Functional connectivity in BOLD and CBF data: similarity and reliability of resting brain networks

Multiparameter neuroimaging study of neurovascular coupling changes in patients with end-stage renal disease

PURPOSE

To assess changes in neurovascular coupling (NVC) by evaluating the relationship between cerebral perfusion and brain connectivity in patients with end-stage renal disease (ESRD) undergoing hemodialysis versus in healthy control participants. And by exploring brain regions with abnormal NVC associated with cognitive deficits in patients, we aim to provide new insights into potential preventive and therapeutic interventions.

MATERIALS AND METHODS

A total of 45 patients and 40 matched healthy controls were prospectively enrolled in our study. Montreal Cognitive Assessment (MoCA) was used to assess cognitive function. Arterial spin labeling (ASL) was used to calculate cerebral blood flow (CBF), and graph theory-based analysis of results from resting-state functional magnetic resonance imaging (rs-fMRI) was used to calculate brain network topological parameters (node betweenness centrality [BC], node efficiency [Ne], and node degree centrality [DC]). Three NVC biomarkers (CBF-BC, CBF-Ne, and CBF-DC coefficients) at the whole brain level and 3 NVC biomarkers (CBF/BC, CBF/Ne, and CBF/DC ratios) at the local brain region level were used to assess NVC. Mann-Whitney U tests were used to compare the intergroup differences in NVC parameters. Spearman's correlation analysis was used to evaluate the relationship among NVC dysfunctional pattern, cognitive impairment, and clinical characteristics multiple comparisons were corrected using a voxel-wise false-discovery rate (FDR) method (p < .05).

RESULTS

Patients showed significantly reduced global coupling coefficients for CBF-Ne (p = .023) and CBF-BC (p = .035) compared to healthy controls. Coupling ratios at the local brain region level were significantly higher in patients in 33 brain regions (all p values < .05). Coupling ratio changes alone or accompanied by changes in CBF, node properties, or both CBF and node properties were identified. In patients, negative correlations were seen between coupling ratios and MoCA scores in many brain regions, including the left dorsolateral superior frontal gyrus, the bilateral median cingulate and paracingulate gyri, and the right superior parietal gyrus. The correlations remained even after adjusting for hemoglobin and hematocrit levels.

CONCLUSION

Disrupted NVC may be one mechanism underlying cognitive impairment in dialysis patients.

Reversibility of Cognitive Deficits and Functional Connectivity With Transfusion in Children With Sickle Cell Disease

BACKGROUND AND OBJECTIVES

People with sickle cell disease (SCD) are at risk of cognitive dysfunction independent of stroke. Diminished functional connectivity in select large-scale networks and white matter integrity reflect the neurologic consequences of SCD. Because chronic transfusion therapy is neuroprotective in preventing stroke and strengthening executive function abilities in people with SCD, we hypothesized that red blood cell (RBC) transfusion facilitates the acute reversal of disruptions in functional connectivity while white matter integrity remains unaffected.

METHODS

Children with SCD receiving chronic transfusion therapy underwent a brain MRI measuring white matter integrity with diffusion tensor imaging and resting-state functional connectivity within 3 days before and after transfusion of RBCs. Cognitive assessments with the NIH Toolbox were acquired after transfusion and then immediately before the following transfusion cycle.

RESULTS

Sixteen children with a median age of 12.5 years were included. Global assessments of functional connectivity using homotopy (p = 0.234) or modularity (p = 0.796) did not differ with transfusion. Functional connectivity within the frontoparietal network significantly strengthened after transfusion (median intranetwork Z-score 0.21 [0.17-0.30] before transfusion, 0.29 [0.20-0.36] after transfusion, p < 0.001), while there was not a significant change seen within the sensory motor, visual, auditory, default mode, dorsal attention, or cingulo-opercular networks. Corresponding to the change within the frontoparietal network, there was a significant improvement in executive function abilities after transfusion (median executive function composite score 87.7 [81.3-90.7] before transfusion, 90.3 [84.3-93.7] after transfusion, p = 0.021). Participants with stronger connectivity in the frontoparietal network before transfusion had a significantly greater improvement in the executive function composite score with transfusion (r = 0.565, 95% CI 0.020-0.851, p = 0.044). While functional connectivity and executive abilities strengthened with transfusion, there was not a significant change in white matter integrity as assessed by fractional anisotropy and mean diffusivity within 16 white matter tracts or globally with tract-based spatial statistics.

DISCUSSION

Strengthening of functional connectivity with concomitant improvement in executive function abilities with transfusion suggests that functional connectivity MRI could be used as a biomarker for acutely reversible neurocognitive injury as novel therapeutics are developed for people with SCD.

Mapping brain state-dependent sensory responses across the mouse cortex

Sensory information must be integrated across a distributed brain network for stimulus processing and perception. Recent studies have revealed specific spatiotemporal patterns of cortical activation for the early and late components of sensory-evoked responses, which are associated with stimulus features and perception, respectively. Here, we investigated how the brain state influences the sensory-evoked activation across the mouse cortex. We utilized isoflurane to modulate the brain state and conducted wide-field calcium imaging of Thy1-GCaMP6f mice to monitor distributed activation evoked by multi-whisker stimulation. Our findings reveal that the level of anesthesia strongly shapes the spatiotemporal features and the functional connectivity of the sensory-activated network. As anesthesia levels decrease, we observe increasingly complex responses, accompanied by the emergence of the late component within the sensory-evoked response. The persistence of the late component under anesthesia raises new questions regarding the potential existence of perception during unconscious states.

The novel imaging methods in diagnosis and assessment of cerebrovascular diseases: an overview

Cerebrovascular diseases, including ischemic strokes, hemorrhagic strokes, and vascular malformations, are major causes of morbidity and mortality worldwide. The advancements in neuroimaging techniques have revolutionized the field of cerebrovascular disease diagnosis and assessment. This comprehensive review aims to provide a detailed analysis of the novel imaging methods used in the diagnosis and assessment of cerebrovascular diseases. We discuss the applications of various imaging modalities, such as computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), and angiography, highlighting their strengths and limitations. Furthermore, we delve into the emerging imaging techniques, including perfusion imaging, diffusion tensor imaging (DTI), and molecular imaging, exploring their potential contributions to the field. Understanding these novel imaging methods is necessary for accurate diagnosis, effective treatment planning, and monitoring the progression of cerebrovascular diseases.

Stronger influence of systemic than local hemodynamic-vascular factors on resting-state BOLD functional connectivity

Correlated fluctuations in the blood oxygenation level dependent (BOLD) signal of resting-state functional MRI (i.e., BOLD-functional connectivity, BOLD-FC) reflect a spectrum of neuronal and non-neuronal processes. In particular, there are multiple hemodynamic-vascular influences on BOLD-FC on both systemic (e.g., perfusion delay) and local levels (e.g., neurovascular coupling). While the influence of individual factors has been studied extensively, combined and comparative studies of systemic and local hemodynamic-vascular factors on BOLD-FC are scarce, notably in humans. We employed a multi-modal MRI approach to investigate and compare distinct hemodynamic-vascular processes and their impact on homotopic BOLD-FC in healthy controls and patients with unilateral asymptomatic internal carotid artery stenosis (ICAS). Asymptomatic ICAS is a cerebrovascular disorder, in which neuronal functioning is largely preserved but hemodynamic-vascular processes are impaired, mostly on the side of stenosis. Investigated indicators for local hemodynamic-vascular processes comprise capillary transit time heterogeneity (CTH) and cerebral blood volume (CBV) from dynamic susceptibility contrast (DSC) MRI, and cerebral blood flow (CBF) from pseudo-continuous arterial spin labeling (pCASL). Indicators for systemic processes are time-to-peak (TTP) from DSC MRI and BOLD lags from functional MRI. For each of these parameters, their influence on BOLD-FC was estimated by a comprehensive linear mixed model. Equally across groups, we found that individual mean BOLD-FC, local (CTH, CBV, and CBF) and systemic (TTP and BOLD lag) hemodynamic-vascular factors together explain 40.7% of BOLD-FC variance, with 20% of BOLD-FC variance explained by hemodynamic-vascular factors, with an about two-times larger contribution of systemic versus local factors. We conclude that regional differences in blood supply, i.e., systemic perfusion delays, exert a stronger influence on BOLD-FC than impairments in local neurovascular coupling.

