitive in capturing the complex pattern of prematurity effects. Future studies might apply multivariate frameworks to identify premature infants at risk of a negative neurodevelopmental outcome.

[Energy metabolism disorder and functional magnetic resonance imaging of the medial prefrontal cortex in mice with chronic unpredictable mild stress]

OBJECTIVE

To analyze spontaneous activities and energy metabolism in the medial prefrontal cortex (mPFC) of mice with chronic unpredictable mild stress (CUMS) and explore the correlation of these changes with the mTORC1 signaling pathway.

OBJECTIVE

Normal C57Bl/6 mice were randomly divided into control group (n=16) and depression model group (n= 16), and the mice in the latter group were subjected to 8 weeks of modeling with CUMS. Behavioral tests including open field test, sucrose consumption test, tail suspension test and forced swimming test were performed, and the changes in prefrontal gray matter volume and the amplitude of low frequency fluctuation (ALFF) in the mice were detected with functional magnetic resonance imaging. The CUMS mice were then randomized into two groups for treatment with ketamine (n=8) or saline (n=8). The mPFC tissues of the mice were collected for detecting the phosphorylation levels of mTORC1-related proteins with Western blotting and ATP level and NADP ⁺/NADPH ratio with ELISA in the 3 groups.

OBJECTIVE

Compared with the control mice, CUMS mice exhibited a distinct depressive phenotype with significantly decreased sucrose preference (P < 0.05) and shortened total distances (P < 0.01) and central exercise distances (P < 0.05) in the open field test without obvious changes of immobile time in tail suspension test and forced swimming test (P>0.05). Prefrontal gray matter volume and mALFF increased (P < 0.01), and the phosphorylation level of mTORC1- related proteins, ATP level and NADP ⁺/NADPH ratio all decreased significantly (P < 0.05) in CUMS mice. After ketamine treatment, the phosphorylation level of mTORC1-related proteins and ATP level increased significantly in CUMS mice (P < 0.05), but the increase of NADP ⁺/NADPH ratio was not statistically significant.

OBJECTIVE

The mPFC of CUMS mice shows increased spontaneous activities but lowered productivity efficiency, indicating the presence of energy metabolism disorder in the mPFC, which is related with reduced mTORC1 phosphorylation and can be alleviated by activating the mTORC1 pathway with ketamine.

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.

Inferring Macroscale Brain Dynamics via Fusion of Simultaneous EEG-fMRI

Advances in the instrumentation and signal processing for simultaneously acquired electroencephalography and functional magnetic resonance imaging (EEG-fMRI) have enabled new ways to observe the spatiotemporal neural dynamics of the human brain. Central to the utility of EEG-fMRI neuroimaging systems are the methods for fusing the two data streams, with machine learning playing a key role. These methods can be dichotomized into those that are symmetric and asymmetric in terms of how the two modalities inform the fusion. Studies using these methods have shown that fusion yields new insights into brain function that are not possible when each modality is acquired separately. As technology improves and methods for fusion become more sophisticated, the future of EEG-fMRI for noninvasive measurement of brain dynamics includes mesoscale mapping at ultrahigh magnetic resonance fields, targeted perturbation-based neuroimaging, and using deep learning to uncover nonlinear representations that link the electrophysiological and hemodynamic measurements.

Resting cerebral oxygen metabolism exhibits archetypal network features

Standard magnetic resonance imaging approaches offer high‐resolution but indirect measures of neural activity, limiting understanding of the physiological processes associated with imaging findings. Here, we used calibrated functional magnetic resonance imaging during the resting state to recover low‐frequency fluctuations of the cerebral metabolic rate of oxygen (CMRO₂). We tested whether functional connections derived from these fluctuations exhibited organization properties similar to those established by previous standard functional and anatomical connectivity studies. Seventeen participants underwent 20 min of resting imaging during dual‐echo, pseudocontinuous arterial spin labeling, and blood‐oxygen‐level dependent (BOLD) signal acquisition. Participants also underwent a 10 min normocapnic and hypercapnic procedure. Brain‐wide, CMRO₂ low‐frequency fluctuations were subjected to graph‐based and voxel‐wise functional connectivity analyses. Results demonstrated that connections derived from resting CMRO₂ fluctuations exhibited complex, small‐world topological properties (i.e., high integration and segregation, cost efficiency) consistent with those observed in previous studies using functional and anatomical connectivity approaches. Voxel‐wise CMRO₂ connectivity also exhibited spatial patterns consistent with four targeted resting‐state subnetworks: two association (i.e., frontoparietal and default mode) and two perceptual (i.e., auditory and occipital‐visual). These are the first findings to support the use of calibration‐derived CMRO₂ low‐frequency fluctuations for detecting brain‐wide organizational properties typical of healthy participants. We discuss interpretations, advantages, and challenges in using calibration‐derived oxygen metabolism signals for examining the intrinsic organization of the human brain.

Cerebrovascular Reactivity Mapping Without Gas Challenges: A Methodological Guide

Cerebrovascular reactivity (CVR) is defined as the ability of vessels to alter their caliber in response to vasoactive factors, by means of dilating or constricting, in order to increase or decrease regional cerebral blood flow (CBF). Importantly, CVR may provide a sensitive biomarker for pathologies where vasculature is compromised. Furthermore, the spatiotemporal dynamics of CVR observed in healthy subjects, reflecting regional differences in cerebral vascular tone and response, may also be important in functional MRI studies based on neurovascular coupling mechanisms. Assessment of CVR is usually based on the use of a vasoactive stimulus combined with a CBF measurement technique. Although transcranial Doppler ultrasound has been frequently used to obtain global flow velocity measurements, MRI techniques are being increasingly employed for obtaining CBF maps. For the vasoactive stimulus, vasodilatory hypercapnia is usually induced through the manipulation of respiratory gases, including the inhalation of increased concentrations of carbon dioxide. However, most of these methods require an additional apparatus and complex setups, which not only may not be well-tolerated by some populations but are also not widely available. For these reasons, strategies based on voluntary breathing fluctuations without the need for external gas challenges have been proposed. These include the task-based methodologies of breath holding and paced deep breathing, as well as a new generation of methods based on spontaneous breathing fluctuations during resting-state. Despite the multitude of alternatives to gas challenges, existing literature lacks definitive conclusions regarding the best practices for the vasoactive modulation and associated analysis protocols. In this work, we perform an extensive review of CVR mapping techniques based on MRI and CO2 variations without gas challenges, focusing on the methodological aspects of the breathing protocols and corresponding data analysis. Finally, we outline a set of practical guidelines based on generally accepted practices and available data, extending previous reports and encouraging the wider application of CVR mapping methodologies in both clinical and academic MRI settings.

