Inflow effects on functional MRI

Glymphatic system dysfunction in adult ADHD: Relationship to cognitive performance

OBJECTIVES

While attention-deficit/hyperactivity disorder (ADHD) persists into adulthood, the relationship between glymphatic system function and cognitive performance in adult ADHD remains unclear. This study investigated the association between glymphatic system markers and cognitive outcomes in adults with ADHD.

METHODS

This case-control study includes 41 adults with ADHD and 108 age-matched healthy controls (HCs). Glymphatic function was evaluated using choroid plexus volume (CPV), diffusion tensor imaging along the perivascular space (DTI-ALPS) index and coupling between blood‑oxygen-level-dependent signals and cerebrospinal fluid signals (BOLD-CSF coupling). Cognitive performance was measured using standardized neuropsychological tests.

RESULTS

Compared with HCs, adults with ADHD exhibited significantly lower bilateral and whole-brain ALPS indices (P < 0.05). Although CPV was increased in the ADHD group, this difference did not reach statistical significance, and no significant differences were observed in BOLD-CSF coupling between the two groups. Furthermore, whole-brain ALPS indices were positively associated with visual memory performance (r = 0.422, P = 0.005), an effect that was more pronounced in the right hemisphere (r = 0.458, P = 0.002).

LIMITATIONS

The cross-sectional design limits causal inferences, and the effects of medication were not fully accounted for.

CONCLUSIONS

These findings identify an association between glymphatic dysfunction and cognitive impairment in adults with ADHD. The observed correlation suggests that alterations in glymphatic function may underlie ADHD-related cognitive deficits. Targeting these pathways could provide novel therapeutic opportunities in the management of adult ADHD.

Modeling dynamic inflow effects in fMRI to quantify cerebrospinal fluid flow

Cerebrospinal fluid (CSF) flow in the brain is tightly regulated and essential for brain health, and imaging techniques are needed to quantitatively establish the properties of this flow system. Flow-sensitive fMRI has recently emerged as a tool to measure large scale CSF flow dynamics with high sensitivity and temporal resolution; however, the measured signal is not quantitative. Here, we developed a dynamic model to simulate fMRI inflow signals based on time-varying flow velocities. We validated the model in both human and phantom data, and used it to identify important properties of the fMRI inflow signal that inform how the signal should be interpreted. Additionally, we developed a physics-based deep learning framework to invert the model, which enables direct estimation of velocity using fMRI inflow data. This work allows new quantitative information to be obtained from fMRI, which will enable neuroimaging researchers to take advantage of the high sensitivity, high temporal resolution, and wide availability of fMRI to obtain flow signals that are physically interpretable.

Total cerebral blood volume changes drive macroscopic cerebrospinal fluid flux in humans

In the mammalian brain, the directed motion of cerebrospinal fluid (CSF-flux) is instrumental in the distribution and removal of solutes. Changes in total cerebral blood volume (CBV) have been hypothesized to drive CSF-flux. We tested this hypothesis in two multimodal brain imaging experiments in healthy humans, in which we drove large changes in total CBV by neuronal burst-suppression under anesthesia or by transient global vasodilation in a hypercapnic challenge. We indirectly monitored CBV changes with a high temporal resolution based on associated changes in total brain volume by functional MRI (fMRI) and measured cerebral blood flow by arterial spin-labeling. Relating CBV-sensitive signals to fMRI-derived measures of macroscopic CSF flow across the basal cisternae, we demonstrate that increasing total CBV extrudes CSF from the skull and decreasing CBV allows its influx. Moreover, CSF largely stagnates when CBV is stable. Together, our results establish the direct coupling between total CBV changes and CSF-flux.

Test-retest reliability of coupling between cerebrospinal fluid flow and global brain activity after normal sleep and sleep deprivation

The glymphatic system (GS) plays a key role in maintaining brain homeostasis by clearing metabolic waste during sleep, with the coupling between global blood-oxygen-level-dependent (gBOLD) and cerebrospinal fluid (CSF) signals serving as a potential marker for glymphatic clearance function. However, the test-retest reliability and spatial heterogeneity of gBOLD-CSF coupling after different sleep conditions remain unclear. In this study, we assessed the test-retest reliability of gBOLD-CSF coupling following either normal sleep or total sleep deprivation (TSD) in 64 healthy adults under controlled laboratory conditions. The reliability was high after normal sleep (ICC = 0.763) but decreased following TSD (ICC = 0.581). Moreover, spatial heterogeneity was evident in participants with normal sleep, with lower-order networks (visual, somatomotor, and attention) showing higher ICC values compared to higher-order networks (default-mode, limbic, and frontoparietal). This spatial variation was less distinct in the TSD group. These results demonstrate the robustness of the gBOLD-CSF coupling method and emphasize the significance of considering sleep history in glymphatic function research.

Sex-specific age-related differences in cerebrospinal fluid clearance assessed by resting-state functional magnetic resonance imaging

Cerebrospinal fluid (CSF) flow may assist the clearance of brain wastes, such as amyloid-β (Aβ) and tau, and thus play an important role in aging and dementias. However, a lack of non-invasive tools to assess the CSF dynamics-related clearance in humans hindered the understanding of the relevant changes in healthy aging. The global infra-slow (<0.1 Hz) brain activity measured by the global mean resting-state fMRI signal (gBOLD) was recently found to be coupled by large CSF movements. This coupling has been found to correlate with various pathologies of Alzheimer's disease (AD), particularly Aβ pathology, linking it to waste clearance. Using resting-state fMRI data from a group of 719 healthy aging participants, we examined the sex-specific differences of the gBOLD-CSF coupling over a wide age range between 36-100 years of age. We found that this coupling index remains stable before around age 55 and then starts to decline afterward, particularly in females. Menopause may contribute to the accelerated decline in females.

Decoupling Between Brain Activity and Cerebrospinal Fluid Movement in Neurological Disorders

Recent research has identified a link between the global mean signal of resting-state functional MRI (fMRI) and macro-scale cerebrospinal fluid movement, indicating the potential link between this resting-state dynamic and brain waste clearance. Consistent with this notion, the strength of this coupling has been associated with multiple neurodegenerative disease pathologies, especially the build-up of toxic proteins. This article aimed to review the latest advancements in this research area, emphasizing studies on spontaneous global brain activity that is tightly linked to the global mean resting-state fMRI signal, and aimed to discuss potential mechanisms through which this activity and associated physiological modulations might affect brain waste clearance. The available evidence supports the presence of a highly organized global brain activity that is linked to arousal and memory systems. This global brain dynamic, along with its associated physiological modulations, has the potential to influence brain waste clearance through multiple pathways through multiple pathways. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 3.

Real-time quantification of in vivo cerebrospinal fluid velocity using the functional magnetic resonance imaging inflow effect

In vivo estimation of cerebrospinal fluid (CSF) velocity is crucial for understanding the glymphatic system and its potential role in neurodegenerative disorders such as Alzheimer's disease and Parkinson's disease. Current cardiac or respiratory-gated approaches, such as 4D flow magnetic resonance imaging (MRI), cannot capture CSF movement in real time because of limited temporal resolution and, in addition, deteriorate in accuracy at low fluid velocities. Other techniques like real-time phase-contrast-MRI or time-spatial labeling inversion pulse are not limited by temporal averaging but have limited availability, even in research settings. This study aims to quantify the inflow effect of dynamic CSF motion on functional MRI (fMRI) for in vivo, real-time measurement of CSF flow velocity. We considered linear and nonlinear models of velocity waveforms and empirically fit them to fMRI data from a controlled flow experiment. To assess the utility of this methodology in human data, CSF flow velocities were computed from fMRI data acquired in eight healthy volunteers. Breath-holding regimens were used to amplify CSF flow oscillations. Our experimental flow study revealed that CSF velocity is nonlinearly related to inflow effect-mediated signal increase and well estimated using an extension of a previous nonlinear framework. Using this relationship, we recovered velocity from in vivo fMRI signal, demonstrating the potential of our approach for estimating CSF flow velocity in the human brain. This novel method could serve as an alternative approach to quantifying slow flow velocities in real time, such as CSF flow in the ventricular system, thereby providing valuable insights into the glymphatic system's function and its implications for neurological disorders.