Similar neural pathways link psychological stress and brain-age in health and multiple sclerosis

Clinical and neuroscientific studies suggest a link between psychological stress and reduced brain health in health and neurological disease but it is unclear whether mediating pathways are similar. Consequently, we applied an arterial-spin-labeling MRI stress task in 42 healthy persons and 56 with multiple sclerosis, and investigated regional neural stress responses, associations between functional connectivity of stress-responsive regions and the brain-age prediction error, a highly sensitive machine learning brain health biomarker, and regional brain-age constituents in both groups. Stress responsivity did not differ between groups. Although elevated brain-age prediction errors indicated worse brain health in patients, anterior insula-occipital cortex (healthy persons: occipital pole; patients: fusiform gyrus) functional connectivity correlated with brain-age prediction errors in both groups. Finally, also gray matter contributed similarly to regional brain-age across groups. These findings might suggest a common stress-brain health pathway whose impact is amplified in multiple sclerosis by disease-specific vulnerability factors.

Alexithymia characteristics are associated with salience network activity in healthy participants: an arterial spin labeling study

BACKGROUND

Alexithymia, a personality trait characterized by difficulties in identifying and expressing their emotions despite having a range of emotional experiences, can impact individuals' stress coping mechanisms. While many studies have investigated brain functions associated with specific tasks in relation to emotion processing, research focusing on resting-state brain functions has been limited. Thus, the aim of this study was to investigate the relationship between alexithymia and brain function by analyzing arterial spin labeling (ASL) data obtained during the resting state.

METHODS

A brain structural and functional imaging study was conducted on 42 healthy adult men and women using ASL and the 20-item Toronto Alexithymia Scale (TAS-20) questionnaire survey. Cerebral blood flow and functional connectivity values were calculated for regions of interest in the default mode network, saliency network, and central executive network from the ASL data. Correlation analysis was performed with TAS20 scores, and partial correlation analysis was conducted to control for anxiety and depression.

RESULTS

The functional connectivity analysis revealed a negative correlation between the functional connectivity of the right insular cortex and left anterior cingulate cortex and the total score of TAS, as well as difficulty identifying feelings and difficulty describing feeling subscores, indicating that the higher the scores, the weaker the functional connectivity between these regions (T = -3.830, p = 0.0013, R = -0.5180). This correlation remained significant even after controlling for anxiety and depression using partial correlation analysis.

CONCLUSION

The present study revealed differences in the activity of the Saliency Network at rest as measured by ASL, which were independent of anxiety and depression, and varied depending on the severity of alexithymia. This functional change may underlie the neural basis of decreased emotional processing observed in alexithymia. These findings may contribute to the elucidation of the neural mechanisms of alexithymia, which can lead to social impairments, and suggest the usefulness of ASL measurement as a biomarker of alexithymia.

Extracting functional connectivity brain networks at the resting state from pulsed arterial spin labeling data

Introduction

Functional connectivity in the brain is often studied with blood oxygenation level dependent (BOLD) resting state functional magnetic resonance imaging (rsfMRI), but the BOLD signal is several steps removed from neuronal activity. Arterial spin labeling (ASL), particularly pulsed ASL (PASL), has also the capacity to measure the blood-flow changes in response to activity. In this paper, we investigated the feasibility of extracting major brain networks from PASL data, in contrast with rsfMRI analsyis.

Materials and methods

In this retrospective study, we analyzed a cohort dataset that consists of 21 mild traumatic brain injury (mTBI) patients and 29 healthy controls, which was collected in a previous study. By extracting 10 major brain networks from the data of both PASL and rsfMRI, we contrasted their similarities and differences in the 10 networks extracted from both modalities.

Results

Our data demonstrated that PASL could be used to extract all 10 major brain networks. Eight out of 10 networks demonstrated over 60 % similarity to rsfMRI data. Meanwhile, there are similar but not identical changes in networks detected between mTBI patients and healthy controls with both modalities. Notably, the PASL-extracted default mode network (DMN), other than the rsfMRI-extracted DMN, includes some regions known to be associated with the DMN in other studies. It demonstrated that PASL data can be analyzed to identify resting state networks with reasonable reliability, even without rsfMRI data.

Conclusion

Our analysis provides an opportunity to extract functional connectivity information in heritage datasets in which ASL but not BOLD was collected.

Multimodal Classification Framework Based on Hypergraph Latent Relation for End-Stage Renal Disease Associated with Mild Cognitive Impairment

Combined arterial spin labeling (ASL) and functional magnetic resonance imaging (fMRI) can reveal more comprehensive properties of the spatiotemporal and quantitative properties of brain networks. Imaging markers of end-stage renal disease associated with mild cognitive impairment (ESRDaMCI) will be sought from these properties. The current multimodal classification methods often neglect to collect high-order relationships of brain regions and remove noise from the feature matrix. A multimodal classification framework is proposed to address this issue using hypergraph latent relation (HLR). A brain functional network with hypergraph structural information is constructed by fMRI data. The feature matrix is obtained through graph theory (GT). The cerebral blood flow (CBF) from ASL is selected as the second modal feature matrix. Then, the adaptive similarity matrix is constructed by learning the latent relation between feature matrices. Latent relation adaptive similarity learning (LRAS) is introduced to multi-task feature learning to construct a multimodal feature selection method based on latent relation (LRMFS). The experimental results show that the best classification accuracy (ACC) reaches 88.67%, at least 2.84% better than the state-of-the-art methods. The proposed framework preserves more valuable information between brain regions and reduces noise among feature matrixes. It provides an essential reference value for ESRDaMCI recognition.

Molecular-enriched functional connectivity in the human brain using multiband multi-echo simultaneous ASL/BOLD fMRI

Receptor-enriched analysis of functional connectivity by targets (REACT) is a strategy to enrich functional MRI (fMRI) data with molecular information on the neurotransmitter distribution density in the human brain, providing a biological basis to the functional connectivity (FC) analysis. Although this approach has been used in BOLD fMRI studies only so far, extending its use to ASL imaging would provide many advantages, including the more direct link of ASL with neuronal activity compared to BOLD and its suitability for pharmacological MRI studies assessing drug effects on baseline brain function. Here, we applied REACT to simultaneous ASL/BOLD resting-state fMRI data of 29 healthy subjects and estimated the ASL and BOLD FC maps related to six molecular systems. We then compared the ASL and BOLD FC maps in terms of spatial similarity, and evaluated and compared the test-retest reproducibility of each modality. We found robust spatial patterns of molecular-enriched FC for both modalities, moderate similarity between BOLD and ASL FC maps and comparable reproducibility for all but one molecular-enriched functional networks. Our findings showed that ASL is as informative as BOLD in detecting functional circuits associated with specific molecular pathways, and that the two modalities may provide complementary information related to these circuits.

Longitudinal evaluation of the functional connectivity changes in the secondary somatosensory cortex (S2) of the monkey brain during acute stroke

Background

Somatosensory deficits are frequently seen in acute stroke patients and may recover over time and affect functional outcome. However, the underlying mechanism of function recovery remains poorly understood. In the present study, progressive function alteration of the secondary somatosensory cortex (S2) and its relationship with regional perfusion and neurological outcome were examined using a monkey model of stroke.

Methods and materials

Rhesus monkeys (n = 4) were induced with permanent middle cerebral artery occlusion (pMCAo). Resting-state functional MRI, dynamic susceptibility contrast perfusion MRI, diffusion-weighted, T₁ and T₂ weighted images were collected before surgery and at 4-6, 48, and 96 h post stroke on a 3T scanner. Progressive changes of relative functional connectivity (FC), cerebral blood flow (CBF), and CBF/Tmax (Time to Maximum) of affected S2 regions were evaluated. Neurological deficits were assessed using the Spetzler approach.

Results

Ischemic lesion was evidently seen in the MCA territory including S2 in each monkey. Relative FC of injured S2 regions decreased substantially following stroke. Spetzler scores dropped substantially at 24 h post stroke but slightly recovered from Day 2 to Day 4. Relative FC progressively increased from 6 to 48 and 96 h post stroke and correlated significantly with relative CBFand CBF/Tmax changes.

Conclusion

The present study revealed the progressive alteration of function connectivity in S2 during acute stroke. The preliminary results suggested the function recovery might start couple days post occlusion and collateral circulation might play a key role in the recovery of somatosensory function after stroke insult. The relative function connectivity in S2 may provide additional information for prediction of functional outcome in stroke patients.