The Problem of Neurovascular Uncoupling

Neurovascular uncoupling (NVU) is one of the most important confounds of blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMR imaging) in the setting of focal brain lesions such as brain tumors. This article reviews the assessment of NVU related to focal brain lesions with emphasis on the use of cerebrovascular reactivity mapping measurement methods and resting state BOLD fMR imaging metrics in the detection of NVU, as well as the use of amplitude of low-frequency fluctuation metrics to mitigate the effects of NVU on clinical fMR imaging activation.

Hemodynamic Scaling of Task-Induced Signal Changes in Tumor Subjects

Background: FMRI signal amplitude can change during stimulus presentation due to underlying neural function and hemodynamic responses limiting the accuracy of fMRI in pre-surgical planning. To account for these changes in fMRI activation signal, we used breath-hold tasks to mimic hemodynamic changes in brain tumor subjects and scaled the activation response.

Methods: Motor and/or language fMRI was performed in 21 subjects with brain tumor. A breath-hold task was also performed in these subjects to obtain the hemodynamic response changes independent of neural changes. The task activation signals were calibrated on a voxel wise basis for all the subjects. Direct cortical stimulation was used to verify the scaled results of task-based fMRI.

Results: After scaling for the hemodynamic response function (HRF) on a voxel wise basis, the spatial extent of the scaled activation was more clustered together and appeared to minimize false positives. Similarly, accounting for the underlying canonical HRF, the percentage increase of active voxels after scaling had lower standard non-deviation suggesting that the activation response across voxels were more similar.

Conclusion: Although preliminary in nature, this study suggests that the variation in hemodynamic changes can be calibrated using breath-hold in brain tumor subjects and can also be used for other clinical cases where the underlying HRF has been altered.

Resting-State Functional Connectivity: Signal Origins and Analytic Methods

Resting state functional connectivity (RSFC) has been widely studied in functional magnetic resonance imaging (fMRI) and is observed by a significant temporal correlation of spontaneous low-frequency signal fluctuations (SLFs) both within and across hemispheres during rest. Different hypotheses of RSFC include the biophysical origin hypothesis and cognitive origin hypothesis, which show that the role of SLFs and RSFC is still not completely understood. Furthermore, RSFC and age studies have shown an "age-related compensation" phenomenon. RSFC data analysis methods include time domain analysis, seed-based correlation, regional homogeneity, and principal and independent component analyses. Despite advances in RSFC, the authors also discuss challenges and limitations, ranging from head motion to methodological limitations.

Cortical laminar resting-state signal fluctuations scale with the hypercapnic blood oxygenation level-dependent response

Calibrated functional magnetic resonance imaging can remove unwanted sources of signal variability in the blood oxygenation level‐dependent (BOLD) response. This is achieved by scaling, using information from a perfusion‐sensitive scan during a purely vascular challenge, typically induced by a gas manipulation or a breath‐hold task. In this work, we seek for a validation of the use of the resting‐state fluctuation amplitude (RSFA) as a scaling factor to remove vascular contributions from the BOLD response. Given the peculiarity of depth‐dependent vascularization in gray matter, BOLD and vascular space occupancy (VASO) data were acquired at submillimeter resolution and averaged across cortical laminae. RSFA from the primary motor cortex was, thus, compared to the amplitude of hypercapnia‐induced signal changes (tSD_hc) and with the M factor of the Davis model on a laminar level. High linear correlations were observed for RSFA and tSD_hc (R² = 0.92 ± 0.06) and somewhat reduced for RSFA and M (R² = 0.62 ± 0.19). Laminar profiles of RSFA‐normalized BOLD signal changes yielded good agreement with corresponding VASO profiles. Overall, this suggests that RSFA contains strong vascular components and is also modulated by baseline quantities contained in the M factor. We conclude that RSFA may replace the scaling factor tSD_hc for normalizing the laminar BOLD response.

A vascular-task response dependency and its application in functional imaging of brain tumors

PURPOSE

Preoperative functional MRI (fMRI) is limited by a muted BOLD response caused by abnormal vasoreactivity and resultant neurovascular uncoupling adjacent to malignant brain tumors. We propose to overcome this limitation and more accurately identify eloquent areas adjacent to brain tumors by independently assessing vasoreactivity using breath-holding and incorporating these data into the fMRI analysis.

METHODS

Local vasoreactivity using a breath-holding paradigm with the same timing as the functional motor and language tasks was determined in 16 patients (9 glioblastomas, 1 anaplastic astrocytoma, 5 low grade astrocytomas, and 1 metastasis) and 6 healthy control subjects. We derived an fMRI model based on an observed vaso-task response dependency that takes into account the altered hemodynamics adjacent to brain tumors.

RESULTS

In both healthy controls and brain tumor subjects, we found a statistical dependency between breath-hold and task BOLD response. In tumor subjects, activation maps that take into account this vaso-task dependency demonstrated clinically meaningful areas of activation that were not seen using the task-only analysis in about half of the cases studied. This included localization of language areas adjacent to brain tumors.

CONCLUSIONS

The present preliminary results demonstrate that neurovascular uncoupling known to affect the accuracy of BOLD fMRI adjacent to brain tumors may be, at least partially, overcome by incorporating an observed vaso-task dependency in the BOLD signal analysis.

Resting CMRO2 fluctuations show persistent network hyper-connectivity following exposure to sub-concussive collisions

Exposure to head impacts may alter brain connectivity within cortical hubs such as the default-mode network (DMN). However, studies have yet to consider the confounding effects of altered resting cerebral blood flow (CBF0) and cerebrovascular reactivity (CVR) on changes in connectivity following sub-concussive impacts. Here, 23 Canadian collegiate football players were followed during a season using calibrated resting-state MRI and helmet accelerometers to examine the interplay between the neural and vascular factors that determine functional connectivity (FC). Connectivity-based analyses using blood oxygen level dependent (BOLD) and cerebral metabolic rate of oxygen consumption (CMRO2) mapping were used to study the DMN longitudinally. Network-specific decreases in CBF0 were observed one month following the season, while impaired CVR was documented at both mid-season and one month following the season, compared to pre-season baseline. Alterations in CBF0 and BOLD-based CVR throughout the season suggest that neurophysiological markers may show different susceptibility timelines following head impacts. DMN connectivity was increased throughout the season, independent of changes in cerebrovascular physiology, suggesting that alterations in FC following sub-concussive impacts are robust and independent of changes in brain hemodynamics. No significant correlations between impact kinematics and DMN connectivity changes were documented in this study. Altogether, these findings create a strong paradigm for future studies to examine the underlying neural and vascular mechanisms associated with increases in network connectivity following repeated exposure to sub-concussive collisions, in an effort to improve management of head impacts in contact sports.