Submillimeter fMRI Acquisition Techniques for Detection of Laminar and Columnar Level Brain Activation

Since the first demonstration in the early 1990s, functional MRI (fMRI) has emerged as one of the most powerful, noninvasive neuroimaging tools to probe brain functions. Subsequently, fMRI techniques have advanced remarkably, enabling the acquisition of functional signals with a submillimeter voxel size. This innovation has opened the possibility of investigating subcortical neural activities with respect to the cortical depths or cortical columns. For this purpose, numerous previous works have endeavored to design suitable functional contrast mechanisms and dedicated imaging techniques. Depending on the choice of the functional contrast, functional signals can be detected with high sensitivity or with improved spatial specificity to the actual activation site, and the pertaining issues have been discussed in a number of earlier works. This review paper primarily aims to provide an overview of the subcortical fMRI techniques that allow the acquisition of functional signals with a submillimeter resolution. Here, the advantages and disadvantages of the imaging techniques will be described and compared. We also summarize supplementary imaging techniques that assist in the analysis of the subcortical brain activation for more accurate mapping with reduced geometric deformation. This review suggests that there is no single universally accepted method as the gold standard for subcortical fMRI. Instead, the functional contrast and the corresponding readout imaging technique should be carefully determined depending on the purpose of the study. Due to the technical limitations of current fMRI techniques, most subcortical fMRI studies have only targeted partial brain regions. As a future prospect, the spatiotemporal resolution of fMRI will be pushed to satisfy the community's need for a deeper understanding of whole-brain functions and the underlying connectivity in order to achieve the ultimate goal of a time-resolved and layer-specific spatial scale. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.

Real-time Quantification of in vivo cerebrospinal fluid velocity using fMRI inflow effect

In vivo estimation of cerebrospinal fluid (CSF) velocity is crucial for understanding the glymphatic system and its potential role in neurodegenerative disorders such as Alzheimer's disease and Parkinson's disease. Current cardiac or respiratory gated approaches, such as 4D flow MRI, cannot capture CSF movement in real time due to limited temporal resolution and in addition deteriorate in accuracy at low fluid velocities. Other techniques like real-time PC-MRI or time-spatial labeling inversion pulse are not limited by temporal averaging but have limited availability even in research settings. This study aims to quantify the inflow effect of dynamic CSF motion on functional magnetic resonance imaging (fMRI) for in vivo, real-time measurement of CSF flow velocity. We considered linear and nonlinear models of velocity waveforms and empirically fit them to fMRI data from a controlled flow experiment. To assess the utility of this methodology in human data, CSF flow velocities were computed from fMRI data acquired in eight healthy volunteers. Breath holding regimens were used to amplify CSF flow oscillations. Our experimental flow study revealed that CSF velocity is nonlinearly related to inflow effect-mediated signal increase and well estimated using an extension of a previous nonlinear framework. Using this relationship, we recovered velocity from in vivo fMRI signal, demonstrating the potential of our approach for estimating CSF flow velocity in the human brain. This novel method could serve as an alternative approach to quantifying slow flow velocities in real time, such as CSF flow in the ventricular system, thereby providing valuable insights into the glymphatic system's function and its implications for neurological disorders.

Regional Glymphatic Abnormality in Behavioral Variant Frontotemporal Dementia

OBJECTIVES

Glymphatic function has not yet been explored in behavioral variant frontotemporal dementia (bvFTD). The spatial correlation between regional glymphatic function and bvFTD remains unknown.

METHOD

A total of 74 patients with bvFTD and 67 age- and sex-matched healthy controls (HCs) were selected from discovery dataset and replication dataset. All participants underwent neuropsychological assessment. Glymphatic measures including choroid plexus (CP) volume, diffusion tensor imaging along the perivascular (DTI-ALPS) index, and coupling between blood-oxygen-level-dependent signals and cerebrospinal fluid signals (BOLD-CSF coupling), were compared between the two groups. Regional glymphatic function was evaluated by dividing DTI-ALPS and BOLD-CSF coupling into anterior, middle, and posterior regions. The bvFTD-related metabolic pattern was identified using spatial covariance analysis based on l8 F-FDG-PET.

RESULTS

Patients with bvFTD showed higher CP volume (p < 0.001); anterior and middle DTI-ALPS (p < 0.001); and weaker anterior BOLD-CSF coupling (p < 0.05) than HCs after controlling for cortical gray matter volume in both datasets. In bvFTD from the discovery dataset, the anterior DTI-ALPS was negatively associated with the expression of the bvFTD-related metabolic pattern (r = -0.52, p = 0.034) and positively related with regional standardized uptake value ratios of l8 F-FDG-PET in bvFTD-related brain regions (r range: 0.49 to 0.62, p range: 0.017 to 0.047). Anterior and middle glymphatic functions were related to global cognition and disease severity.

INTERPRETATION

Our findings reveal abnormal glymphatic function, especially in the anterior and middle regions of brain in bvFTD. Regional glymphatic dysfunction may contribute to the pathogenesis of bvFTD. ANN NEUROL 2023;94:442-456.

Reduced coupling of global brain function and cerebrospinal fluid dynamics in Parkinson's disease

Dysfunction of the glymphatic system, an intracranial clearance pathway that drains misfolded proteins, has been implicated in the onset of Parkinson's disease (PD). Recently, the coupling strength of global blood-oxygen-level-dependent (gBOLD) signals and cerebrospinal fluid (CSF) inflow dynamics have been suggested to be an indicator of glymphatic function. Using resting-state functional magnetic resonance imaging (MRI), we quantified gBOLD-CSF coupling strength as the cross-correlation between baseline gBOLD and CSF inflow signals to evaluate glymphatic function and its association with the clinical manifestations of PD. We found that gBOLD-CSF coupling in drug-naïve PD patients was significantly weaker than that in normal controls, but significantly stronger in patients less affected by sleep disturbances than in those more affected by sleep disturbances, based on the PD sleep scale. Furthermore, we collected longitudinal data from patients and found that baseline gBOLD-CSF coupling negatively correlated with the rate of change over time, but positively correlated with the rate of change in UPDRS-III scores. In conclusion, severe gBOLD-CSF decoupling in PD patients may reflect longitudinal motor impairment, thereby providing a potential marker of glymphatic dysfunction in PD.

Wide-spread brain activation and reduced CSF flow during avian REM sleep

Mammalian sleep has been implicated in maintaining a healthy extracellular environment in the brain. During wakefulness, neuronal activity leads to the accumulation of toxic proteins, which the glymphatic system is thought to clear by flushing cerebral spinal fluid (CSF) through the brain. In mice, this process occurs during non-rapid eye movement (NREM) sleep. In humans, ventricular CSF flow has also been shown to increase during NREM sleep, as visualized using functional magnetic resonance imaging (fMRI). The link between sleep and CSF flow has not been studied in birds before. Using fMRI of naturally sleeping pigeons, we show that REM sleep, a paradoxical state with wake-like brain activity, is accompanied by the activation of brain regions involved in processing visual information, including optic flow during flight. We further demonstrate that ventricular CSF flow increases during NREM sleep, relative to wakefulness, but drops sharply during REM sleep. Consequently, functions linked to brain activation during REM sleep might come at the expense of waste clearance during NREM sleep.