Diverse Task Classification from Activation Patterns of Functional Neuro-Images Using Feature Fusion Module

One of the emerging fields in functional magnetic resonance imaging (fMRI) is the decoding of different stimulations. The underlying idea is to reveal the hidden representative signal patterns of various fMRI tasks for achieving high task-classification performance. Unfortunately, when multiple tasks are processed, performance remains limited due to several challenges, which are rarely addressed since the majority of the state-of-the-art studies cover a single neuronal activity task. Accordingly, the first contribution of this study is the collection and release of a rigorously acquired dataset, which contains cognitive, behavioral, and affective fMRI tasks together with resting state. After a comprehensive analysis of the pitfalls of existing systems on this new dataset, we propose an automatic multitask classification (MTC) strategy using a feature fusion module (FFM). FFM aims to create a unique signature for each task by combining deep features with time-frequency representations. We show that FFM creates a feature space that is superior for representing task characteristics compared to their individual use. Finally, for MTC, we test a diverse set of deep-models and analyze their complementarity. Our results reveal higher classification accuracy compared to benchmarks. Both the dataset and the code are accessible to researchers for further developments.

Multimodality neuroimaging in vascular mild cognitive impairment: A narrative review of current evidence

The vascular mild cognitive impairment (VaMCI) is generally accepted as the premonition stage of vascular dementia (VaD). However, most studies are focused mainly on VaD as a diagnosis in patients, thus neglecting the VaMCI stage. VaMCI stage, though, is easily diagnosed by vascular injuries and represents a high-risk period for the future decline of patients’ cognitive functions. The existing studies in China and abroad have found that magnetic resonance imaging technology can provide imaging markers related to the occurrence and development of VaMCI, which is an important tool for detecting the changes in microstructure and function of VaMCI patients. Nevertheless, most of the existing studies evaluate the information of a single modal image. Due to the different imaging principles, the data provided by a single modal image are limited. In contrast, multi-modal magnetic resonance imaging research can provide multiple comprehensive data such as tissue anatomy and function. Here, a narrative review of published articles on multimodality neuroimaging in VaMCI diagnosis was conducted，and the utilization of certain neuroimaging bio-markers in clinical applications was narrated. These markers include evaluation of vascular dysfunction before tissue damages and quantification of the extent of network connectivity disruption. We further provide recommendations for early detection, progress, prompt treatment response of VaMCI, as well as optimization of the personalized treatment plan.

Alterations of Cerebral Blood Flow and its Connectivity Patterns Measured with Arterial Spin Labeling in Mild Cognitive Impairment

OBJECTIVES

Cerebral blood flow (CBF) is an important index for measuring brain function. Studies have shown that regional CBF changes inconsistently in mild cognitive impairment (MCI). Arterial spin labeling (ASL) is widely used in the study of CBF in patients with MCI. However, alterations in CBF connectivity in these patients remain poorly understood.

METHODS

In this study, 3D pseudo-continuous arterial spin labeling (3D-pCASL) technology was used to investigate the changes in regional CBF and CBF connectivity between 32 MCI patients and 32 healthy controls. The normalized CBF was used to reduce inter-subject variations. Both group comparisons in the CBF and correlations between CBF alterations and cognitive scores were assessed. CBF connectivity of brain regions with regional CBF differences was also compared between groups.

RESULTS

We found that compared with that in controls, the CBF was significantly reduced in the left superior parietal gyrus in MCI patients, whereas it was increased in the left precentral gyrus, right superior temporal gyrus, right putamen, and left supplementary motor area. In patients with MCI, significant correlations were identified between CBF and neuropsychological scales. Importantly, MCI patients exhibited CBF disconnections between the left supplementary motor area and the left superior parietal gyrus.

CONCLUSION

This study found that there are not only changes in regional CBF but also in CBF connectivity patterns in MCI patients compared with controls. These observations may provide a novel explanation for the neural mechanism underlying the pathophysiology in patients with Alzheimer's disease and MCI.

Functional connectivity with medial temporal regions differs across cultures during post-encoding rest

Connectivity of the brain at rest can reflect individual differences and impact behavioral outcomes, including memory. The present study investigated how culture influences functional connectivity with regions of the medial temporal lobe. In this study, 46 Americans and 59 East Asians completed a resting state scan after encoding pictures of objects. To investigate cross-cultural differences in resting state functional connectivity, left parahippocampal gyrus (anterior and posterior regions) and left hippocampus were selected as seed regions. These regions were selected, because they were previously implicated in a study of cultural differences during the successful encoding of detailed memories. Results revealed that left posterior parahippocampal gyrus had stronger connectivity with temporo-occipital regions for East Asians compared with Americans and stronger connectivity with parieto-occipital regions for Americans compared with East Asians. Left anterior parahippocampal gyrus had stronger connectivity with temporal regions for East Asians than Americans and stronger connectivity with frontal regions for Americans than East Asians. Although connectivity did not relate to memory performance, patterns did relate to cultural values. The degree of independent self-construal and subjective value of tradition were associated with functional connectivity involving left anterior parahippocampal gyrus. Findings are discussed in terms of potential cultural differences in memory consolidation or more general trait or state-based processes, such as holistic versus analytic processing.

Effect of group-based vs individualized stimulation site selection on reliability of network-targeted TMS

BACKGROUND

Transcranial magnetic stimulation (TMS) is a widely used technique for the noninvasive assessment and manipulation of brain activity and behavior. Although extensively used for research and clinical purposes, recent studies have questioned the reliability of TMS findings because of the high inter-individual variability that has been observed.

OBJECTIVE

In this study, we compared the efficacy and reliability of different targeting scenarios on the TMS-evoked response.

METHODS

24 subjects underwent a single pulse stimulation protocol over two parietal nodes belonging to the Dorsal Attention (DAN) and Default Mode (DMN) Networks respectively. Across visits, the stimulated target for both networks was chosen either based on group-derived networks' maps or personalized network topography based on individual anatomy and functional profile. All stimulation visits were conducted twice, one month apart, during concomitant electroencephalography recording.

RESULTS

At the network level, we did not observe significant differences in the TMS-evoked response between targeting conditions. However, reliable patterns of activity were observed- for both networks tested- following the individualized targeting approach. When the same analyses were carried out at the electrode space level, evidence of reliable patterns was observed following the individualized stimulation of the DAN, but not of the DMN.

CONCLUSIONS

Our findings suggest that individualization of stimulation sites might ensure reliability of the evoked TMS-response across visits. Furthermore, individualized stimulation sites appear to be of foremost importance in highly variable, high order task-positive networks, such as the DAN.

Application of pseudocontinuous arterial spin labeling perfusion imaging in children with autism spectrum disorders

Introduction

Pseudocontinuous Arterial Spin Labeling (pCASL) perfusion imaging allows non-invasive quantification of regional cerebral blood flow (CBF) as part of a multimodal magnetic resonance imaging (MRI) protocol. This study aimed to compare regional CBF in autism spectrum disorders (ASD) individuals with their age-matched typically developing (TD) children using pCASL perfusion imaging.

Materials and methods

This cross-sectional study enrolled 17 individuals with ASD and 13 TD children. All participants underwent pCASL examination on a 3.0 T MRI scanner. Children in two groups were assessed for clinical characteristics and developmental profiles using Autism Behavior Checklist (ABC) and Gesell development diagnosis scale (GDDS), respectively. We compared CBF in different cerebral regions of ASD and TD children. We also assessed the association between CBF and clinical characteristics/developmental profile.

Results

Compared with TD children, individuals with ASD demonstrated a reduction in CBF in the left frontal lobe, the bilateral parietal lobes, and the bilateral temporal lobes. Within the ASD group, CBF was significantly higher in the right parietal lobe than in the left side. Correlation analysis of behavior characteristics and CBF in different regions showed a positive correlation between body and object domain scores on the ABC and CBF of the bilateral occipital lobes, and separately, between language domain scores and CBF of the left frontal lobe. The score of the social and self-help domain was negatively correlated with the CBF of the left frontal lobe, the left parietal lobe, and the left temporal lobe.

Conclusion

Cerebral blood flow was found to be negatively correlated with scores in the social and self-help domain, and positively correlated with those in the body and object domain, indicating that CBF values are a potential MRI-based biomarker of disease severity in ASD patients. The findings may provide novel insight into the pathophysiological mechanisms of ASD.

Recent Technical Developments in ASL: A Review of the State of the Art

This review article provides an overview of a range of recent technical developments in advanced arterial spin labeling (ASL) methods that have been developed or adopted by the community since the publication of a previous ASL consensus paper by Alsop et al. It is part of a series of review/recommendation papers from the International Society for Magnetic Resonance in Medicine Perfusion Study Group. Here, we focus on advancements in readouts and trajectories, image reconstruction, noise reduction, partial volume correction, quantification of nonperfusion parameters, fMRI, fingerprinting, vessel selective ASL, angiography, deep learning, and ultrahigh field ASL. We aim to provide a high level of understanding of these new approaches and some guidance for their implementation, with the goal of facilitating the adoption of such advances by research groups and by MRI vendors. Topics outside the scope of this article that are reviewed at length in separate articles include velocity selective ASL, multiple-timepoint ASL, body ASL, and clinical ASL recommendations.