Effect sizes of BOLD CVR, resting-state signal fluctuations and time delay measures for the assessment of hemodynamic impairment in carotid occlusion patients

Background and purpose

The BOLD signal amplitude as a response to a hypercapnia stimulus is commonly used to assess cerebrovascular reserve. Despite recent advances, the implementation remains cumbersome and alternative ways to assess hemodynamic impairment are desirable. Resting-state BOLD signal fluctuations (rsBOLD) have been proposed however data on its sensitivity and dependence on baseline venous cerebral blood volume (vCBV) is limited. The primary aim of this study was to compare the effect sizes of resting-state and hypercapnia induced BOLD signal changes in the detection of hemodynamic impairment. The second aim of the study was to assess the dependence of BOLD signal variability on vCBV.

Materials and methods

Fifteen patients with internal carotid artery occlusive disease and 15 matched healthy controls were included in this study. The BOLD signal was derived from a dual-echo gradient-echo echo-planar sequence during hypercapnia (HC) and hyperoxia (HO) gas modulations. BOLD (fractional) amplitude of low frequency fluctuations ((f)ALFF) was compared to HC-BOLD, BOLD response delays derived from time delay analysis and ΔBOLD in response to progressively increasing HC. Effect sizes (i.e. the standard mean difference between patients and controls) were calculated. HO-BOLD was used to estimate vCBV, and its contribution to the variability in rsBOLD signal was evaluated.

Results

The effect sizes of ALFF and fALFF (0.61 and 0.72) were lower than the effect sizes related to hypercapnia-based hemodynamic assessment analysis; 1.62, 1.56 and 0.90 for HC-BOLD, BOLD response delays and ΔBOLD in response to progressively increasing HC. A moderate relation was found between (f)ALFF and HC-BOLD in controls (R² of 0.61 and 0.42), but this relation decreased in patients (R² of 0.33 and 0.15). (f)ALFF did not differ between patients and controls whereas HC-BOLD did (p < 0.005). The ΔBOLD response to progressively increasing HC was significantly different in between patients and controls for ΔEtCO₂ values ≥ 2 mmHg (at +2  mmHg F(1, 18) = 5.85, p = 0.026). Up to 31% and 53% of the variance in the ALFF and HC-BOLD spatial distribution could be explained by HO-BOLD.

Conclusion

ALFF and fALFF demonstrated a moderate effect size to detect hemodynamic impairment whereas the effect size was large for methods employing a hypercapnia-based vascular stress stimulus. Based on our analysis of BOLD signal change as a response to a progressively increasing hypercapnia stimulus we can argue that a hypercapnia stimulus of at least 2 mmHg above baseline EtCO₂ is necessary to evaluate hemodynamic impairment. We also demonstrated that a substantial amount of information imbedded in the rsBOLD and HC-BOLD was explained by HO-BOLD. HO-BOLD can serve as a proxy for vCBV and this thus indicates that one should be careful when adopting these techniques in disease cases with compromised CBV.

Limitations of Resting-State Functional MR Imaging in the Setting of Focal Brain Lesions

Methods of image acquisition and analysis for resting-state functional MR imaging (rsfMR imaging) are still evolving. Neurovascular uncoupling and susceptibility artifact are important confounds of rsfMR imaging in the setting of focal brain lesions such as brain tumors. This article reviews the detection of these confounds using rsfMR imaging metrics in the setting of focal brain lesions. In the near future, with the wide range of ongoing research in rsfMR imaging, these issues likely will be overcome and will open new windows into brain function and connectivity.

Value of Frequency Domain Resting-State Functional Magnetic Resonance Imaging Metrics Amplitude of Low-Frequency Fluctuation and Fractional Amplitude of Low-Frequency Fluctuation in the Assessment of Brain Tumor-Induced Neurovascular Uncoupling

The aim of this study was to explore whether the phenomenon of brain tumor-related neurovascular uncoupling (NVU) in resting-state blood oxygen level-dependent functional magnetic resonance imaging (BOLD fMRI) (rsfMRI) may also affect the resting-state fMRI (rsfMRI) frequency domain metrics the amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF). Twelve de novo brain tumor patients, who underwent clinical fMRI examinations, including task-based fMRI (tbfMRI) and rsfMRI, were included in this Institutional Review Board-approved study. Each patient displayed decreased/absent tbfMRI activation in the primary ipsilesional (IL) sensorimotor cortex in the absence of a corresponding motor deficit or suboptimal task performance, consistent with NVU. Z-score maps for the motor tasks were obtained from general linear model analysis (reflecting motor activation vs. rest). Seed-based correlation analysis (SCA) maps of sensorimotor network, ALFF, and fALFF were calculated from rsfMRI data. Precentral and postcentral gyri in contralesional (CL) and IL hemispheres were parcellated using an automated anatomical labeling template for each patient. Region of interest (ROI) analysis was performed on four maps: tbfMRI, SCA, ALFF, and fALFF. Voxel values in the CL and IL ROIs of each map were divided by the corresponding global mean of ALFF and fALFF in the cortical brain tissue. Group analysis revealed significantly decreased IL ALFF (p = 0.02) and fALFF (p = 0.03) metrics compared with CL ROIs, consistent with similar findings of significantly decreased IL BOLD signal for tbfMRI (p = 0.0005) and SCA maps (p = 0.0004). The frequency domain metrics ALFF and fALFF may be markers of lesion-induced NVU in rsfMRI similar to previously reported alterations in tbfMRI activation and SCA-derived resting-state functional connectivity maps.