Cortical depth-dependent human fMRI of resting-state networks using EPIK

Introduction

Recent laminar-fMRI studies have substantially improved understanding of the evoked cortical responses in multiple sub-systems; in contrast, the laminar component of resting-state networks spread over the whole brain has been less studied due to technical limitations. Animal research strongly suggests that the supragranular layers of the cortex play a critical role in maintaining communication within the default mode network (DMN); however, whether this is true in this and other human cortical networks remains unclear.

Methods

Here, we used EPIK, which offers unprecedented coverage at sub-millimeter resolution, to investigate cortical broad resting-state dynamics with depth specificity in healthy volunteers.

Results

Our results suggest that human DMN connectivity is primarily supported by intermediate and superficial layers of the cortex, and furthermore, the preferred cortical depth used for communication can vary from one network to another. In addition, the laminar connectivity profile of some networks showed a tendency to change upon engagement in a motor task. In line with these connectivity changes, we observed that the amplitude of the low-frequency-fluctuations (ALFF), as well as the regional homogeneity (ReHo), exhibited a different laminar slope when subjects were either performing a task or were in a resting state (less variation among laminae, i.e., lower slope, during task performance compared to rest).

Discussion

The identification of varied laminar profiles concerning network connectivity, ALFF, and ReHo, observed across two brain states (task vs. rest) has major implications for the characterization of network-related diseases and suggests the potential diagnostic value of laminar fMRI in psychiatric disorders, e.g., to differentiate the cortical dynamics associated with disease stages linked, or not linked, to behavioral changes. The evaluation of laminar-fMRI across the brain encompasses computational challenges; nonetheless, it enables the investigation of a new dimension of the human neocortex, which may be key to understanding neurological disorders from a novel perspective.

Sex-specific age-related changes in glymphatic function assessed by resting-state functional magnetic resonance imaging

The glymphatic system that clears out brain wastes, such as amyloid-β (Aβ) and tau, through cerebrospinal fluid (CSF) flow may play an important role in aging and dementias. However, a lack of non-invasive tools to assess the glymphatic function in humans hindered the understanding of the glymphatic changes in healthy aging. The global infra-slow (<0.1 Hz) brain activity measured by the global mean resting-state fMRI signal (gBOLD) was recently found to be coupled by large CSF movements. This coupling has been used to measure the glymphatic process and found to correlate with various pathologies of Alzheimer's disease (AD), including Aβ pathology. Using resting-state fMRI data from a large group of 719 healthy aging participants, we examined the sex-specific changes of the gBOLD-CSF coupling, as a measure of glymphatic function, over a wide age range between 36-100 years old. We found that this coupling index remains stable before around age 55 and then starts to decline afterward, particularly in females. Menopause may contribute to the accelerated decline in females.

Ultra-slow fMRI fluctuations in the fourth ventricle as a marker of drowsiness

Wakefulness levels modulate estimates of functional connectivity (FC), and, if unaccounted for, can become a substantial confound in resting-state fMRI. Unfortunately, wakefulness is rarely monitored due to the need for additional concurrent recordings (e.g., eye tracking, EEG). Recent work has shown that strong fluctuations around 0.05Hz, hypothesized to be CSF inflow, appear in the fourth ventricle (FV) when subjects fall asleep, and that they correlate significantly with the global signal. The analysis of these fluctuations could provide an easy way to evaluate wakefulness in fMRI-only data and improve our understanding of FC during sleep. Here we evaluate this possibility using the 7T resting-state sample from the Human Connectome Project (HCP). Our results replicate the observation that fourth ventricle ultra-slow fluctuations (∼0.05Hz) with inflow-like characteristics (decreasing in intensity for successive slices) are present in scans during which subjects did not comply with instructions to keep their eyes open (i.e., drowsy scans). This is true despite the HCP data not being optimized for the detection of inflow-like effects. In addition, time-locked BOLD fluctuations of the same frequency could be detected in large portions of grey matter with a wide range of temporal delays and contribute in significant ways to our understanding of how FC changes during sleep. First, these ultra-slow fluctuations explain half of the increase in global signal that occurs during descent into sleep. Similarly, global shifts in FC between awake and sleep states are driven by changes in this slow frequency band. Second, they can influence estimates of inter-regional FC. For example, disconnection between frontal and posterior components of the Defulat Mode Network (DMN) typically reported during sleep were only detectable after regression of these ultra-slow fluctuations. Finally, we report that the temporal evolution of the power spectrum of these ultra-slow FV fluctuations can help us reproduce sample-level sleep patterns (e.g., a substantial number of subjects descending into sleep 3 minutes following scanning onset), partially rank scans according to overall drowsiness levels, and predict individual segments of elevated drowsiness (at 60 seconds resolution) with 71% accuracy.

Mapping oxidative metabolism in the human brain with calibrated fMRI in health and disease

Conventional functional MRI (fMRI) with blood-oxygenation level dependent (BOLD) contrast is an important tool for mapping human brain activity non-invasively. Recent interest in quantitative fMRI has renewed the importance of oxidative neuroenergetics as reflected by cerebral metabolic rate of oxygen consumption (CMR_O2) to support brain function. Dynamic CMR_O2 mapping by calibrated fMRI require multi-modal measurements of BOLD signal along with cerebral blood flow (CBF) and/or volume (CBV). In human subjects this "calibration" is typically performed using a gas mixture containing small amounts of carbon dioxide and/or oxygen-enriched medical air, which are thought to produce changes in CBF (and CBV) and BOLD signal with minimal or no CMR_O2 changes. However non-human studies have demonstrated that the "calibration" can also be achieved without gases, revealing good agreement between CMR_O2 changes and underlying neuronal activity (e.g., multi-unit activity and local field potential). Given the simpler set-up of gas-free calibrated fMRI, there is evidence of recent clinical applications for this less intrusive direction. This up-to-date review emphasizes technological advances for such translational gas-free calibrated fMRI experiments, also covering historical progression of the calibrated fMRI field that is impacting neurological and neurodegenerative investigations of the human brain.

Multi-echo balanced SSFP with a sequential phase-encoding order for functional MR imaging at 7T

PURPOSE

To develop a 2D multi-echo passband balanced SSFP (bSSFP) sequence using an echo-train readout with a sequential phase-encoding order (sequential multi-echo bSSFP), and evaluate its performance in fast functional brain imaging at 7 T.

METHODS

As images of sequential multi-echo bSSFP exhibit multiple ghosts due to periodic k-space modulations, a GRAPPA-based reconstruction method was proposed to eliminate ghosting artifacts. MRI experiments were performed to compare the image quality of multi-echo bSSFP and conventional single-echo bSSFP. Submillimeter-resolution fMRI using a checkerboard visual stimulus was conducted to compare the activation characteristics of multi-echo bSSFP, conventional single-echo bSSFP and standard gradient-echo EPI (GE-EPI).

RESULTS

A higher mean structural similarity index was found between images of single-echo bSSFP and multi-echo bSSFP with a shorter echo train length (ETL). Multi-echo bSSFP (ETL = 3) showed higher temporal SNR (tSNR) values than GRAPPA-accelerated single-echo bSSFP (R = 2). In submillimeter-resolution fMRI experiments, multi-echo bSSFP (ETL = 3) approached the imaging speed of GRAPPA-accelerated single-echo bSSFP (R = 2), but without tSNR penalty and reduced activation due to acceleration. The median t-value and the number of significantly activated voxels were comparable between GE-EPI and multi-echo bSSFP (ETL = 3) that provides virtually distortion-free functional images and inherits the activation patterns of conventional bSSFP.

