Functional brain mapping by blood oxygenation level-dependent contrast magnetic resonance imaging. A comparison of signal characteristics with a biophysical model

Performance of receive head arrays versus ultimate intrinsic SNR at 7 T and 10.5 T

PURPOSE

We examined magnetic field dependent SNR gains and ability to capture them with multichannel receive arrays for human head imaging in going from 7 T, the most commonly used ultrahigh magnetic field (UHF) platform at the present, to 10.5 T, which represents the emerging new frontier of >10 T in UHFs.

METHODS

Electromagnetic (EM) models of 31-channel and 63-channel multichannel arrays built for 10.5 T were developed for 10.5 T and 7 T simulations. A 7 T version of the 63-channel array with an identical coil layout was also built. Array performance was evaluated in the EM model using a phantom mimicking the size and electrical properties of the human head and a digital human head model. Experimental data was obtained at 7 T and 10.5 T with the 63-channel array. Ultimate intrinsic SNR (uiSNR) was calculated for the two field strengths using a voxelized cloud of dipoles enclosing the phantom or the digital human head model as a reference to assess the performance of the two arrays and field depended SNR gains.

RESULTS

uiSNR calculations in both the phantom and the digital human head model demonstrated SNR gains at 10.5 T relative to 7 T of 2.6 centrally, ˜2 at the location corresponding to the edge of the brain, ˜1.4 at the periphery. The EM models demonstrated that, centrally, both arrays captured ˜90% of the uiSNR at 7 T, but only ˜65% at 10.5 T, leading only to ˜2-fold gain in array SNR in going from 7 to 10.5 T. This trend was also observed experimentally with the 63-channel array capturing a larger fraction of the uiSNR at 7 T compared to 10.5 T, although the percentage of uiSNR captured were slightly lower at both field strengths compared to EM simulation results.

CONCLUSIONS

Major uiSNR gains are predicted for human head imaging in going from 7 T to 10.5 T, ranging from ˜2-fold at locations corresponding to the edge of the brain to 2.6-fold at the center, corresponding to approximately quadratic increase with the magnetic field. Realistic 31- and 63-channel receive arrays, however, approach the central uiSNR at 7 T, but fail to do so at 10.5 T, suggesting that more coils and/or different type of coils will be needed at 10.5 T and higher magnetic fields.

COVID-19 is associated with changes in brain function and structure: A multimodal meta-analysis of neuroimaging studies

The actual role of coronavirus disease 2019 (COVID-19) in brain damage has been increasingly reported, necessitating a meta-analysis to collate and summarize the inconsistent findings from functional imaging and voxel-based morphometry (VBM) studies. A comprehensive voxel-wise meta-analysis of the whole brain was conducted to identify alterations in functional activity and gray matter volume (GMV) between COVID-19 patients and healthy controls (HCs) by using Seed-based d Mapping software. We included 15 functional imaging studies (484 patients with COVID-19, 534 HCs) and 9 VBM studies (449 patients with COVID-19, 388 HCs) in the analysis. Overall, patients with COVID-19 exhibited decreased functional activity in the right superior temporal gyrus (STG) (extending to the right middle and inferior temporal gyrus, insula, and temporal pole [TP]), left insula, right orbitofrontal cortex (OFC) (extending to the right olfactory cortex), and left cerebellum compared to HCs. For VBM, patients with COVID-19, relative to HCs, showed decreased GMV in the bilateral anterior cingulate cortex/medial prefrontal cortex (extending to the bilateral OFC), and left cerebellum, and increased GMV in the bilateral amygdala (extending to the bilateral hippocampus, STG, TP, MTG, and right striatum). Moreover, overlapping analysis revealed that patients with COVID-19 exhibited both decreased functional activity and increased GMV in the right TP (extending to the right STG). The multimodal meta-analysis suggests that brain changes of function and structure in the temporal lobe, OFC and cerebellum, and functional or structural alterations in the insula and the limbic system in COVID-19. These findings contribute to a better understanding of the pathophysiology of brain alterations in COVID-19. SIGNIFICANCE STATEMENT: This first large-scale multimodal meta-analysis collates existing neuroimaging studies and provides voxel-wise functional and structural whole-brain abnormalities in COVID-19. Findings of this meta-analysis provide valuable insights into the dynamic brain changes (from infection to recovery) and offer further explanations for the pathophysiological basis of brain alterations in COVID-19.

Fast 3D fMRI acquisition with high spatial resolutions over a reduced FOV

PURPOSE

To develop and demonstrate a fast 3D fMRI acquisition technique with high spatial resolution over a reduced FOV, named k-t 3D reduced FOV imaging (3D-rFOVI).

METHODS

Based on 3D gradient-echo EPI, k-t 3D-rFOVI used a 2D RF pulse to reduce the FOV in the in-plane phase-encoding direction, boosting spatial resolution without increasing echo train length. For image acceleration, full sampling was applied in the central k-space region along the through-slab direction (kz) for all time frames, while randomized undersampling was used in outer kz regions at different time frames. Images were acquired at 3T and reconstructed using a method based on partial separability. fMRI detection sensitivity of k-t 3D-rFOVI was quantitively analyzed with simulation data. Human visual fMRI experiments were performed to evaluate k-t 3D-rFOVI and compare it with a commercial multiband EPI sequence.

RESULTS

The simulation data showed that k-t 3D-rFOVI can detect 100% of fMRI activations with an acceleration factor (R) of 2 and ˜80% with R = 6. In the human fMRI data acquired with 1.5-mm spatial resolution and 800-ms volume TR (TRvol), k-t 3D-rFOVI with R = 4 detected 46% more activated voxels in the visual cortex than the multiband EPI. Additional fMRI experiments showed that k-t 3D-rFOVI can achieve TRvol of 480 ms with R = 6, while reliably detecting visual activation.