Implication of the Slow-5 Oscillations in the Disruption of the Default-Mode Network in Healthy Aging and Stroke

The processes of normal aging and aging-related pathologies subject the brain to an active re-organization of its brain networks. Among these, the default-mode network (DMN) is consistently implicated with a demonstrated reduction in functional connectivity within the network. However, no clear stipulation on the underlying mechanisms of the de-synchronization has yet been provided. In this study, we examined the spectral distribution of the intrinsic low-frequency oscillations (LFOs) of the DMN sub-networks in populations of young normals, older subjects, and acute and subacute ischemic stroke patients. The DMN sub-networks were derived using a mid-order group independent component analysis with 117 eyes-closed resting-state functional magnetic resonance imaging (rs-fMRI) sessions from volunteers in those population groups, isolating three robust components of the DMN among other resting-state networks. The posterior component of the DMN presented noticeable differences. Measures of amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) of the network component demonstrated a decrease in resting-state cortical oscillation power in the elderly (normal and patient), specifically in the slow-5 (0.01-0.027 Hz) range of oscillations. Furthermore, the contribution of the slow-5 oscillations during the resting state was diminished for a greater influence of the slow-4 (0.027-0.073 Hz) oscillations in the subacute stroke group, not only suggesting a vulnerability of the slow-5 oscillations to disruption but also indicating a change in the distribution of the oscillations within the resting-state frequencies. The reduction of network slow-5 fALFF in the posterior DMN component was found to present a potential association with behavioral measures, suggesting a brain-behavior relationship to those oscillations, with this change in behavior potentially resulting from an altered network integrity induced by a weakening of the slow-5 oscillations during the resting state. The repeated identification of those frequencies in the disruption of DMN stresses a critical role of the slow-5 oscillations in network disruption, and it accentuates the importance of managing those oscillations in the health of the DMN.

Cerebrovascular reactivity measured by functional magnetic resonance imaging during breath-hold challenge: A systematic review

Cerebrovascular reactivity (CVR) is the cerebral hemodynamic response to a vasoactive substance. Breath-hold (BH) induced CVR has the advantage of being non-invasive and easy to implement during magnetic resonance imaging (MRI). We systematically reviewed the literature regarding MRI measurement of BH induced CVR. The literature was searched using MEDLINE with the search terms breath-hold; and MRI or cerebrovascular reactivity. The search yielded 2244 results and 54 articles were included. Between-group comparisons have found that CVR was higher among healthy controls than patients with various pathologies (e.g. sleep apnea, diabetes, hypertension etc.). However, counter-intuitive findings have also been reported, including higher CVR among smokers, sedentary individuals, and patients with schizophrenia vs.

CONTROLS

Methodological studies have highlighted important measurement characteristics (e.g. normalizing signal to end-tidal CO₂), and comparisons of BH induced CVR to non-BH methods. Future studies are warranted to address questions about group differences, treatment response, disease progression, and other salient clinical themes. Standardization of CVR and BH designs is needed to fully exploit the potential of this practical non-invasive method.

Brain plasticity and migraine transformation: fMRI evidences

INTRODUCTION

Chronification transforms episodic migraine into the pathologic chronic form. Biological characteristics of the migrainous brain progressively change, in predisposed subjects, under the repetition of external and internal stimuli. Modifications involve neurons, synapses, neurotransmitters, receptors, connectivity and pain control. f-MRI is a promising way to explore the still unclear biology of this progression. Areas covered: Data included were obtained from the most relevant and updated works available on PubMed about this topic. We summarized the pathophysiology of migraine chronification and of brain plasticity, and we described the different fMRI techniques and their main evidences about migraine transformation. Expert commentary: Functional-MRI has revealed many aspects regarding the peculiarity of the migrainous brain and its tendency toward chronicity but a series of questions are still open: What are the hallmarks of the predisposition to chronification? Which elements are the cause and which the consequence of this process?

Hypercapnic evaluation of vascular reactivity in healthy aging and acute stroke via functional MRI

Functional MRI (fMRI) is well-established for the study of brain function in healthy populations, although its clinical application has proven more challenging. Specifically, cerebrovascular reactivity (CVR), which allows the assessment of the vascular response that serves as the basis for fMRI, has been shown to be reduced in healthy aging as well as in a range of diseases, including chronic stroke. However, the timing of when this occurs relative to the stroke event is unclear. We used a breath-hold fMRI task to evaluate CVR across gray matter in a group of acute stroke patients (< 10 days from stroke; N = 22) to address this question. These estimates were compared with those from both age-matched (N = 22) and younger (N = 22) healthy controls. As expected, young controls had the greatest mean CVR, as indicated by magnitude and extent of fMRI activation; however, stroke patients did not differ from age-matched controls. Moreover, the ipsilesional and contralesional hemispheres of stroke patients did not differ with respect to any of these measures. These findings suggest that fMRI remains a valid tool within the first few days of a stroke, particularly for group fMRI studies in which findings are compared with healthy subjects of similar age. However, given the relatively high variability in CVR observed in our stroke sample, caution is warranted when interpreting fMRI data from individual patients or a small cohort. We conclude that a breath-hold task can be a useful addition to functional imaging protocols for stroke patients.

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Breath-holding can be used to assess the validity of fMRI in stroke patients.

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Vascular reactivity, estimated by breath-hold fMRI, was greatest in young controls.

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Acute stroke patients and age-matched controls had similar vascular reactivity.

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Modeling the breath-hold response on an individual basis can improve results.

Quantitative mapping of cerebrovascular reactivity using resting-state BOLD fMRI: Validation in healthy adults

In conventional neuroimaging, cerebrovascular reactivity (CVR) is quantified primarily using the blood-oxygenation level-dependent (BOLD) functional MRI (fMRI) signal, specifically, as the BOLD response to intravascular carbon dioxide (CO2) modulations, in units of [%ΔBOLD/mmHg]. While this method has achieved wide appeal and clinical translation, the tolerability of CO2-related tasks amongst patients and the elderly remains a challenge in more routine and large-scale applications. In this work, we propose an improved method to quantify CVR by exploiting intrinsic fluctuations in CO2 and corresponding changes in the resting-state BOLD signal (rs-qCVR). Our rs-qCVR approach requires simultaneous monitoring of PETCO2, cardiac pulsation and respiratory volume. In 16 healthy adults, we compare our quantitative CVR estimation technique to the prospective CO2-targeting based CVR quantification approach (qCVR, the "standard"). We also compare our rs-CVR to non-quantitative alternatives including the resting-state fluctuation amplitude (RSFA), amplitude of low-frequency fluctuation (ALFF) and global-signal regression. When all subjects were pooled, only RSFA and ALFF were significantly associated with qCVR. However, for characterizing regional CVR variations within each subject, only the PETCO2-based rs-qCVR measure is strongly associated with standard qCVR in 100% of the subjects (p≤0.1). In contrast, for the more qualitative CVR measures, significant within-subject association with qCVR was only achieved in 50-70% of the subjects. Our work establishes the feasibility of extracting quantitative CVR maps using rs-fMRI, opening the possibility of mapping functional connectivity and qCVR simultaneously.