Altered Coupling Between Cerebral Blood Flow and Voxel-Mirrored Homotopic Connectivity Affects Stroke-Induced Speech Comprehension Deficits

The neurophysiological basis of the association between interhemispheric connectivity and speech comprehension processing remains unclear. This prospective study examined regional cerebral blood flow (CBF), homotopic functional connectivity, and neurovascular coupling, and their effects on comprehension performance in post-stroke aphasia. Multimodal imaging data (including data from functional magnetic resonance imaging and arterial spin labeling imaging) of 19 patients with post-stroke aphasia and 22 healthy volunteers were collected. CBF, voxel-mirrored homotopic connectivity (VMHC), CBF-VMHC correlation, and CBF/VMHC ratio maps were calculated. Between-group comparisons were performed to identify neurovascular changes, and correlation analyses were conducted to examine their relationship with the comprehension domain. The correlation between CBF and VMHC of the global gray matter decreased in patients with post-stroke aphasia. The total speech comprehension score was significantly associated with VMHC in the peri-Wernicke area [posterior superior temporal sulcus (pSTS): r = 0.748, p = 0.001; rostroventral area 39: r = 0.641, p = 0.008]. The decreased CBF/VMHC ratio was also mainly associated with the peri-Wernicke temporoparietal areas. Additionally, a negative relationship between the mean CBF/VMHC ratio of the cingulate gyrus subregion and sentence-level comprehension was observed (r = −0.658, p = 0.006). These findings indicate the contribution of peri-Wernicke homotopic functional connectivity to speech comprehension and reveal that abnormal neurovascular coupling of the cingulate gyrus subregion may underly comprehension deficits in patients with post-stroke aphasia.

Effects of interventions on cerebral perfusion in the Alzheimer's disease spectrum: A systematic review

Cerebral perfusion dysfunctions are seen in the early stages of Alzheimer's disease (AD). We systematically reviewed the literature to investigate the effect of pharmacological and non-pharmacological interventions on cerebral hemodynamics in randomized controlled trials involving AD patients or Mild Cognitive Impairment (MCI) due to AD. Studies involving other dementia types were excluded. Data was searched in April 2021 on MEDLINE, Embase, and Web of Science. Risk of bias was assessed using Cochrane Risk of Bias Tool. A meta-synthesis was performed separating results from MCI and AD studies. 31 studies were included and involved 310 MCI and 792 CE patients. The MCI studies (n = 8) included physical, cognitive, dietary, and pharmacological interventions. The AD studies (n = 23) included pharmacological, physical interventions, and phytotherapy. Cerebral perfusion was assessed with PET, ASL, Doppler, fNIRS, DSC-MRI, Xe-CT, and SPECT. Randomization and allocation concealment methods and subject characteristics such as AD-onset, education, and ethnicity were missing in several papers. Positive effects on hemodynamics were seen in 75 % of the MCI studies, and 52 % of the AD studies. Inserting cerebral perfusion outcome measures, together with established AD biomarkers, is fundamental to target all disease mechanisms and understand the role of cerebral perfusion in AD.

Multivariate Gaussian Copula Mutual Information to Estimate Functional Connectivity with Less Random Architecture

Recognition of a brain region’s interaction is an important field in neuroscience. Most studies use the Pearson correlation to find the interaction between the regions. According to the experimental evidence, there is a nonlinear dependence between the activities of different brain regions that is ignored by Pearson correlation as a linear measure. Typically, the average activity of each region is used as input because it is a univariate measure. This dimensional reduction, i.e., averaging, leads to a loss of spatial information across voxels within the region. In this study, we propose using an information-theoretic measure, multivariate mutual information (mvMI), as a nonlinear dependence to find the interaction between regions. This measure, which has been recently proposed, simplifies the mutual information calculation complexity using the Gaussian copula. Using simulated data, we show that the using this measure overcomes the mentioned limitations. Additionally using the real resting-state fMRI data, we compare the level of significance and randomness of graphs constructed using different methods. Our results indicate that the proposed method estimates the functional connectivity more significantly and leads to a smaller number of random connections than the common measure, Pearson correlation. Moreover, we find that the similarity of the estimated functional networks of the individuals is higher when the proposed method is used.

Comparison of test–retest reliability of BOLD and pCASL fMRI in a two-center study

Background

The establishment of test–retest reliability and reproducibility (TRR) is an important part of validating any research tool, including functional magnetic resonance imaging (fMRI). The primary objective of this study is to investigate the reliability of pseudo-Continuous Arterial Spin Labeling (pCASL) and Blood Oxygen Level Dependent (BOLD) fMRI data acquired across two different scanners in a sample of healthy adults. While single site/single scanner studies have shown acceptable repeatability, TRR of both in a practical multisite study occurring in two facilities spread out across the country with weeks to months between scans is critically needed.

Methods

Ten subjects were imaged with similar 3 T MRI scanners at the University of Pittsburgh and Massachusetts General Hospital. Finger-tapping and Resting-state data were acquired for both techniques. Analysis of the resting state data for functional connectivity was performed with the Functional Connectivity Toolbox, while analysis of the finger tapping data was accomplished with FSL. pCASL Blood flow data was generated using AST Toolbox. Activated areas and networks were identified via pre-defined atlases and dual-regression techniques. Analysis for TRR was conducted by comparing pCASL and BOLD images in terms of Intraclass correlation coefficients, Dice Similarity Coefficients, and repeated measures ANOVA.

Results

Both BOLD and pCASL scans showed strong activation and correlation between the two locations for the finger tapping tasks. Functional connectivity analyses identified elements of the default mode network in all resting scans at both locations. Multivariate repeated measures ANOVA showed significant variability between subjects, but no significant variability for location. Global CBF was very similar between the two scanning locations, and repeated measures ANOVA showed no significant differences between the two scanning locations.

Conclusions

The results of this study show that when similar scanner hardware and software is coupled with identical data analysis protocols, consistent and reproducible functional brain images can be acquired across sites. The variability seen in the activation maps is greater for pCASL versus BOLD images, as expected, however groups maps are remarkably similar despite the low number of subjects. This demonstrates that multi-site fMRI studies of task-based and resting state brain activity is feasible.

The effect of acquisition duration on cerebral blood flow-based resting-state functional connectivity

Resting-state functional connectivity (rs-FC) is widely used to examine the functional architecture of the brain, and the blood-oxygenation-level-dependent (BOLD) signal is often utilized for determining rs-FC. However, the BOLD signal is susceptible to various factors that have less influence on the cerebral blood flow (CBF). Therefore, CBF could comprise an alternative for determining rs-FC. Since acquisition duration is one of the essential parameters for obtaining reliable rs-FC, we investigated the effect of acquisition duration on CBF-based rs-FC to examine the reliability of CBF-based rs-FC. Nineteen participants underwent CBF scanning for a total duration of 50 min. Variance of CBF-based rs-FC within the whole brain and 13 large-scale brain networks at various acquisition durations was compared to that with a 50-min duration using the Levene's test. Variance of CBF-based rs-FC at any durations did not differ from that at a 50-min duration (p > .05). Regarding variance of rs-FC within each large-scale brain network, the acquisition duration required to obtain reliable estimates of CBF-based rs-FC was shorter than 10 min and varied across large-scale brain networks. Altogether, an acquisition duration of at least 10 min is required to obtain reliable CBF-based rs-FC. These results indicate that CBF-based resting-state functional magnetic resonance imaging (rs-fMRI) with more than 10 min of total acquisition duration could be an alternative method to BOLD-based rs-fMRI to obtain reliable rs-FC.

Brain networks in migraine with and without aura: An exploratory arterial spin labeling MRI study

OBJECTIVES

The aim of this exploratory study was to investigate the underlying pathomechanisms of migraine with aura (MA) and migraine without aura (MO) in the interictal phase using a connectivity analysis.

METHODS

We prospectively enrolled patients who were newly diagnosed with migraine. All patients underwent brain MRI, including diffusion tensor imaging and arterial spin labeling perfusion MRI. We analyzed the differences between patients with MA and those with MO in structural connectivity based on diffusion tensor imaging and functional connectivity based on arterial spin labeling perfusion MRI using a graph theoretical analysis.