CONCLUSION

Sequential multi-echo bSSFP (ETL = 3) is suitable for fast fMRI with submillimeter in-plane resolution, and offers an option to accelerate bSSFP imaging without tSNR penalty like parallel imaging.

Measurement of CSF pulsation from EPI-based human fMRI

It is recently discovered that the glymphatic system and meningeal lymphatic system are the primary routes for the clearance of brain waste products. The CSF flow is part of these systems, facilitating the clearance procedure. Nonetheless, the relationship between CSF flow and brain functional activity has been underexplored. To investigate CSF dynamics and functional brain activity simultaneously, recent studies have proposed a CSF inflow index measured on edge slices (CSFedge) of echo-planar imaging (EPI) based functional magnetic resonance imaging (fMRI), however, it lacks the quantitative aspect of the CSF pulsation. We proposed a new method for quantifying CSF pulsation (CSFpulse) based on an interslice CSF pulsation model in the 4^th ventricle of EPI-based fMRI. The proposed CSFpulse successfully detected the higher CSF flow during the resting state than the typical task states (visual and motor) (p<.05), which is consistent with previous studies based on phase contrast (PC) MRI and CSF volume MRI, while it was not detected in CSFedge based indices or baseline CSF signals in various regions of interest (ROIs). Moreover, CSFpulse demonstrated dynamic functional changes in CSF pulsation: it decreased during the activation-on blocks while it increased during the activation-off blocks. CSFpulse significantly correlated with stroke volume measured using PC MRI, a standard method for CSF pulsation quantification, under the same functional state, while CSFedge based indices or CSF ROIs showed no correlation with the PC MRI stroke volume. Lastly, the correlation of CSFpulse with global BOLD was weaker than that of CSFedge, suggesting that CSFpulse may reflect distinct CSF physiological information that is less affected by global BOLD effects. Based on these results, the proposed CSFpulse provides CSF pulsatility information more accurately in a quantitative manner than CSFedge based indices from the recent CSF studies or the conventional ROI-based analysis. In addition to the high correlation with PC MRI, CSFpulse is much faster than PC MRI and provides information of functional brain activations simultaneously, advantageous over PC MRI or CSF volume MRI. Accordingly, the suggested CSFpulse can be used for investigating intra-subject functional changes in BOLD and CSF pulsation simultaneously and inter-subject CSF pulsation variations based on conventional EPI-based fMRI, which warrants further investigation.

Whole-brain studies of spontaneous behavior in head-fixed rats enabled by zero echo time MB-SWIFT fMRI

Understanding the link between the brain activity and behavior is a key challenge in modern neuroscience. Behavioral neuroscience, however, lacks tools to record whole-brain activity in complex behavioral settings. Here we demonstrate that a novel Multi-Band SWeep Imaging with Fourier Transformation (MB-SWIFT) functional magnetic resonance imaging (fMRI) approach enables whole-brain studies in spontaneously behaving head-fixed rats. First, we show anatomically relevant functional parcellation. Second, we show sensory, motor, exploration, and stress-related brain activity in relevant networks during corresponding spontaneous behavior. Third, we show odor-induced activation of olfactory system with high correlation between the fMRI and behavioral responses. We conclude that the applied methodology enables novel behavioral study designs in rodents focusing on tasks, cognition, emotions, physical exercise, and social interaction. Importantly, novel zero echo time and large bandwidth approaches, such as MB-SWIFT, can be applied for human behavioral studies, allowing more freedom as body movement is dramatically less restricting factor.

A line through the brain: implementation of human line-scanning at 7T for ultra-high spatiotemporal resolution fMRI

Functional magnetic resonance imaging (fMRI) is a widely used tool in neuroscience to detect neurally evoked responses, e.g. the blood oxygenation level-dependent (BOLD) signal. Typically, BOLD fMRI has millimeter spatial resolution and temporal resolution of one to few seconds. To study the sub-millimeter structures and activity of the cortical gray matter, the field needs an fMRI method with high spatial and temporal resolution. Line-scanning fMRI achieves very high spatial resolution and high sampling rate, at the cost of a sacrifice in volume coverage. Here, we present a human line-scanning implementation on a 7T MRI system. First, we investigate the quality of the saturation pulses that suppress MR signal outside the line. Second, we established the best coil combination for reconstruction. Finally, we applied the line-scanning method in the occipital lobe during a visual stimulation task, showing BOLD responses along cortical depth, every 250 µm with a 200 ms repetition time (TR). We found a good correspondence of t-statistics values with 2D gradient-echo echo planar imaging (GE-EPI) BOLD fMRI data with the same temporal resolution and voxel volume (R = 0.6 ± 0.2). In summary, we demonstrate the feasibility of line-scanning in humans and this opens line-scanning fMRI for applications in cognitive and clinical neuroscience.

Decoupling of Global Brain Activity and Cerebrospinal Fluid Flow in Parkinson's Disease Cognitive Decline

BACKGROUND

Deposition and spreading of misfolded proteins (α-synuclein and tau) have been linked to Parkinson's disease cognitive dysfunction. The glymphatic system may play an important role in the clearance of these toxic proteins via cerebrospinal fluid (CSF) flow through perivascular and interstitial spaces. Recent studies discovered that sleep-dependent global brain activity is coupled to CSF flow, which may reflect glymphatic function.

OBJECTIVE

The objective of this current study was to determine if the decoupling of brain activity-CSF flow is linked to Parkinson's disease cognitive dysfunction.

METHODS

Functional and structural MRI data, clinical motor (Unified Parkinson's Disease Rating Scale), and cognitive (Montreal Cognitive Assessment [MoCA]) scores were collected from 60 Parkinson's disease and 58 control subjects. Parkinson's disease patients were subgrouped into those with mild cognitive impairment (MoCA < 26), n = 31, and those without mild cognitive impairment (MoCA ≥ 26), n = 29. The coupling strength between the resting-state global blood-oxygen-level-dependent signal and associated CSF flow was quantified, compared among groups, and associated with clinical and structural measurements.

RESULTS

Global blood-oxygen-level-dependent signal-CSF coupling decreased significantly (P < 0.006) in Parkinson's disease patients showing mild cognitive impairment, compared with those without mild cognitive impairment and controls. Reduced global blood-oxygen-level-dependent signal-CSF coupling was associated with decreased MoCA scores present in Parkinson's disease patients (P = 0.005) but not in controls (P = 0.65). Weaker global blood-oxygen-level-dependent signal-CSF coupling in Parkinson's disease patients also was associated with a thinner right entorhinal cortex (Spearman's correlation, -0.36; P = 0.012), an early structural change often seen in Alzheimer's disease.

CONCLUSIONS

The decoupling between global brain activity and associated CSF flow is related to Parkinson's disease cognitive impairment. © 2021 International Parkinson and Movement Disorder Society.