Differing Patterns of Altered Slow-5 Oscillations in Healthy Aging and Ischemic Stroke

The 'default-mode' network (DMN) has been investigated in the presence of various disorders, such as Alzheimer's disease and Autism spectrum disorders. More recently, this investigation has expanded to include patients with ischemic injury. Here, we characterized the effects of ischemic injury in terms of its spectral distribution of resting-state low-frequency oscillations and further investigated whether those specific disruptions were unique to the DMN, or rather more general, affecting the global cortical system. With 43 young healthy adults, 42 older healthy adults, 14 stroke patients in their early stage (<7 days after stroke onset), and 16 stroke patients in their later stage (between 1 to 6 months after stroke onset), this study showed that patterns of cortical system disruption may differ between healthy aging and following the event of an ischemic stroke. The stroke group in the later stage demonstrated a global reduction in the amplitude of the slow-5 oscillations (0.01-0.027 Hz) in the DMN as well as in the primary visual and sensorimotor networks, two 'task-positive' networks. In comparison to the young healthy group, the older healthy subjects presented a decrease in the amplitude of the slow-5 oscillations specific to the components of the DMN, while exhibiting an increase in oscillation power in the task-positive networks. These two processes of a decrease DMN and an increase in 'task-positive' slow-5 oscillations may potentially be related, with a deficit in DMN inhibition, leading to an elevation of oscillations in non-DMN systems. These findings also suggest that disruptions of the slow-5 oscillations in healthy aging may be more specific to the DMN while the disruptions of those oscillations following a stroke through remote (diaschisis) effects may be more widespread, highlighting a non-specificity of disruption on the DMN in stroke population. The mechanisms underlying those differing modes of network disruption need to be further explored to better inform our understanding of brain function in healthy individuals and following injury.

Recovery of slow-5 oscillations in a longitudinal study of ischemic stroke patients

Functional networks in resting-state fMRI are identified by characteristics of their intrinsic low-frequency oscillations, more specifically in terms of their synchronicity. With advanced aging and in clinical populations, this synchronicity among functionally linked regions is known to decrease and become disrupted, which may be associated with observed cognitive and behavioral changes. Previous work from our group has revealed that oscillations within the slow-5 frequency range (0.01–0.027 Hz) are particularly susceptible to disruptions in aging and following a stroke. In this study, we characterized longitudinally the changes in the slow-5 oscillations in stroke patients across two different time-points. We followed a group of ischemic stroke patients (n = 20) and another group of healthy older adults (n = 14) over two visits separated by a minimum of three months (average of 9 months). For the stroke patients, one visit occurred in their subacute window (10 days to 6 months after stroke onset), the other took place in their chronic window (> 6 months after stroke). Using a mid-order group ICA method on 10-minutes eyes-closed resting-state fMRI data, we assessed the frequency distributions of a component's representative time-courses for differences in regards to slow-5 spectral power. First, our stroke patients, in their subacute stage, exhibited lower amplitude slow-5 oscillations in comparison to their healthy counterparts. Second, over time in their chronic stage, those same patients showed a recovery of those oscillations, reaching near equivalence to the healthy older adult group. Our results indicate the possibility of an eventual recovery of those initially disrupted network oscillations to a near-normal level, providing potentially a biomarker for stroke recovery of the cortical system. This finding opens new avenues in infra-slow oscillation research and could serve as a useful biomarker in future treatments aimed at recovery.

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Slow-5 oscillation amplitudes are reduced in stroke patients at the subacute stage.

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Slow-5 oscillation amplitudes correlate with cognitive performance.

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Slow-5 oscillations recover in the same patients at the chronic stage.

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Findings support the high implication of slow-5 oscillations in network disruption.

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Slow-5 oscillations may serve as a bio-marker of functional network health.

The association between cerebrovascular reactivity and resting-state fMRI functional connectivity in healthy adults: The influence of basal carbon dioxide

Although widely used in resting-state fMRI (fMRI) functional connectivity measurement (fcMRI), the BOLD signal is only an indirect measure of neuronal activity, and is inherently modulated by both neuronal activity and vascular physiology. For instance, cerebrovascular reactivity (CVR) varies widely across individuals irrespective of neuronal function, but the implications for fcMRI are currently unknown. This knowledge gap compromises our ability to correctly interpret fcMRI measurements. In this work, we investigate the relationship between CVR and resting fcMRI measurements in healthy young adults, in both the motor and the executive-control networks. We modulate CVR within each individual by subtly increasing and decreasing resting vascular tension through baseline end-tidal CO2 (PETCO2), and measure fcMRI during these hypercapnic, hypocapnic and normocapnic states. Furthermore, we assess the association between CVR and fcMRI within and across individuals. Within individuals, resting PETCO2 is found to significantly influence both CVR and resting fcMRI values. In addition, we find resting fcMRI to be significantly and positively associated with CVR across the group in both networks. This relationship is potentially mediated by concomitant alterations in BOLD signal fluctuation amplitude. This work clearly demonstrates and quantifies a major vascular modulator of resting fcMRI, one that is also subject and regional dependent. We suggest that individualized correction for CVR effects in fcMRI measurements is essential for fcMRI studies of healthy brains, and can be even more important in studying diseased brains.