RESULTS

We enrolled 58 patients with migraine (11 patients with MA and 47 patients with MO). There were no differences between patients with MA and those with MO in the network measures of global structural connectivity. However, differences in global functional connectivity were found between the two groups. The assortative coefficient was lower in patients with MA than in those with MO (-0.050 vs. -0.012, p = .017). There were no differences in local structural and functional connectivity between patients with MA and those with MO.

CONCLUSION

We found differences in global functional connectivity between patients with MO and those with MA. The study of MA and MO using a connectivity analysis may shed light on migraine pathophysiology. We suggest it is worthwhile to investigate if changes in functional connectivity may serve as novel biomarkers in MA. In this regard, ASL MRI appears to be valuable in the context of network analysis, but further studies are needed to confirm our findings.

Laminar perfusion imaging with zoomed arterial spin labeling at 7 Tesla

Laminar fMRI based on BOLD and CBV contrast at ultrahigh magnetic fields has been applied for studying the dynamics of mesoscopic brain networks. However, the quantitative interpretations of BOLD/CBV fMRI results are confounded by different baseline physiology across cortical layers. Here we introduce a novel 3D zoomed pseudo-continuous arterial spin labeling (pCASL) technique at 7T that offers the capability for quantitative measurements of laminar cerebral blood flow (CBF) both at rest and during task activation with high spatial specificity and sensitivity. We found arterial transit time in superficial layers is ∼100 ms shorter than in middle/deep layers revealing the time course of labeled blood flowing from pial arteries to downstream microvasculature. Resting state CBF peaked in the middle layers which is highly consistent with microvascular density measured from human cortex specimens. Finger tapping induced a robust two-peak laminar profile of CBF increases in the superficial (somatosensory and premotor input) and deep (spinal output) layers of M1, while finger brushing task induced a weaker CBF increase in superficial layers (somatosensory input). This observation is highly consistent with reported laminar profiles of CBV activation on M1. We further demonstrated that visuospatial attention induced a predominant CBF increase in deep layers and a smaller CBF increase on top of the lower baseline CBF in superficial layers of V1 (feedback cortical input), while stimulus driven activity peaked in the middle layers (feedforward thalamic input). With the capability for quantitative CBF measurements both at baseline and during task activation, high-resolution ASL perfusion fMRI at 7T provides an important tool for in vivo assessment of neurovascular function and metabolic activities of neural circuits across cortical layers.

Cerebral Blood Flow Difference Between Acute and Chronic Tinnitus Perception: A Perfusion Functional Magnetic Resonance Imaging Study

Purpose: The central nervous mechanism of acute tinnitus is different from that of chronic tinnitus, which may be related to the difference of cerebral blood flow (CBF) perfusion in certain regions. To verify this conjecture, we used arterial spin labeling (ASL) perfusion magnetic resonance imaging (MRI) in this study to compare the CBF alterations of patients with acute and chronic tinnitus. Methods: The current study included patients with chronic tinnitus (n = 35), acute tinnitus (n = 30), and healthy controls (n = 40) who were age-, sex-, and education-matched. All participants underwent MRI scanning and then ASL images were obtained to measure CBF of the entire brain and analyze the differences between groups as well as the correlations with tinnitus characteristics. Results: The chronic tinnitus group showed increased z-CBF in the right superior temporal gyrus (STG) and superior frontal gyrus (SFG) when compared with the acute tinnitus patients. Further connectivity analysis found enhanced CBF connectivity between the right STG and fusiform gyrus (FG), the right SFG and left middle occipital gyrus (MOG), as well as the right parahippocampal gyrus (PHG). Moreover, in the chronic tinnitus group, the tinnitus handicap questionnaire (THQ) score was positively correlated with the normalized z-CBF of right STG (r = 0.440, p = 0.013). Conclusion: Our results confirmed that the CBF changes in some brain regions were different between acute and chronic tinnitus patients, which was correlated with certain tinnitus characteristics. This is of great value to further research on chronicity of tinnitus, and ASL has a promising application in the measurement of CBF.

Advances in resting state fMRI acquisitions for functional connectomics

Resting state functional magnetic resonance imaging (rs-fMRI) is based on spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal, which occur simultaneously in different brain regions, without the subject performing an explicit task. The low-frequency oscillations of the rs-fMRI signal demonstrate an intrinsic spatiotemporal organization in the brain (brain networks) that may relate to the underlying neural activity. In this review article, we briefly describe the current acquisition techniques for rs-fMRI data, from the most common approaches for resting state acquisition strategies, to more recent investigations with dedicated hardware and ultra-high fields. Specific sequences that allow very fast acquisitions, or multiple echoes, are discussed next. We then consider how acquisition methods weighted towards specific parts of the BOLD signal, like the Cerebral Blood Flow (CBF) or Volume (CBV), can provide more spatially specific network information. These approaches are being developed alongside the commonly used BOLD-weighted acquisitions. Finally, specific applications of rs-fMRI to challenging regions such as the laminae in the neocortex, and the networks within the large areas of subcortical white matter regions are discussed. We finish the review with recommendations for acquisition strategies for a range of typical applications of resting state fMRI.

Decomposition of individual-specific and individual-shared components from resting-state functional connectivity using a multi-task machine learning method

Resting-state functional connectivity (RSFC) can be used for mapping large-scale human brain networks during rest. There is considerable interest in distinguishing the individual-shared and individual-specific components in RSFC for the better identification of individuals and prediction of behavior. Therefore, we propose a multi-task learning based sparse convex alternating structure optimization (MTL-sCASO) method to decompose RSFC into individual-specific connectivity and individual-shared connectivity. We used synthetic data to validate the efficacy of the MTL-sCASO method. In addition, we verified that individual-specific connectivity achieves higher identification rates than the Pearson correlation (PC) method, and the individual-specific components observed in 886 individuals from the Human Connectome Project (HCP) examined in two sessions over two consecutive days might serve as individual fingerprints. Individual-specific connectivity has low inter-subject similarity (-0.005±0.023), while individual-shared connectivity has high inter-subject similarity (0.822±0.061). We also determined the anatomical locations (region or subsystem) related to individual attributes and common features. We find that individual-specific connectivity exhibits low degree centrality in the sensorimotor processing system but high degree centrality in the control system. Importantly, the individual-specific connectivity estimated by the MTL-sCASO method accurately predicts behavioral scores (improved by 9.4% compared to the PC method) in the cognitive dimension. The decomposition of individual-specific and individual-shared components from RSFC provides a new approach for tracing individual traits and group analysis using functional brain networks.

Validation of cerebral blood flow connectivity as imaging prognostic biomarker on subcortical stroke

Stroke is a major cause of vascular cognitive dysfunction, such as memory impairment. We aimed to explore the neural substrates underlying verbal memory impairment in subcortical stroke patients by the methods of voxel‐wise cerebral blood flow (CBF) and the functional covariance network (FCN). Sixty patients with chronic subcortical stroke and 60 normal controls (NCs) were recruited into this study. We used a three‐dimensional pseudo‐continuous arterial spin‐labeling imaging to measure alterations in CBF and FCNs. We mapped the overall CBF alterations in a voxel‐wise manner and compared CBF measurements using a two‐sample t test. Correlations between CBF and verbal memory were also investigated. Subsequently, we constructed FCNs by calculating the correlation between specific regions and all other voxels of a whole brain, separately within the two groups. Thereafter, by comparing differences of the FCN patterns between the patient and NC groups, we investigated the connection alterations within the FCN maps. The stroke patients showed verbal short‐term memory (VSTM) deficits compared to NCs. The patients exhibited decreased CBF in the ipsilesional insula and ventral sensorimotor network, and increased CBF in contralesional frontal cortical and subcortical regions (putamen and thalamus). Meanwhile, the CBF in the ipsilesional insula was positively correlated, and the contralesional frontal cortical was negativity correlated, with VSTM scores. Moreover we found that stroke patients exhibited disordered connection within FCNs compared to NCs. The study suggests that the underlying imaging biomarker of VSTM impairment in patients with subcortical stroke was associated with disconnection of the frontal lobe network.

Mapping the orbitofrontal cortex using temporal fluctuations in cerebral blood flow

INTRODUCTION

The orbitofrontal cortex (OFC) is involved in diverse cognitive and behavioral processes including incentive valuation, decision-making, and reinforcement learning. Anatomic and cytoarchitectonic studies divide the OFC along both medial-lateral and rostral-caudal axes. OFC regions diverge in structure and function, assessed in vivo using white matter tractography and blood oxygenation level-dependent (BOLD) MRI, respectively. However, interpretation of T₂ *-weighted BOLD is limited by susceptibility artifacts in the inferior frontal lobes, with the spatial pattern of these artifacts frequently assuming the geometry of OFC organization. Here, we utilize a novel perfusion-weighted arterial spin labeling (ASL) functional connectivity approach, which is minimally susceptibility-weighted, to test the hypothesis that OFC topology reflects correlated temporal hemodynamic activity.