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

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

A novel method of quantifying hemodynamic delays to improve hemodynamic response, and CVR estimates in CO2 challenge fMRI

Elevated carbon dioxide (CO2) in breathing air is widely used as a vasoactive stimulus to assess cerebrovascular functions under hypercapnia (i.e., "stress test" for the brain). Blood-oxygen-level-dependent (BOLD) is a contrast mechanism used in functional magnetic resonance imaging (fMRI). BOLD is used to study CO2-induced cerebrovascular reactivity (CVR), which is defined as the voxel-wise percentage BOLD signal change per mmHg change in the arterial partial pressure of CO2 (PaCO2). Besides the CVR, two additional important parameters reflecting the cerebrovascular functions are the arrival time of arterial CO2 at each voxel, and the waveform of the local BOLD signal. In this study, we developed a novel analytical method to accurately calculate the arrival time of elevated CO2 at each voxel using the systemic low frequency oscillations (sLFO: 0.01-0.1 Hz) extracted from the CO2 challenge data. In addition, 26 candidate hemodynamic response functions (HRF) were used to quantitatively describe the temporal brain reactions to a CO2 stimulus. We demonstrated that our approach improved the traditional method by allowing us to accurately map three perfusion-related parameters: the relative arrival time of blood, the hemodynamic response function, and CVR during a CO2 challenge.

Postcontractile blood oxygenation level-dependent (BOLD) response in Duchenne muscular dystrophy

Duchenne muscular dystrophy (DMD) is characterized by a progressive replacement of muscle by fat and fibrous tissue, muscle weakness, and loss of functional abilities. Impaired vasodilatory and blood flow responses to muscle activation have also been observed in DMD and associated with mislocalization of neuronal nitric oxide synthase mu (nNOSμ) from the sarcolemma. The objective of this study was to determine whether the postcontractile blood oxygen level-dependent (BOLD) MRI response is impaired in DMD and correlated with established markers of disease severity in DMD, including MRI muscle fat fraction (FF) and clinical functional measures. Young boys with DMD (n = 16, 5-14 yr) and unaffected controls (n = 16, 5-14 yr) were evaluated using postcontractile BOLD, FF, and functional assessments. The BOLD response was measured following five brief (2 s) maximal voluntary dorsiflexion contractions, each separated by 1 min of rest. FFs from the anterior compartment lower leg muscles were quantified via chemical shift-encoded imaging. Functional abilities were assessed using the 10 m walk/run and the 6-min walk distance (6MWD). The peak BOLD responses in the tibialis anterior and extensor digitorum longus were reduced (P < 0.001) in DMD compared with controls. Furthermore, the anterior compartment peak BOLD response correlated with function (6MWD ρ = 0.87, P < 0.0001; 10 m walk/run time ρ = -0.78, P < 0.001) and FF (ρ = -0.52, P = 0.05). The reduced postcontractile BOLD response in DMD may reflect impaired microvascular function. The relationship observed between the postcontractile peak BOLD response and functional measures and FF suggests that the BOLD response is altered with disease severity in DMD.NEW & NOTEWORTHY This study examined the postcontractile blood oxygen level-dependent (BOLD) response in boys with Duchenne muscular dystrophy (DMD) and unaffected controls, and correlated this measure to markers of disease severity. Our findings indicate that the postcontractile BOLD response is impaired in DMD after brief muscle contractions, is correlated to disease severity, and may be valuable to implement in future studies to evaluate treatments targeting microvascular function in DMD.

Reduced coupling between cerebrospinal fluid flow and global brain activity is linked to Alzheimer disease-related pathology

The glymphatic system plays an important role in clearing the amyloid-β (Aβ) and tau proteins that are closely linked to Alzheimer disease (AD) pathology. Glymphatic clearance, as well as Aβ accumulation, is highly dependent on sleep, but the sleep-dependent driving forces behind cerebrospinal fluid (CSF) movements essential to the glymphatic flux remain largely unclear. Recent studies have reported that widespread, high-amplitude spontaneous brain activations in the drowsy state and during sleep, which are shown as large global signal peaks in resting-state functional magnetic resonance imaging (rsfMRI), are coupled with CSF movements, suggesting their potential link to glymphatic flux and metabolite clearance. By analyzing multimodal data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) project, here we showed that the coupling between the global fMRI signal and CSF influx is correlated with AD-related pathology, including various risk factors for AD, the severity of AD-related diseases, the cortical Aβ level, and cognitive decline over a 2-year follow-up. These results provide critical initial evidence for involvement of sleep-dependent global brain activity, as well as the associated physiological modulations, in the clearance of AD-related brain waste.

This study reveals strong coupling between the global fMRI signal and cerebrospinal fluid influx, finding that this is correlated with Alzheimer’s disease-related pathology, disease severity, and cognitive decline. This supports a link between spontaneous low-frequency brain dynamics and Alzheimer’s disease pathology, presumably due to their role in glymphatic clearance.

Individual differences in haemoglobin concentration influence bold fMRI functional connectivity and its correlation with cognition

Resting-state connectivity measures the temporal coherence of the spontaneous neural activity of spatially distinct regions, and is commonly measured using BOLD-fMRI. The BOLD response follows neuronal activity, when changes in the relative concentration of oxygenated and deoxygenated haemoglobin cause fluctuations in the MRI T2* signal. Since the BOLD signal detects changes in relative concentrations of oxy/deoxy-haemoglobin, individual differences in haemoglobin levels may influence the BOLD signal-to-noise ratio in a manner independent of the degree of neural activity. In this study, we examined whether group differences in haemoglobin may confound measures of functional connectivity. We investigated whether relationships between measures of functional connectivity and cognitive performance could be influenced by individual variability in haemoglobin. Finally, we mapped the neuroanatomical distribution of the influence of haemoglobin on functional connectivity to determine where group differences in functional connectivity are manifest. In a cohort of 518 healthy elderly subjects (259 men), each sex group was median-split into two groups with high and low haemoglobin concentration. Significant differences were obtained in functional connectivity between the high and low haemoglobin groups for both men and women (Cohen's d 0.17 and 0.03 for men and women respectively). The haemoglobin connectome in males showed a widespread systematic increase in functional connectivity correlation values, whilst the female connectome showed predominantly parietal and subcortical increases and temporo-parietal decreases. Despite the haemoglobin groups having no differences in cognitive measures, significant differences in the linear relationships between cognitive performance and functional connectivity were obtained for all 5 cognitive tests in males, and 4 out of 5 tests in females. Our findings confirm that individual variability in haemoglobin levels that give rise to group differences are an important confounding variable in BOLD-fMRI-based studies of functional connectivity. Controlling for haemoglobin variability as a potentially confounding variable is crucial to ensure the reproducibility of human brain connectome studies, especially in studies that compare groups of individuals, compare sexes, or examine connectivity-cognition relationships.

An equal-TE ultrafast 3D gradient-echo imaging method with high tolerance to magnetic susceptibility artifacts: Application to BOLD functional MRI

PURPOSE

To develop an ultrafast 3D gradient echo-based MRI method with constant TE and high tolerance to B₀ inhomogeneity, dubbed ERASE (equal-TE rapid acquisition with sequential excitation), and to introduce its use in BOLD functional MRI (fMRI).

THEORY AND METHODS

Essential features of ERASE, including spin behavior, were characterized, and a comparison study was conducted with conventional EPI. To demonstrate high tolerance to B₀ inhomogeneity, in vivo imaging of the mouse brain with a fiber-optic implant was performed at 9.4 T, and human brain imaging (including the orbitofrontal cortex) was performed at 3 T and 7 T. To evaluate the performance of ERASE in BOLD-fMRI, the characteristics of SNR and temporal SNR were analyzed for in vivo rat brains at 9.4 T in comparison with multislice gradient-echo EPI. Percent signal changes and t-scores are also presented.

RESULTS

For both mouse brain and human brain imaging, ERASE exhibited a high tolerance to magnetic susceptibility artifacts, showing much lower distortion and signal dropout, especially in the regions involving large magnetic susceptibility effects. For BOLD-fMRI, ERASE provided higher temporal SNR and t-scores than EPI, but exhibited similar percent signal changes in in vivo rat brains at 9.4 T.