Age-Related Changes in Inter-Network Connectivity by Component Analysis

Healthy aging is associated with brain changes that reflect an alteration to a functional unit in response to the available resources and architecture. Even before the onset of noticeable cognitive decline, the neural scaffolds underlying cognitive function undergo considerable change. Prior studies have suggested a disruption of the connectivity pattern within the "default-mode" network (DMN), and more specifically a disruption of the anterio-posterior connectivity. In this study, we explored the effects of aging on within-network connectivity of three DMN subnetworks: a posterior DMN (pDMN), an anterior DMN (aDMN), and a ventral DMN (vDMN); as well as between-network connectivity during resting-state. Using groupICA on 43 young and 43 older healthy adults, we showed a reduction of network co-activation in two of the DMN subnetworks (pDMN and aDMN) and demonstrated a difference in between-component connectivity levels. The older group exhibited more numerous high-correlation pairs (Pearson's rho > 0.3, Number of comp-pairs = 46) in comparison to the young group (Number of comp-pairs = 34), suggesting a more connected/less segregated cortical system. Moreover, three component-pairs exhibited statistically significant differences between the two populations. Visual areas V2-V1 and V2-V4 were more correlated in the older adults, while aDMN-pDMN correlation decreased with aging. The increase in the number of high-correlation component-pairs and the elevated correlation in the visual areas are consistent with the prior hypothesis that aging is associated with a reduction of functional segregation. However, the aDMN-pDMN dis-connectivity may be occurring under a different mechanism, a mechanism more related to a breakdown of structural integrity along the anterio-posterior axis.

The influence of mild carbon dioxide on brain functional homotopy using resting-state fMRI

Homotopy reflects the intrinsic functional architecture of the brain through synchronized spontaneous activity between corresponding bilateral regions, measured as voxel mirrored homotopic connectivity (VMHC). Hypercapnia is known to have clear impact on brain hemodynamics through vasodilation, but have unclear effect on neuronal activity. This study investigates the effect of hypercapnia on brain homotopy, achieved by breathing 5% carbon dioxide (CO2 ) gas mixture. A total of 14 healthy volunteers completed three resting state functional MRI (RS-fMRI) scans, the first and third under normocapnia and the second under hypercapnia. VMHC measures were calculated as the correlation between the BOLD signal of each voxel and its counterpart in the opposite hemisphere. Group analysis was performed between the hypercapnic and normocapnic VMHC maps. VMHC showed a diffused decrease in response to hypercapnia. Significant regional decreases in VMHC were observed in all anatomical lobes, except for the occipital lobe, in the following functional hierarchical subdivisions: the primary sensory-motor, unimodal, heteromodal, paralimbic, as well as in the following functional networks: ventral attention, somatomotor, default frontoparietal, and dorsal attention. Our observation that brain homotopy in RS-fMRI is affected by arterial CO2 levels suggests that caution should be used when comparing RS-fMRI data between healthy controls and patients with pulmonary diseases and unusual respiratory patterns such as sleep apnea or chronic obstructive pulmonary disease.

Lateralized resting-state functional connectivity in the task-positive and task-negative networks

Studies on functional brain lateralization using functional magnetic resonance imaging (fMRI) have generally focused on lateralization of local brain regions. To explore the lateralization on the whole-brain level, lateralization of functional connectivity using resting-state fMRI (N=87, right handed) was analyzed and left- and right-lateralized networks were mapped. Four hundred two equally spaced regions of interest (ROI) covering the entire gray matter were divided into 358 task-positive and 44 task-negative ROIs. Lateralization of functional connectivity was analyzed separately for the task-positive and task-negative regions to prevent spuriously high lateralization indices caused by negative correlations between task-positive and task-negative regions. Lateralized functional connections were obtained using k-means clustering analysis. Within the task-positive network, the right-lateralized functional connections were between the occipital and inferior/middle frontal regions among other connections, whereas the left-lateralized functional connections were among fusiform gyrus and inferior frontal and inferior/superior parietal regions. Within the task-negative network, the left-lateralized connections were mainly between the precuneus and medial prefrontal regions. Specific brain regions exhibited different left- or right-lateralized connections with other regions, which suggest the importance of reporting lateralized connections over lateralized seed regions. The mean lateralization indices of the left- and right-lateralized connections were correlated, suggesting that the lateralization of connectivity may result from complementary processes between the lateralized networks. The potential functions of the lateralized networks were discussed.

Intrinsic patterns of coupling between correlation and amplitude of low-frequency fMRI fluctuations are disrupted in degenerative dementia mainly due to functional disconnection

Low frequency fluctuations (LFFs) of the BOLD signal are a major discovery in the study of the resting brain with functional magnetic resonance imaging (fMRI). Two fMRI-based measures, functional connectivity (FC), a measure of signal synchronicity, and the amplitude of LFFs (ALFF), a measure of signal periodicity, have been proved to be sensitive to changes induced by several neurological diseases, including degenerative dementia. In spite of the increasing use of these measures, whether and how they are related to each other remains to be elucidated. In this work we used voxel-wise FC and ALFF computed in different frequency bands (slow-5: 0.01-0.027 Hz; slow-4: 0.027-0.073 Hz; and full-band: 0.01-0.073 Hz), in order to assess their relationship in healthy elderly as well as the relevant changes induced by Alzheimer’s Disease (AD) and Mild Cognitive Impairment (MCI). We found that in healthy elderly subjects FC and ALFF are positively correlated in anterior and posterior cingulate cortex (full-band, slow-4 and slow-5), temporal cortex (full-band and slow-5), and in a set of subcortical regions (full-band and slow-4). These correlation patterns between FC and ALFF were absent in either AD or MCI patients. Notably, the loss of correlation between FC and ALFF in the AD group was primarily due to changes in FC rather than in ALFF. Our results indicate that degenerative dementia is characterized by a loss of global connection rather than by a decrease of fluctuation amplitude.

Stability of low-frequency fluctuation amplitudes in prolonged resting-state fMRI

The (fractional) amplitudes of low-frequency fluctuations (f)ALFF are popular measures for the magnitude of low-frequency oscillations in resting-state fMRI (R-fMRI) data. Both measures can be directly derived from the spectral power of R-fMRI time courses. Numerous studies suggest that ALFF and fALFF might be used as biomarkers for a variety of diseases including schizophrenia, major depressive disorder, and obsessive-compulsive disorder. However, the temporal stability of (f)ALFF values, which is of great importance for the application of (f)ALFF both as a biomarker and scaling parameter, has not been studied in detail yet. Here, we quantify the temporal stability, robustness and reproducibility of both ALFF and fALFF maps obtained from R-fMRI data by performing statistical analyses over 55 minute resting-state scans which included a period of NaCl infusion. We also examine the differences of using either raw or standardised (f)ALFF maps. Our analyses show that no significant changes of (f)ALFF values over the 55minute period occur for both raw and standardised (f)ALFF maps. In addition, we demonstrate that raw (f)ALFF maps across subjects are correlated with head motion as quantified via frame-wise displacement, whereas no such correlation is present in standardised (f)ALFF maps. In conclusion, the results of our study show that both ALFF and fALFF qualify as potential biomarkers due to their high temporal stability.