METHODS

In healthy participants (n = 20; age = 29.5 ± 7.3), 3D ASL scans were acquired (TR/TE = 3,900/13 ms; spatial resolution = 3.8 mm isotropic). To evaluate reproducibility, follow-up scanning on a separate day was performed on a participant subset (n = 8). ASL-based connectivity was modeled for gray matter OFC voxels, and k-means clustering (k = 2-8) applied to correlation statistics.

RESULTS

These approaches revealed both medial-lateral and rostral-caudal OFC divisions, confirming our hypothesis. Longitudinal reproducibility testing revealed 84% voxel clustering agreement between sessions for the k = 2 solution.

CONCLUSION

To our knowledge, this constitutes the first in vivo cortical parcellation based on perfusion fluctuations. Our approach confirms functional OFC subdivisions predicted from anatomy using a less susceptibility-sensitive method than the conventional approach.

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.

Brain network dynamics fingerprints are resilient to data heterogeneity

CONTEXT

Large multi-site neuroimaging datasets have significantly advanced our quest to understand brain-behavior relationships and to develop biomarkers of psychiatric and neurodegenerative disorders. Yet, such data collections come at a cost, as the inevitable differences across samples may lead to biased or erroneous conclusions.

OBJECTIVE

We aim to validate the estimation of individual brain network dynamics fingerprints and appraise sources of variability in large resting-state functional magnetic resonance imaging (rs-fMRI) datasets by providing a novel point of view based on data-driven dynamical models.

APPROACH

Previous work has investigated this critical issue in terms of effects on static measures, such as functional connectivity and brain parcellations. Here, we utilize dynamical models (Hidden Markov models - HMM) to examine how diverse scanning factors in multi-site fMRI recordings affect our ability to infer the brain's spatiotemporal wandering between large-scale networks of activity. Specifically, we leverage a stable HMM trained on the Human Connectome Project (homogeneous) dataset, which we then apply to an heterogeneous dataset of traveling subjects scanned under a multitude of conditions.

MAIN RESULTS

Building upon this premise, we first replicate previous work on the emergence of non-random sequences of brain states. We next highlight how these time-varying brain activity patterns are robust subject-specific fingerprints. Finally, we suggest these fingerprints may be used to assess which scanning factors induce high variability in the data.

SIGNIFICANCE

These results demonstrate that we can i) use large scale dataset to train models that can be then used to interrogate subject-specific data, ii) recover the unique trajectories of brain activity changes in each individual, but also iii) urge caution as our ability to infer such patterns is affected by how, where and when we do so.

Consistent Cerebral Blood Flow Covariance Networks across Healthy Individuals and Their Similarity with Resting State Networks and Vascular Territories

Cerebral blood flow (CBF) represents the local blood supply to the brain, and it can be considered a proxy for neuronal activation. Independent component analysis (ICA) can be applied to CBF maps to derive patterns of spatial covariance across subjects. In the present study, we aimed to assess the consistency of the independent components derived from CBF maps (CBF-ICs) across a cohort of 92 healthy individuals. Moreover, we evaluated the spatial similarity of CBF-ICs with respect to resting state networks (RSNs) and vascular territories (VTs). The data were acquired on a 1.5 T scanner using arterial spin labeling (ASL) and resting state functional magnetic resonance imaging. Similarity was assessed considering the entire ASL dataset. Consistency was evaluated by splitting the dataset into subsamples according to three different criteria: (1) random split of age and sex-matched subjects, (2) elderly vs. young, and (3) males vs. females. After standard preprocessing, ICA was performed. Both consistency and similarity were assessed by visually comparing the CBF-ICs. Then, the degree of spatial overlap was quantified with Dice Similarity Coefficient (DSC). Frontal, left, and right occipital, cerebellar, and thalamic CBF-ICs were consistently identified among the subsamples, independently of age and sex, with fair to moderate overlap (0.2 < DSC ≤ 0.6). These regions are functional hubs, and their involvement in many neurodegenerative pathologies has been observed. As slight to moderate overlap (0.2< DSC < 0.5) was observed between CBF-ICs and some RSNs and VTs, CBF-ICs may mirror a combination of both functional and vascular brain properties.

Aberrant resting-state cerebral blood flow and its connectivity in primary dysmenorrhea on arterial spin labeling MRI

PURPOSE

This study aimed to clarify the resting-state cerebral blood flow alteration patterns induced by primary dysmenorrhea, investigate the relationships between cerebral blood flow alterations and clinical parameters of patients with primary dysmenorrhea, and explore whether brain regions with abnormal cerebral blood flow also feature functional connectivity changes.

METHODS

Arterial spin labeling imaging and clinical parameters were acquired in 42 patients with primary dysmenorrhea and 41 healthy controls during their menstrual phases. Differences in cerebral blood flow were compared between the two groups, and the clusters with significant group differences were selected as the regions of interest for further statistical analyses.

RESULTS

Compared to healthy controls, patients with primary dysmenorrhea exhibited increased cerebral blood flow in the bilateral precuneus, left posterior cingulate cortex, and right rolandic operculum. Among patients with primary dysmenorrhea, we identified a negative correlation between the cerebral blood flow in the right rolandic operculum and the visual analogue score for anxiety, and greater correlation between the functional connectivity in the precuneus/posterior cingulate cortex and the right middle cingulate cortex, and between the right rolandic operculum and the left inferior parietal lobule and the bilateral postcentral gyrus.

DISCUSSION

Cerebral blood flow abnormalities associated with primary dysmenorrhea were mainly concentrated in the areas comprising the default mode network in primary dysmenorrhea patients, which could be involved in the central mechanism of primary dysmenorrhea. Cerebral blood flow alteration in the rolandic operculum may underlie an anxiety-induced compulsive tendency in patients with primary dysmenorrhea. Investigating the enhanced connectivity among various pain-related brain regions could improve understanding of the onset and development of primary dysmenorrhea.

Discovery and replication of cerebral blood flow differences in major depressive disorder

Major depressive disorder (MDD) is a serious, heterogeneous disorder accompanied by brain-related changes, many of which are still to be discovered or refined. Arterial spin labeling (ASL) is a neuroimaging technique used to measure cerebral blood flow (CBF; perfusion) to understand brain function and detect differences among groups. CBF differences have been detected in MDD, and may reveal biosignatures of disease-state. The current work aimed to discover and replicate differences in CBF between MDD participants and healthy controls (HC) as part of the EMBARC study. Participants underwent neuroimaging at baseline, prior to starting study medication, to investigate biosignatures in MDD. Relative CBF (rCBF) was calculated and compared between 106 MDD and 36 HC EMBARC participants (whole-brain Discovery); and 58 MDD EMBARC participants and 58 HC from the DLBS study (region-of-interest Replication). Both analyses revealed reduced rCBF in the right parahippocampus, thalamus, fusiform and middle temporal gyri, as well as the left and right insula, for those with MDD relative to HC. Both samples also revealed increased rCBF in MDD relative to HC in both the left and right inferior parietal lobule, including the supramarginal and angular gyri. Cingulate and prefrontal regions did not fully replicate. Lastly, significant associations were detected between rCBF in replicated regions and clinical measures of MDD chronicity. These results (1) provide reliable evidence for ASL in detecting differences in perfusion for multiple brain regions thought to be important in MDD, and (2) highlight the potential role of using perfusion as a biosignature of MDD.

Associations between cerebral blood flow and structural and functional brain imaging measures in individuals with neuropsychologically defined mild cognitive impairment

Reduced cerebral blood flow (CBF), an indicator of neurovascular processes and metabolic demands, is a common finding in Alzheimer's disease. However, little is known about what contributes to CBF deficits in individuals with mild cognitive impairment (MCI). We examine regional CBF differences in 17 MCI compared with 21 age-matched cognitively healthy older adults. Next, we examined associations between CBF, white matter lesion (WML) volume, amplitude of low-frequency fluctuations, and cortical thickness to better understand whether altered CBF was detectable before other markers and the potential mechanistic underpinnings of CBF deficits in MCI. MCI had significantly reduced CBF, whereas cortical thickness and amplitude of low-frequency fluctuation were not affected. Reduced CBF was associated with the WML volume but not associated with other measures. Given the presumed vascular etiology of WML and relative worsening of vascular health in MCI, it may suggest CBF deficits result from early vascular as opposed to metabolic deficits in MCI. These findings may support vascular mechanisms as an underlying component of cognitive impairment.