CONCLUSION

When compared with conventional EPI, ERASE is much less sensitive, not only to EPI-related artifacts such as Nyquist ghosting, but also to B₀ inhomogeneity including magnetic susceptibility effects. It is promising for use in BOLD-fMRI, providing higher temporal SNR and t-scores with constant TE when compared with EPI, although further optimization is needed for human fMRI.

A Case of Cerebral Hyperperfusion Showing Unique Characteristics on Susceptibility-weighted MR Imaging after Carotid Endarterectomy

Cerebral hyperperfusion syndrome (CHS) is a potentially devastating complication of carotid endarterectomy (CEA). Early detection and treatment of hyperperfusion are important before the condition develops into CHS. We herein present a case involving a 65-year-old female with severe right internal carotid artery (ICA) stenosis, who experienced hyperperfusion after right CEA. During the postoperative course, changes in the resting cerebral blood flow (rCBF) were evaluated using single-photon emission computed tomography (SPECT), and were found to correlate with the changes in the signal intensity of cortical arteries, cortical veins, and perilateral ventricular veins of the right middle cerebral artery (MCA) territory on susceptibility-weighted imaging (SWI). SWI showed a prominent hyperintensity of cortical arteries in the right MCA territory at postoperative day 1 (POD1), but the hyperintensity gradually decreased over time and became indistinct by POD48. As for cortical veins and perilateral ventricular veins, SWI showed an increased signal intensity of these veins during the peak of rCBF on POD1, but later, the signal intensity decreased as rCBF decreased on POD5. The signal intensity of cortical veins and perilateral ventricular veins finally returned to normal on POD9. Those SWI findings could be related to an impairment of cerebral autoregulation and the resulting hyperperfusion. SWI could be potentially useful as an additional tool in the evaluation of hyperperfusion.

The resting-state fMRI arterial signal predicts differential blood transit time through the brain

Previous studies have found that aperiodic, systemic low-frequency oscillations (sLFOs) are present in blood-oxygen-level-dependent (BOLD) data. These signals are in the same low frequency band as the "resting state" signal; however, they are distinct signals which represent non-neuronal, physiological oscillations. The same sLFOs are found in the periphery (i.e. finger tips) as changes in oxy/deoxy-hemoglobin concentration using concurrent near-infrared spectroscopy. Together, this evidence points toward an extra-cerebral origin of these sLFOs. If this is the case, it is expected that these sLFO signals would be found in the carotid arteries with time delays that precede the signals found in the brain. To test this hypothesis, we employed the publicly available MyConnectome dataset (a two-year longitudinal study of a single subject) to extract the sLFOs in the internal carotid arteries (ICAs) with the help of the T1/T2-weighted images. Significant, but negative, correlations were found between the LFO BOLD signals from the ICAs and (1) the global signal (GS), (2) the superior sagittal sinus, and (3) the jugulars. We found the consistent time delays between the sLFO signals from ICAs, GS and veins which coincide with the blood transit time through the cerebral vascular tree.

Cerebral Autoregulation Evidenced by Synchronized Low Frequency Oscillations in Blood Pressure and Resting-State fMRI

Resting-state functional magnetic resonance imaging (rs-fMRI) is a widely used technique for mapping the brain’s functional architecture, so delineating the main sources of variance comprising the signal is crucial. Low frequency oscillations (LFO) that are not of neural origin, but which are driven by mechanisms related to cerebral autoregulation (CA), are present in the blood-oxygenation-level-dependent (BOLD) signal within the rs-fMRI frequency band. In this study we use a MR compatible device (Caretaker, Biopac) to obtain a non-invasive estimate of beat-to-beat mean arterial pressure (MAP) fluctuations concurrently with rs-fMRI at 3T. Healthy adult subjects (n = 9; 5 male) completed two 20-min rs-fMRI scans. MAP fluctuations were decomposed into different frequency scales using a discrete wavelet transform, and oscillations at approximately 0.1 Hz show a high degree of spatially structured correlations with matched frequency fMRI fluctuations. On average across subjects, MAP fluctuations at this scale of the wavelet decomposition explain ∼2.2% of matched frequency fMRI signal variance. Additionally, a simultaneous multi-slice multi-echo acquisition was used to collect 10-min rs-fMRI at three echo times at 7T in a separate group of healthy adults (n = 5; 5 male). Multiple echo times were used to estimate the R₂^∗ decay at every time point, and MAP was shown to strongly correlate with this signal, which suggests a purely BOLD (i.e., blood flow related) origin. This study demonstrates that there is a significant component of the BOLD signal that has a systemic physiological origin, and highlights the fact that not all localized BOLD signal changes necessarily reflect blood flow supporting local neural activity. Instead, these data show that a proportion of BOLD signal fluctuations in rs-fMRI are due to localized control of blood flow that is independent of local neural activity, most likely reflecting more general systemic autoregulatory processes. Thus, fMRI is a promising tool for studying flow changes associated with cerebral autoregulation with high spatial resolution.

Segmented Echo Planar Imaging Improves Detection of Subcortical Functional Connectivity Networks in the Rat Brain

Susceptibility artifacts in the vicinity of aural and nasal cavities result in significant signal drop-out and image distortion in echo planar imaging of the rat brain. These effects may limit the study of resting state functional connectivity in deep brain regions. Here, we explore the use of segmented EPI for resting state fMRI studies in the rat, and assess the relative merits of this method compared to single shot EPI. Sequences were evaluated in terms of signal-to-noise ratio, geometric distortions, data driven detection of resting state networks and group level correlations of time series. Multishot imaging provided improved SNR, temporal SNR and reduced geometric distortion in deep areas, while maintaining acceptable overall image quality in cortical regions. Resting state networks identified by independent component analysis were consistent across methods, but multishot EPI provided a more robust and accurate delineation of connectivity patterns involving deep regions typically affected by susceptibility artifacts. Importantly, segmented EPI showed reduced between-subject variability and stronger statistical significance of pairwise correlations at group level over the whole brain and in particular in subcortical regions. Multishot EPI may represent a valid alternative to snapshot methods in functional connectivity studies, particularly for the investigation of subcortical regions and deep gray matter nuclei.

Reprint of 'Noise contributions to the fMRI signal: An Overview'

The ability to discriminate signal from noise plays a key role in the analysis and interpretation of functional magnetic resonance imaging (fMRI) measures of brain activity. Over the past two decades, a number of major sources of noise have been identified, including system-related instabilities, subject motion, and physiological fluctuations. This article reviews the characteristics of the various noise sources as well as the mechanisms through which they affect the fMRI signal. Approaches for distinguishing signal from noise and the associated challenges are also reviewed. These challenges reflect the fact that some noise sources, such as respiratory activity, are generated by the same underlying brain networks that give rise to functional signals that are of interest.