Assessment of unconstrained cerebrovascular reactivity marker for large age-range FMRI studies

Breath hold (BH), a commonly used task to measure cerebrovascular reactivity (CVR) in fMRI studies varies in outcome among individuals due to subject-physiology and/or BH-inspiration/expiration differences (i.e., performance). In prior age-related fMRI studies, smaller task-related BOLD response variability is observed among younger than older individuals. Also, a linear CVR versus task relationship exists in younger individuals which maybe useful to test the accuracy of CVR responses in older groups. Hence we hypothesized that subject-related physiological and/or BH differences, if present, may compromise CVR versus task linearity in older individuals. To test the hypothesis, empirical BH versus task relationships from motor and cognitive areas were obtained in younger (mean age = 26 years) and older (mean age = 58 years) human subjects. BH versus task linearity was observed only in the younger group, confirming our hypothesis. Further analysis indicated BH responses and its variability to be similar in both younger and older groups, suggesting that BH may not accurately represent CVR in a large age range. Using the resting state fluctuation of amplitude (RSFA) as an unconstrained alternative to BH, subject-wise correspondence between BH and RSFA was tested. Correlation between BH versus RSFA was significant within the motor but was not significant in the cognitive areas in the younger and was completely disrupted in both areas in the older subjects indicating that BH responses are constrained by subject-related physiology and/or performance-related differences. Contrasting BH to task, RSFA-task relationships were independent of age accompanied by age-related increases in CVR variability as measured by RSFA, not observed with BH. Together the results obtained indicate that RSFA accurately represents CVR in any age range avoiding multiple and yet unknown physiologic and task-related pitfalls of BH.

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

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

Neurovascular factors in resting-state functional MRI

There has been growing interest in the use of resting-state functional magnetic resonance imaging (rsfMRI) for the assessment of disease and treatment, and a number of studies have reported significant disease-related changes in resting-state blood oxygenation level dependent (BOLD) signal amplitude and functional connectivity. rsfMRI is particularly suitable for clinical applications because the approach does not require the patient to perform a task and scans can be obtained in a relatively short amount of time. However, the mechanisms underlying resting-state BOLD activity are not well understood and thus the interpretation of changes in resting state activity is not always straightforward. The BOLD signal represents the hemodynamic response to neural activity, and changes in resting-state activity can reflect a complex combination of neural, vascular, and metabolic factors. This paper examines the role of neurovascular factors in rsfMRI and reviews approaches for the interpretation and analysis of resting state measures in the presence of confounding factors.

Abnormal amplitude low-frequency oscillations in medication-naive, first-episode patients with major depressive disorder: a resting-state fMRI study

BACKGROUND

Recent resting-state fMRI studies on major depressive disorder (MDD) have found altered temporal correlation between low-frequency oscillations (LFOs). However, changes on the amplitudes of these LFOs remain largely unknown.

METHODS

Twenty-two medication-naive, first-episode patients with MDD and 19 age-, sex-, education-matched healthy controls were recruited. Resting-state fMRI was obtained by using an echo-planar imaging sequence and the fractional amplitude of low-frequency fluctuations (fALFF) was calculated to investigate the amplitude of LFOs in the resting state.

RESULTS

Compared with control subjects, patients with MDD showed significantly decreased fALFF in right cerebellum posterior lobe, left parahippocampal gyrus and right middle frontal gyrus and increased fALFF in left superior occipital gyrus/cuneus (p<0.05, corrected for multiple comparisons). Further receiver operating characteristic curves (ROC) analyses suggested that the alterations of fALFF in these regions might be used as markers to classify patients with MDD from healthy controls.

CONCLUSIONS

These findings indicated LFOs abnormalities in MDD and the fALFF analysis might be a potential approach in further exploration of this disorder.

Age-related differences in memory-encoding fMRI responses after accounting for decline in vascular reactivity

BOLD fMRI has provided a wealth of information about the aging brain. A common finding is that posterior regions of the brain manifest an age-related decrease in activation while the anterior regions show an age-related increase. Several neurocognitive models have been proposed to interpret these findings. However, one issue that has not been sufficiently considered to date is that the BOLD signal is based on vascular responses secondary to neural activity. Thus the above findings could be in part due to a vascular change, especially in view of the expected decline of vascular health with age. In the present study, we aim to examine age-related differences in memory-encoding fMRI response in the context of vascular aging. One hundred and thirty healthy subjects ranging from 20 to 89 years old underwent a scene-viewing fMRI task and, in the same session, cerebrovascular reactivity (CVR) was measured in each subject using a CO2-inhalation task. Without accounting for the influence of vascular changes, the task-activated fMRI signal showed the typical age-related decrease in visual cortex and medial temporal lobe (MTL), but manifested an increase in the right inferior frontal gyrus (IFG). In the same individuals, an age-related CVR reduction was observed in all of these regions. We then used a previously proposed normalization approach to calculate a CVR-corrected fMRI signal, which was defined as the uncorrected signal divided by CVR. Based on the CVR-corrected fMRI signal, an age-related increase is now seen in both the left and right sides of IFG; and no brain regions showed a signal decrease with age. We additionally used a model-based approach to examine the fMRI data in the context of CVR, which again suggested an age-related change in the two frontal regions, but not in the visual and MTL regions.

RESCALE: Voxel-specific task-fMRI scaling using resting state fluctuation amplitude

The BOLD signal measured in fMRI studies depends not only on neuronal activity, but also on other parameters like tissue vascularization, which may vary between subjects and between brain regions. A correction for variance from vascularization effects can thus lead to improved group statistics by reducing inter-subject variability. The fractional amplitude of low-frequency fluctuations (fALFF) as determined in a resting-state scan has been shown to be dependent on vascularization. Here we present a correction method termed RESCALE (REsting-state based SCALing of parameter Estimates) that uses local information to compute a voxel-wise scaling factor based on the correlation structure of fALFF and task activation parameter estimates from within a cube of 3 × 3 × 3 surrounding that voxel. The scaling method was used on a visuo-motor paradigm and resulted in a consistent increase in t-values in all task-activated cortical regions, with increases in peak t-values of 37.0% in the visual cortex and 12.7% in the left motor cortex. The RESCALE method as proposed herein can be easily applied to all task-based fMRI group studies provided that resting-state data for the same subject group is also acquired.