Detecting resting-state brain activity using OEF-weighted imaging

Traditional resting-state functional magnetic resonance imaging (fMRI) is mainly based on the blood oxygenation level-dependent (BOLD) contrast. The oxygen extraction fraction (OEF) represents an important parameter of brain metabolism and is a key biomarker of tissue viability, detecting the ratio of oxygen utilization to oxygen delivery. Investigating spontaneous fluctuations in the OEF-weighted signal is crucial for understanding the underlying mechanism of brain activity because of the immense energy budget during the resting state. However, due to the poor temporal resolution of OEF mapping, no studies have reported using OEF contrast to assess resting-state brain activity. In this fMRI study, we recorded brain OEF-weighted fluctuations for 10 min in healthy volunteers across two scanning visits, using our recently developed pulse sequence that can acquire whole-brain voxel-wise OEF-weighted signals with a temporal resolution of 3 s. Using both group-independent component analysis and seed-based functional connectivity analysis, we robustly identified intrinsic brain networks, including the medial visual, lateral visual, auditory, default mode and bilateral executive control networks, using OEF contrast. Furthermore, we investigated the resting-state local characteristics of brain activity based on OEF-weighted signals using regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuations (fALFF). We demonstrated that the gray matter regions of the brain, especially those in the default mode network, showed higher ReHo and fALFF values with the OEF contrast. Moreover, voxel-wise test-retest reliability comparisons across the whole brain demonstrated that the reliability of resting-state brain activity based on the OEF contrast was moderate for the network indices and high for the local activity indices, especially for ReHo. Although the reliabilities of the OEF-based indices were generally lower than those based on BOLD, the reliability of OEF-ReHo was slightly higher than that of BOLD-ReHo, with a small effect size, which indicated that OEF-ReHo could be used as a reliable index for characterizing resting-state local brain activity as a complement to BOLD. In conclusion, OEF can be used as an effective contrast to study resting-state brain activity with a medium to high test-retest reliability.

Evaluation of the spatial variability in the major resting-state networks across human brain functional atlases

The human brain is intrinsically organized into resting‐state networks (RSNs). Currently, several human brain functional atlases are used to define the spatial constituents of these RSNs. However, there are significant concerns about interatlas variability. In response, we undertook a quantitative comparison of the five major RSNs (default mode [DMN], salience, central executive, sensorimotor, and visual networks) across currently available brain functional atlases (n = 6) in which we demonstrated that (a) similarity between atlases was modest and positively linked to the size of the sample used to construct them; (b) across atlases, spatial overlap among major RSNs ranged between 17 and 76% (mean = 39%), which resulted in variability in their functional connectivity; (c) lower order RSNs were generally spatially conserved across atlases; (d) among higher order RSNs, the DMN was the most conserved across atlases; and (e) voxel‐wise flexibility (i.e., the likelihood of a voxel to change network assignment across atlases) was high for subcortical regions and low for the sensory, motor and medial prefrontal cortices, and the precuneus. In order to facilitate RSN reproducibility in future studies, we provide a new freely available Consensual Atlas of REsting‐state Networks, based on the most reliable atlases.

Cerebral Blood Perfusion Predicts Response to Sertraline versus Placebo for Major Depressive Disorder in the EMBARC Trial

BACKGROUND

Major Depressive Disorder (MDD) has been associated with brain-related changes. However, biomarkers have yet to be defined that could "accurately" identify antidepressant-responsive patterns and reduce the trial-and-error process in treatment selection. Cerebral blood perfusion, as measured by Arterial Spin Labelling (ASL), has been used to understand resting-state brain function, detect abnormalities in MDD, and could serve as a marker for treatment selection. As part of a larger trial to identify predictors of treatment outcome, the current investigation aimed to identify perfusion predictors of treatment response in MDD.

METHODS

For this secondary analysis, participants include 231 individuals with MDD from the EMBARC study, a randomised, placebo-controlled trial investigating clinical, behavioural, and biological predictors of antidepressant response. Participants received sertraline (n = 114) or placebo (n = 117) and response was monitored for 8 weeks. Pre-treatment neuroimaging was completed, including ASL. A whole-brain, voxel-wise linear mixed-effects model was conducted to identify brain regions in which perfusion levels differentially predict (moderate) treatment response. Clinical effectiveness of perfusion moderators was investigated by composite moderator analysis and remission rates. Composite moderator analysis combined the effect of individual perfusion moderators and identified which contribute to sertraline or placebo as the "preferred" treatment. Remission rates were calculated for participants "accurately" treated based on the composite moderator (lucky) versus "inaccurately" treated (unlucky).

FINDINGS

Perfusion levels in multiple brain regions differentially predicted improvement with sertraline over placebo. Of these regions, perfusion in the putamen and anterior insula, inferior temporal gyrus, fusiform, parahippocampus, inferior parietal lobule, and orbital frontal gyrus contributed to sertraline response. Remission rates increased from 37% for all those who received sertraline to 53% for those who were lucky to have received it and sertraline was their perfusion-preferred treatment.

INTERPRETATION

This large study showed that perfusion patterns in brain regions involved with reward, salience, affective, and default mode processing moderate treatment response favouring sertraline over placebo. Accurately matching patients with defined perfusion patterns could significantly increase remission rates.

FUNDING

National Institute of Mental Health, the Hersh Foundation, and the Center for Depression Research and Clinical Care, Peter O'Donnell Brain Institute at UT Southwestern Medical Center.Trial Registration.Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMARC) Registration Number: NCT01407094 (https://clinicaltrials.gov/ct2/show/NCT01407094).

Test-retest reliability of cerebral blood flow for assessing brain function at rest and during a vigilance task

Arterial spin labeled (ASL) perfusion magnetic resonance imaging (MRI) is increasingly used to assess regional brain activity and cerebrovascular function in both healthy and clinical populations. ASL perfusion imaging provides a quantitative measure of regional brain activity by determining absolute cerebral blood flow (CBF) values at a resting state or during task performance. However, the comparative reliability of these ASL measures is not well characterized. It is also unclear whether the test-retest reliability of absolute CBF or task-induced CBF change measures would be comparable to the reliability of task performance. In this study, fifteen healthy participants were scanned three times in a strictly controlled in-laboratory study while at rest and during performing a simple and reliable psychomotor vigilance test (PVT). The reliability of absolute CBF and task-induced CBF changes was evaluated using the intraclass correlation coefficient (ICC) and compared to that of task performance. Absolute CBF showed excellent test-retest reliability across the three scans for both resting and PVT scans. The reliability of regional absolute CBF was comparable to that of behavioral measures of PVT performance, and was slightly higher during PVT scans as compared with resting scans. Task-induced regional CBF changes demonstrated only poor to moderate reliability across three scans. These findings suggest that absolute CBF measures are more reliable than task-induced CBF changes for characterizing regional brain function, especially for longitudinal and clinical studies.

Altered coupling of spontaneous brain activities and brain temperature in patients with adolescent-onset, first-episode, drug-naïve schizophrenia

PURPOSE

A recent study has reported that schizophrenia patients show an uncoupled association between intraventricular brain temperature (BT) and cerebral blood flow (CBF). CBF has been found to be closely coupled with spontaneous brain activities (SBAs) derived from resting-state BOLD fMRI metrics. Yet, it is unclear so far whether the relationship between the intraventricular BT and the SBAs may change in patients with adolescent-onset schizophrenia (AOS) compared with that in healthy controls (HCs).

METHODS

The present study recruited 28 first-episode, drug-naïve AOS patients and 22 matched HCs. We measured the temperature of the lateral ventricles (LV) using diffusion-weighted imaging thermometry and measured SBAs using both regional homogeneity and amplitude of low-frequency fluctuation methods. A nonparametric Wilcoxon rank sum test was used to detect the difference in intraventricular BT between AOS patients and HCs with LV volume, age, and sex as covariates. We also evaluated the relationship between the intraventricular BT and the SBAs using partial correlation analysis controlling for LV volume, age, and sex.

RESULTS

We found that HCs showed a significant negative correlation between the intraventricular BT and the local SBAs in the bilateral putamina and left superior temporal gyrus, while such a correlation was absent in AOS patients. Additionally, no significant difference between the two groups was found in the intraventricular BT.

CONCLUSION

These findings suggest that AOS patients may experience an uncoupling between intraventricular BT and SBAs in several schizophrenia-related brain areas, which may be associated with the altered relationships among intraventricular BT, CBF, and metabolism.