7T-fMRI: Faster temporal resolution yields optimal BOLD sensitivity for functional network imaging specifically at high spatial resolution

Recent developments in accelerated imaging methods allow faster acquisition of high spatial resolution images. This could improve the applications of functional magnetic resonance imaging at 7 Tesla (7T-fMRI), such as neurosurgical planning and Brain Computer Interfaces (BCIs). However, increasing the spatial and temporal resolution will both lead to signal-to-noise ratio (SNR) losses due to decreased net magnetization per voxel and T₁-relaxation effect, respectively. This could potentially offset the SNR efficiency gains made with increasing temporal resolution. We investigated the effects of varying spatial and temporal resolution on fMRI sensitivity measures and their implications on fMRI-based BCI simulations. We compared temporal signal-to-noise ratio (tSNR), observed percent signal change (%∆S), volumes of significant activation, Z-scores and decoding performance of linear classifiers commonly used in BCIs across a range of spatial and temporal resolution images acquired during an ankle-tapping task. Our results revealed an average increase of 22% in %∆S (p=0.006) and 9% in decoding performance (p=0.015) with temporal resolution only at the highest spatial resolution of 1.5×1.5×1.5mm³, despite a 29% decrease in tSNR (p<0.001) and plateaued Z-scores. Further, the volume of significant activation was indifferent (p>0.05) across spatial resolution specifically at the highest temporal resolution of 500ms. These results demonstrate that the overall BOLD sensitivity can be increased significantly with temporal resolution, granted an adequately high spatial resolution with minimal physiological noise level. This shows the feasibility of diffuse motor-network imaging at high spatial and temporal resolution with robust BOLD sensitivity with 7T-fMRI. Importantly, we show that this sensitivity improvement could be extended to an fMRI application such as BCIs.

Relative latency and temporal variability of hemodynamic responses at the human primary visual cortex

The blood-oxygen-level-dependent (BOLD) functional MRI (fMRI) signal is a robust surrogate for local neuronal activity. However, it has been shown to vary substantially across subjects, brain regions, and repetitive measurements. This variability represents a limit to the precision of the BOLD response and the ability to reliably discriminate brain hemodynamic responses elicited by external stimuli or behavior that are nearby in time. While the temporal variability of the BOLD signal at human visual cortex has been found in the range of a few hundreds of milliseconds, the spatial distributions of the average and standard deviation of this temporal variability have not been quantitatively characterized. Here we use fMRI measurements with a high sampling rate (10Hz) to map the latency, intra- and inter-subject variability of the evoked BOLD signal in human primary (V1) visual cortices using an event-related fMRI paradigm. The latency relative to the average BOLD signal evoked by 30 stimuli was estimated to be 0.03±0.20s. Within V1, the absolute value of the relative BOLD latency was found correlated to intra- and inter-subject temporal variability. After comparing these measures to retinotopic maps, we found that locations with V1 areas sensitive to smaller eccentricity have later responses and smaller inter-subject variabilities. These correlations were found from data with either short inter-stimulus interval (ISI; average 4s) or long ISI (average 30s). Maps of the relative latency as well as inter-/intra-subject variability were found visually asymmetric between hemispheres. Our results suggest that the latency and variability of regional BOLD signal measured with high spatiotemporal resolution may be used to detect regional differences in hemodynamics to inform fMRI studies. However, the physiological origins of timing index distributions and their hemispheric asymmetry remain to be investigated.

Nuisance Regression of High-Frequency Functional Magnetic Resonance Imaging Data: Denoising Can Be Noisy

Recently, emerging studies have demonstrated the existence of brain resting-state spontaneous activity at frequencies higher than the conventional 0.1 Hz. A few groups utilizing accelerated acquisitions have reported persisting signals beyond 1 Hz, which seems too high to be accommodated by the sluggish hemodynamic process underpinning blood oxygen level-dependent contrasts (the upper limit of the canonical model is ∼0.3 Hz). It is thus questionable whether the observed high-frequency (HF) functional connectivity originates from alternative mechanisms (e.g., inflow effects, proton density changes in or near activated neural tissue) or rather is artificially introduced by improper preprocessing operations. In this study, we examined the influence of a common preprocessing step-whole-band linear nuisance regression (WB-LNR)-on resting-state functional connectivity (RSFC) and demonstrated through both simulation and analysis of real dataset that WB-LNR can introduce spurious network structures into the HF bands of functional magnetic resonance imaging (fMRI) signals. Findings of present study call into question whether published observations on HF-RSFC are partly attributable to improper data preprocessing instead of actual neural activities.

Noise contributions to the fMRI signal: An overview

The ability to discriminate signal from noise plays a key role in the analysis and interpretation of functional magnetic resonance imaging (fMRI) measures of brain activity. Over the past two decades, a number of major sources of noise have been identified, including system-related instabilities, subject motion, and physiological fluctuations. This article reviews the characteristics of the various noise sources as well as the mechanisms through which they affect the fMRI signal. Approaches for distinguishing signal from noise and the associated challenges are also reviewed. These challenges reflect the fact that some noise sources, such as respiratory activity, are generated by the same underlying brain networks that give rise to functional signals that are of interest.

Systematic variation of population receptive field properties across cortical depth in human visual cortex

Receptive fields (RFs) in visual cortex are organized in antagonistic, center-surround, configurations. RF properties change systematically across eccentricity and between visual field maps. However, it is unknown how center-surround configurations are organized in human visual cortex across lamina. We use sub-millimeter resolution functional MRI at 7Tesla and population receptive field (pRF) modeling to investigate the pRF properties in primary visual cortex (V1) across cortical depth. pRF size varies according to a U-shaped function, indicating smaller pRF center size in the middle compared to superficial and deeper intra-cortical portions of V1, consistent with non-human primate neurophysiological measurements. Moreover, a similar U-shaped function is also observed for pRF surround size. However, pRF center-surround ratio remains constant across cortical depth. Simulations suggest that this pattern of results can be directly linked to the flow of signals across cortical depth, with the visual input reaching the middle of cortical depth and then spreading towards superficial and deeper layers of V1. Conversely, blood-oxygenation-level-dependent (BOLD) signal amplitude increases monotonically towards the pial surface, in line with the known vascular organization across cortical depth. Independent estimates of the haemodynamic response function (HRF) across cortical depth show that the center-surround pRF size estimates across cortical depth cannot be explained by variations in the full-width half maximum (FWHM) of the HRF.

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.

Evaluation of the Contribution of Signals Originating from Large Blood Vessels to Signals of Functionally Specific Brain Areas

The fusiform face area (FFA) is known to play a pivotal role in face processing. The FFA is located in the ventral region, at the base of the brain, through which large blood vessels run. The location of the FFA via functional MRI (fMRI) may be influenced by these large blood vessels. Responses of large blood vessels may not exactly correspond to neuronal activity in a target area, because they may be diluted and influenced by inflow effects. In this study, we investigated the effects of large blood vessels in the FFA, that is, whether the FFA includes large blood vessels and/or whether inflow signals contribute to fMRI signals of the FFA. For this purpose, we used susceptibility-weighted imaging (SWI) sequences to visualize large blood vessels and dual-echo gradient-echo echo-planar imaging (GE-EPI) to measure inflow effects. These results showed that the location and response signals of the FFA were not influenced by large blood vessels or inflow effects, although large blood vessels were located near the FFA. Therefore, the data from the FFA obtained by individual analysis were robust to large blood vessels but leaving a warning that the data obtained by group analysis may be prone to large blood vessels.

BOLD fractional contribution to resting-state functional connectivity above 0.1 Hz

Blood oxygen level dependent (BOLD) spontaneous signals from resting-state (RS) brains have typically been characterized by low-pass filtered timeseries at frequencies ≤ 0.1 Hz, and studies of these low-frequency fluctuations have contributed exceptional understanding of the baseline functions of our brain. Very recently, emerging evidence has demonstrated that spontaneous activities may persist in higher frequency bands (even up to 0.8 Hz), while presenting less variable network patterns across the scan duration. However, as an indirect measure of neuronal activity, BOLD signal results from an inherently slow hemodynamic process, which in fact might be too slow to accommodate the observed high-frequency functional connectivity (FC). To examine whether the observed high-frequency spontaneous FC originates from BOLD contrast, we collected RS data as a function of echo time (TE). Here we focus on two specific resting state networks - the default-mode network (DMN) and executive control network (ECN), and the major findings are fourfold: (1) we observed BOLD-like linear TE-dependence in the spontaneous activity at frequency bands up to 0.5 Hz (the maximum frequency that can be resolved with TR=1s), supporting neural relevance of the RSFC at a higher frequency range; (2) conventional models of hemodynamic response functions must be modified to support resting state BOLD contrast, especially at higher frequencies; (3) there are increased fractions of non-BOLD-like contributions to the RSFC above the conventional 0.1 Hz (non-BOLD/BOLD contrast at 0.4-0.5 Hz is ~4 times that at <0.1 Hz); and (4) the spatial patterns of RSFC are frequency-dependent. Possible mechanisms underlying the present findings and technical concerns regarding RSFC above 0.1 Hz are discussed.