The influence of the amplitude of low-frequency fluctuations on resting-state functional connectivity

Studies of brain functional connectivity have provided a better understanding of organization and integration of large-scale brain networks. Functional connectivity using resting-state functional magnetic resonance imaging (fMRI) is typically based upon the correlations of the low-frequency fluctuation of fMRI signals. Reproducible spatial maps in the brain have also been observed using the amplitude of low-frequency fluctuations (ALFF) in resting-state. However, little is known about the influence of the ALFF on the functional connectivity measures. In the present study, we analyzed resting-state fMRI data on 79 healthy old individuals. Spatial independent component analysis and regions of interest (ROIs) based connectivity analysis were performed to obtain measures of functional connectivity. ALFF maps were also calculated. First, voxel-matched inter-subject correlations were computed between back-reconstructed IC and ALFF maps. For all the resting-state networks, there was a consistent correlation between ALFF variability and network strengths (within regions that had high IC strengths). Next, inter-subject variance of correlations across 160 functionally defined ROIs were correlated with the corresponding ALFF variance. The connectivity of several ROIs to other regions were more likely to correlate with its own regional ALFF. These regions were mainly located in the anterior cingulate cortex, medial prefrontal cortex, precuneus, insula, basal ganglia, and thalamus. These associations may suggest a functional significance of functional connectivity modulations. Alternatively, the fluctuation amplitudes may arise from physiological noises, and therefore, need to be controlled when studying resting-state functional connectivity.

An introduction to normalization and calibration methods in functional MRI

In functional magnetic resonance imaging (fMRI), the blood oxygenation level dependent (BOLD) signal is often interpreted as a measure of neural activity. However, because the BOLD signal reflects the complex interplay of neural, vascular, and metabolic processes, such an interpretation is not always valid. There is growing evidence that changes in the baseline neurovascular state can result in significant modulations of the BOLD signal that are independent of changes in neural activity. This paper introduces some of the normalization and calibration methods that have been proposed for making the BOLD signal a more accurate reflection of underlying brain activity for human fMRI studies.

Evaluating the effects of systemic low frequency oscillations measured in the periphery on the independent component analysis results of resting state networks

Independent component analysis (ICA) is widely used in resting state functional connectivity studies. ICA is a data-driven method, which uses no a priori anatomical or functional assumptions. However, as a result, it still relies on the user to distinguish the independent components (ICs) corresponding to neuronal activation, peripherally originating signals (without directly attributable neuronal origin, such as respiration, cardiac pulsation and Mayer wave), and acquisition artifacts. In this concurrent near infrared spectroscopy (NIRS)/functional MRI (fMRI) resting state study, we developed a method to systematically and quantitatively identify the ICs that show strong contributions from signals originating in the periphery. We applied group ICA (MELODIC from FSL) to the resting state data of 10 healthy participants. The systemic low frequency oscillation (LFO) detected simultaneously at each participant's fingertip by NIRS was used as a regressor to correlate with every subject-specific IC time course. The ICs that had high correlation with the systemic LFO were those closely associated with previously described sensorimotor, visual, and auditory networks. The ICs associated with the default mode and frontoparietal networks were less affected by the peripheral signals. The consistency and reproducibility of the results were evaluated using bootstrapping. This result demonstrates that systemic, low frequency oscillations in hemodynamic properties overlay the time courses of many spatial patterns identified in ICA analyses, which complicates the detection and interpretation of connectivity in these regions of the brain.

Prediction of Task-Related BOLD fMRI with Amplitude Signatures of Resting-State fMRI

Blood oxygen contrast-functional magnetic resonance imaging (fMRI) signals are a convolution of neural and vascular components. Several studies indicate that task-related (T-fMRI) or resting-state (R-fMRI) responses linearly relate to hypercapnic task responses. Based on the linearity of R-fMRI and T-fMRI with hypercapnia demonstrated by different groups using different study designs, we hypothesized that R-fMRI and T-fMRI signals are governed by a common physiological mechanism and that resting-state fluctuation of amplitude (RSFA) should be linearly related to T-fMRI responses. We tested this prediction in a group of healthy younger humans where R-fMRI, T-fMRI, and hypercapnic (breath hold, BH) task measures were obtained form the same scan session during resting state and during performance of motor and BH tasks. Within individual subjects, significant linear correlations were observed between motor and BH task responses across voxels. When averaged over the whole brain, the subject-wise correlation between the motor and BH tasks showed a similar linear relationship within the group. Likewise, a significant linear correlation was observed between motor-task activity and RSFA across voxels and subjects. The linear rest-task (R-T) relationship between motor activity and RSFA suggested that R-fMRI and T-fMRI responses are governed by similar physiological mechanisms. A practical use of the R-T relationship is its potential to estimate T-fMRI responses in special populations unable to perform tasks during fMRI scanning. Using the R-T relationship determined from the first group of 12 healthy subjects, we predicted the T-fMRI responses in a second group of 7 healthy subjects. RSFA in both the lower and higher frequency ranges robustly predicted the magnitude of T-fMRI responses at the subject and voxel levels. We propose that T-fMRI responses are reliably predictable to the voxel level in situations where only R-fMRI measures are possible, and may be useful for assessing neural activity in task non-compliant clinical populations.

Calibrating BOLD fMRI activations with neurovascular and anatomical constraints

Functional magnetic resonance imaging signals, in addition to reflecting neuronal response, also contain physiological variances. These factors may introduce variability into blood oxygen level-dependent (BOLD) activation results, particularly in different population groups. In this study, we hypothesized that the amplitude as well as the spatial extent of BOLD activation could be improved after minimizing the variance caused by the neurovascular and anatomical factors. Subjects were scanned while they performed finger tapping and digit-symbol substitution tasks (DSSTs). Partial volume and neurovascular effects were estimated on a voxelwise basis using subjects' own gray matter volume (GMV), breath holding (BH), and amplitude of low-frequency fluctuation (ALFF). The results showed that all individual's GMV, BH, and ALFF could significantly predict motor and DSST activations in a voxelwise manner. Whole-brain analyses were conducted to regress out the anatomical and neurovascular information. Differential maps (obtained using t-test) indicated that the adjustment tended to suppress activation in regions that were near vessels such as midline cingulate gyrus, bilateral anterior insula, and posterior cerebellum. These results suggest that voxelwise adjustment using GMV and neurovascular parameters can minimize structural and physiological variances among individuals and be used for quantitative comparisons.