Arterial Spin Labeling Reveals Disrupted Brain Networks and Functional Connectivity in Drug-Resistant Temporal Epilepsy

Resting-state networks (RSNs) and functional connectivity (FC) have been increasingly exploited for mapping brain activity and identifying abnormalities in pathologies, including epilepsy. The majority of studies currently available are based on blood-oxygenation-level-dependent (BOLD) contrast in combination with either independent component analysis (ICA) or pairwise region of interest (ROI) correlations. Despite its success, this approach has several shortcomings as BOLD is only an indirect and non-quantitative measure of brain activity. Conversely, promising results have recently been achieved by arterial spin labeling (ASL) MRI, primarily developed to quantify brain perfusion. However, the wide application of ASL-based FC has been hampered by its complexity and relatively low robustness to noise, leaving several aspects of this approach still largely unexplored. In this study, we firstly aimed at evaluating the effect of noise reduction on spatio-temporal ASL analyses and quantifying the impact of two ad-hoc processing pipelines (basic and advanced) on connectivity measures. Once the optimal strategy had been defined, we investigated the applicability of ASL for connectivity mapping in patients with drug-resistant temporal epilepsy vs. controls (10 per group), aiming at revealing between-group voxel-wise differences in each RSN and ROI-wise FC changes. We first found ASL was able to identify the main network (DMN) along with all the others generally detected with BOLD but never previously reported from ASL. For all RSNs, ICA-based denoising (advanced pipeline) allowed to increase their similarity with the corresponding BOLD template. ASL-based RSNs were visibly consistent with literature findings; however, group differences could be identified in the structure of some networks. Indeed, statistics revealed areas of significant FC decrease in patients within different RSNs, such as DMN and cerebellum (CER), while significant increases were found in some cases, such as the visual networks. Finally, the ROI-based analyses identified several inter-hemispheric dysfunctional links (controls > patients) mainly between areas belonging to the DMN, right-left thalamus and right-left temporal lobe. Conversely, fewer connections, predominantly intra-hemispheric, showed the opposite pattern (controls < patients). All these elements provide novel insights into the pathological modulations characterizing a "network disease" as epilepsy, shading light on the importance of perfusion-based approaches for identifying the disrupted areas and communications between brain regions.

Mesolimbic Dopamine Function Is Related to Salience Network Connectivity: An Integrative Positron Emission Tomography and Magnetic Resonance Study

BACKGROUND

A wide range of neuropsychiatric disorders, from schizophrenia to drug addiction, involve abnormalities in both the mesolimbic dopamine system and the cortical salience network. Both systems play a key role in the detection of behaviorally relevant environmental stimuli. Although anatomical overlap exists, the functional relationship between these systems remains unknown. Preclinical research has suggested that the firing of mesolimbic dopamine neurons may activate nodes of the salience network, but in vivo human research is required given the species-specific nature of this network.

METHODS

We employed positron emission tomography to measure both dopamine release capacity (using the D2/3 receptor ligand 11C-PHNO, n = 23) and dopamine synthesis capacity (using 18F-DOPA, n = 21) within the ventral striatum. Resting-state functional magnetic resonance imaging was also undertaken in the same individuals to investigate salience network functional connectivity. A graph theoretical approach was used to characterize the relationship between dopamine measures and network connectivity.

RESULTS

Dopamine synthesis capacity was associated with greater salience network connectivity, and this relationship was particularly apparent for brain regions that act as information-processing hubs. In contrast, dopamine release capacity was associated with weaker salience network connectivity. There was no relationship between dopamine measures and visual and sensorimotor networks, indicating specificity of the findings.

CONCLUSIONS

Our findings demonstrate a close relationship between the salience network and mesolimbic dopamine system, and they are relevant to neuropsychiatric illnesses in which aberrant functioning of both systems has been observed.

Validations of apomorphine-induced BOLD activation correlations in hemiparkinsonian rhesus macaques

Identification of Parkinson's disease at the earliest possible stage of the disease may provide the best opportunity for the use of disease modifying treatments. However, diagnosing the disease during the pre-symptomatic period remains an unmet goal. To that end, we used pharmacological MRI (phMRI) to assess the function of the cortico-basal ganglia circuit in a non-human primate model of dopamine deficiency to determine the possible relationships between phMRI signals with behavioral, neurochemical, and histological measurements. Animals with unilateral treatments with the neurotoxin, 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), that expressed stable, long-term hemiparkinsonism were challenged with the dopaminergic receptor agonist, apomorphine, and structure-specific phMRI blood oxygen level-dependent (BOLD) activation responses were measured. Behavioral, histopathological, and neurochemical measurements were obtained and correlated with phMRI activation of structures of the cortico-basal ganglia system. Greater phMRI activations in the basal ganglia and cortex were associated with slower movement speed, decreased daytime activity, or more pronounced parkinsonian features. Animals showed decreased stimulus-evoked dopamine release in the putamen and substantia nigra pars compacta and lower basal glutamate levels in the motor cortex on the MPTP-lesioned hemisphere compared to the contralateral hemisphere. The altered neurochemistry was significantly correlated with phMRI signals in the motor cortex and putamen. Finally, greater phMRI activations in the caudate nucleus correlated with fewer tyrosine hydroxylase-positive (TH⁺) nigral cells and decreased TH⁺ fiber density in the putamen. These results reveal the correlation of phMRI signals with the severity of the motor deficits and pathophysiological changes in the cortico-basal ganglia circuit.

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Apomorphine in hemiparkinsonian animals can evoke changes in functional MRI signals.

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Cortico-basal ganglia activation correlates to behavior, neurochemistry, histology

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Pharmacological MRI has potential to be biomarker for Parkinson's disease.

Global fluctuations of cerebral blood flow indicate a global brain network independent of systemic factors

Global synchronization across specialized brain networks is a common feature of network models and in-vivo electrical measurements. Although the imaging of specialized brain networks with blood oxygenation sensitive resting state functional magnetic resonance imaging (rsfMRI) has enabled detailed study of regional networks, the study of globally correlated fluctuations with rsfMRI is confounded by spurious contributions to the global signal from systemic physiologic factors and other noise sources. Here we use an alternative rsfMRI method, arterial spin labeled perfusion MRI, to characterize global correlations and their relationship to correlations and anti-correlations between regional networks. Global fluctuations that cannot be explained by systemic factors dominate the fluctuations in cerebral blood flow. Power spectra of these fluctuations are band limited to below 0.05 Hz, similar to prior measurements of regional network fluctuations in the brain. Removal of these global fluctuations prior to measurement of regional networks reduces all regional network fluctuation amplitudes to below the global fluctuation amplitude and changes the strength and sign of inter network correlations. Our findings support large amplitude, globally synchronized activity across networks that require a reassessment of regional network amplitude and correlation measures.

Regional cerebral hypoperfusion after acute sleep deprivation: A STROBE-compliant study of arterial spin labeling fMRI

Previous neuroimaging studies have shown that functional changes occur after acute sleep deprivation, which suggest detrimental effects of a lack of sleep on the intrinsic functional architecture of the brain. We aimed to identify regional resting perfusion changes in subjects with acute sleep deprivation.Thirty-three healthy subjects with habitual good sleep participated in 36 hours (2 days and 1 night) of sleep deprivation and then underwent the attention network test and pseudo-continuous arterial spin labeling scanning. Regional cerebral blood flow was used to compare cerebral perfusion before and after sleep deprivation. Correlation analyses of regional perfusion changes and scores on the attention network test were performed.Compared with the baseline (n = 20) scans, the scans of subjects after sleep deprivation (n = 26) revealed a slower response time (549.99 milliseconds vs 603.36 milliseconds; t = -2.301; P = .028) and a significantly higher lapse rate (0.88% vs 22.85%; t = -2.977; P = .006). The sleep deprivation subjects showed lower cerebral blood flow (CBF) in the left parahippocampal gyrus/fusiform cortex (pHipp/Fus), right pHipp/Fus, and right prefrontal cortex (PFC) relative to the baseline subjects (Gaussian random field correction, voxel level P < .01, and cluster level P < .05). Although no significant relationships were observed between the altered regional CBF (rCBF) values and the attention network test scores, the receiver-operating characteristic and leave-one-out cross-validation analyses revealed that significant decreases in rCBF in the bilateral pHipp/Fus and right PFC could discriminate between sleep deprivation and good sleep status.We observed that rCBF was reduced after 36 hours (2 days and 1 night) of sleep deprivation. Our preliminary findings suggest an acute vulnerability to hypoperfusion due to lack of sleep.