Spin labeling artery method perfusion MRI study of SPG4 and SCA3/MJD

BACKGROUND

Spinocerebellar ataxia type 3 (SCA3) and Machado-Joseph disease (MJD) are similar diseases that are often referred to jointly as SCA3/MJD. As the most common autosomal-dominantly inherited subtype of hereditary spastic paraplegia (HSP), HSP4 (or SPG4) has overlapping symptoms with SCA3/MJD, which hinders their diagnoses. Arterial spin labeling (ASL) is a noninvasive, contrast-agent free, magnetic resonance perfusion imaging method used to obtain maps of the cerebral blood flow (CBF). Here, we investigated the diagnostic value of ASL in SCA3/MJD and SPG4 patients.

METHODS

A total of 13 SPG4 cases, 38 SCA3/MJD cases (22 onset patients and 16 genetic abnormality-only patients), and 27 healthy volunteers were examined by ASL. Data were processed to obtain the regional CBF (rCBF) and comparatively studied.

RESULTS

In the pons, cerebellar dentate nucleus, and cerebellar cortex, rCBF of the onset SCA3/MJD group was significantly lower than that of the normal control group. In the cerebellar dentate nucleus and cerebellar cortex, the rCBF of the non-onset SCA3/MJD group was significantly lower than that of the control group. In the pons and cerebellar cortex, the rCBF of the onset SCA3/MJD group was significantly lower than that of the SPG4 group.

CONCLUSIONS

SCA3/MJD lesions are mainly located in the cerebellum and brainstem. Gray matter and white matter were both involved, although the deep cerebellar nuclei may be the earliest involved region. Cerebellar and brainstem lesions of SCA3/MJD were more severe than those of SPG4. ASL can aid the diagnosis of SCA3/MJD and SPG4.

Microscopic functional specificity can be predicted from fMRI signals in ventral visual areas

Functional areas specialized for recognition can be activated by a non-preferred stimulus as well as a preferred stimulus. The functional magnetic resonance imaging signals detected in response to different stimuli in an area may have the same or different amplitudes. However, it is uncertain whether the responses originate from the same neuronal populations or heterogeneous ones. To address this concern, we propose a novel method that uses multi-echo echo-planar imaging sequences to evaluate changes in the transverse relaxation profile caused by stimulation. According to this method, the areas related with visual recognition, i.e. fusiform face area and parahippocampal place area, have different transverse relaxation profiles to preferred and non-preferred stimuli, which can be considered as reflecting a difference in neuronal population processing stimuli in those areas. The proposed method can be useful for probing the microscopic functional specificity of brain areas.

Signal contributions to heavily diffusion-weighted functional magnetic resonance imaging investigated with multi-SE-EPI acquisitions

Diffusion-weighted (DW) functional magnetic resonance imaging (fMRI) signal changes have been noted as a promising marker of neural activity. Although there is no agreement on the signal origin, the blood oxygen level dependent (BOLD) effect has figured as one of the most likely sources. In order to investigate possible BOLD and non-BOLD contributions to the signal, DW fMRI was performed on normal volunteers using a sequence with two echo-planar acquisitions after pulsed-gradient spin-echo. Along with the changes to the signal amplitude (ΔS/S) measured at both echo-times, this sequence allowed changes to the transverse relaxation rate (ΔR2) to be estimated for multiple b-values during hypercapnia (HC) and visual stimulation (VS). ΔS/S and ΔR2 observed during HC were relatively insensitive to increasing b-value. On the other hand, ΔS/S demonstrated a clear dependence on b-value at both echo-times for VS. In addition, ΔR2 during the latter half of VS was significantly more negative at b=1400s/mm(2) than for the time-courses at lower b-value, but ΔR2 during the post-stimulus undershoot was independent of b-value. The results have been discussed in terms of two models: the standard intravascular-extravascular model for fMRI and a three-compartment model (one intra- and two extravascular compartments). Within these interpretations the results suggest that the majority of the response is linked to changes in transverse relaxation, but possible contributions from other sources may not be ruled out.

A novel approach for fMRI data analysis based on the combination of sparse approximation and affinity propagation clustering

Clustering analysis has been widely used to detect the functional connectivity from functional magnetic resonance imaging (fMRI) data. However, it has some limitations such as enormous computer memory requirement, and difficulty in estimating the number of clusters. In this study, in order to effectually resolve the deficiencies mentioned above, we have proposed a novel approach (SAAPC) for fMRI data analysis, which combines sparsity, an effective assumption for analyzing fMRI signal, with affinity propagation clustering (APC). The SAAPC method is composed of three parts: to obtain the sparse approximation coefficients set through wavelet packet decomposition and sparsity measuring and selection, which contributes a lot in the brain functional connectivity detection accuracy; to implement a split APC algorithm, which is put forward in this paper to overcome the computer memory shortage problem and to reduce the time cost in basic APC; to reconstruct the source signal by unmixing the mixed fMRI data using the time courses which are derived from the ultimate exemplars. In the task-related experiments, we can see that SAAPC is more accurate to detect the functional networks than basic APC, and it significantly reduces the time cost relative to basic APC. In addition, in the resting-state data experiments, the SAAPC method can successfully identify typical resting-state networks from the resting-state data set, while this performance is seldom reported by the classical cluster method and the basic APC method. This proposed clustering analysis method is expected to have wide applicability.

Optimized simultaneous ASL and BOLD functional imaging of the whole brain

PURPOSE

To compare a double-excitation combined arterial-spin labeling/blood-oxygenation level dependent (ASL/BOLD) functional imaging method to a double-echo method. ASL provides a useful complement to standard BOLD functional imaging, to map effects of cerebral hemodynamics. Whole-brain imaging is necessary to properly characterize large functional networks. A challenge of whole-brain ASL/BOLD is that images for ASL functional contrast must be acquired before significant longitudinal relaxation of the inverted spins occurs; however, a longer echo time (TE) is required for optimal BOLD functional contrast, lengthening the acquisition time. Thus, existing combined ASL/BOLD studies have only partial-brain coverage.

MATERIALS AND METHODS

The proposed method allows acquisition of images for ASL contrast within a short period after the ASL labeling pulse and postinversion delay, then subsequent acquisition of images with longer TE for BOLD contrast. The technique is demonstrated using a narrative comprehension task in 35 normal children, and the double-excitation method is empirically compared with the double-echo method in 7 normal adults.

RESULTS

Compared with a double-echo sequence, simulations show the double-excitation method improves ASL contrast-to-noise ratio (CNR) (∼50%) in later-acquired slices with minimal (<1%) reduction in BOLD CNR in earlier-acquired slices if reduced excitation flip angles for the ASL acquisitions are used. Empirical results from adult data are in agreement with the simulations. Group analyses from the narrative comprehension task also show greater intersubject sensitivity in BOLD versus ASL.

CONCLUSION

Our method simultaneously optimizes ASL and BOLD acquisitions for CNR while economizing acquisition time.