CONCLUSIONS

k-t 3D-rFOVI can simultaneously achieve a high spatial resolution (1.5-mm isotropically) and short TRvol (480-ms) at 3T. It offers a robust acquisition technique for fast fMRI studies over a focused brain volume.

A Multimodal Approach to Measuring Listening Effort: A Systematic Review on the Effects of Auditory Task Demand on Physiological Measures and Their Relationship

OBJECTIVES

Listening effort involves the mental effort required to perceive an auditory stimulus, for example in noisy environments. Prolonged increased listening effort, for example due to impaired hearing ability, may increase risk of health complications. It is therefore important to identify valid and sensitive measures of listening effort. Physiological measures have been shown to be sensitive to auditory task demand manipulations and are considered to reflect changes in listening effort. Such measures include pupil dilation, alpha power, skin conductance level, and heart rate variability. The aim of the current systematic review was to provide an overview of studies to listening effort that used multiple physiological measures. The two main questions were: (1) what is the effect of changes in auditory task demand on simultaneously acquired physiological measures from various modalities? and (2) what is the relationship between the responses in these physiological measures?

DESIGN

Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, relevant articles were sought in PubMed, PsycInfo, and Web of Science and by examining the references of included articles. Search iterations with different combinations of psychophysiological measures were performed in conjunction with listening effort-related search terms. Quality was assessed using the Appraisal Tool for Cross-Sectional Studies.

RESULTS

A total of 297 articles were identified from three databases, of which 27 were included. One additional article was identified from reference lists. Of the total 28 included articles, 16 included an analysis regarding the relationship between the physiological measures. The overall quality of the included studies was reasonable.

CONCLUSIONS

The included studies showed that most of the physiological measures either show no effect to auditory task demand manipulations or a consistent effect in the expected direction. For example, pupil dilation increased, pre-ejection period decreased, and skin conductance level increased with increasing auditory task demand. Most of the relationships between the responses of these physiological measures were nonsignificant or weak. The physiological measures varied in their sensitivity to auditory task demand manipulations. One of the identified knowledge gaps was that the included studies mostly used tasks with high-performance levels, resulting in an underrepresentation of the physiological changes at lower performance levels. This makes it difficult to capture how the physiological responses behave across the full psychometric curve. Our results support the Framework for Understanding Effortful Listening and the need for a multimodal approach to listening effort. We furthermore discuss focus points for future studies.

Mapping vascular network architecture in primate brain using ferumoxytol-weighted laminar MRI

Mapping the vascular organization of the brain is of great importance across various domains of basic neuroimaging research, diagnostic radiology, and neurology. However, the intricate task of precisely mapping vasculature across brain regions and cortical layers presents formidable challenges, resulting in a limited understanding of neurometabolic factors influencing the brain's microvasculature. Addressing this gap, our study investigates whole-brain vascular volume using ferumoxytol-weighted laminar-resolution multi-echo gradient-echo imaging in macaque monkeys. We validate the results with published data for vascular densities and compare them with cytoarchitecture, neuron and synaptic densities. The ferumoxytol-induced change in transverse relaxation rate (ΔR2*), an indirect proxy measure of cerebral blood volume (CBV), was mapped onto twelve equivolumetric laminar cortical surfaces. Our findings reveal that CBV varies 3-fold across the brain, with the highest vascular volume observed in the inferior colliculus and lowest in the corpus callosum. In the cerebral cortex, CBV is notably high in early primary sensory areas and low in association areas responsible for higher cognitive functions. Classification of CBV into distinct groups unveils extensive replication of translaminar vascular network motifs, suggesting distinct computational energy supply requirements in areas with varying cytoarchitecture types. Regionally, baseline R2* and CBV exhibit positive correlations with neuron density and negative correlations with receptor densities. Adjusting image resolution based on the critical sampling frequency of penetrating cortical vessels, allows us to delineate approximately 30% of the arterial-venous vessels. Collectively, these results mark significant methodological and conceptual advancements, contributing to the refinement of cerebrovascular MRI. Furthermore, our study establishes a linkage between neurometabolic factors and the vascular network architecture in the primate brain.

On the influence of the vascular architecture on Gradient Echo and Spin Echo BOLD fMRI signals across cortical depth: a simulation approach based on realistic 3D vascular networks

GE-BOLD contrast stands out as the predominant technique in functional MRI experiments for its high sensitivity and straightforward implementation. GE-BOLD exhibits rather similar sensitivity to vessels independent of their size at submillimeter resolution studies like those examining cortical columns and laminae. However, the presence of nonspecific macrovascular contributions poses a challenge to accurately isolate neuronal activity. SE-BOLD increases specificity towards small vessels, thereby enhancing its specificity to neuronal activity, due to the effective suppression of extravascular contributions caused by macrovessels with its refocusing pulse. However, even SE-BOLD measurements may not completely remove these macrovascular contributions. By simulating hemodynamic signals across cortical depth, we gain insights into vascular contributions to the laminar BOLD signal. In this study, we employed four realistic 3D vascular models to simulate oxygen saturation states in various vascular compartments, aiming to characterize both intravascular and extravascular contributions to GE and SE signals, and corresponding BOLD signal changes, across cortical depth at 7T. Simulations suggest that SE-BOLD cannot completely reduce the macrovascular contribution near the pial surface. Simulations also show that both the specificity and signal amplitude of BOLD signals at 7T depend on the spatial arrangement of large vessels throughout cortical depth and on the pial surface.

A fully synthetic three-dimensional human cerebrovascular model based on histological characteristics to investigate the hemodynamic fingerprint of the layer BOLD fMRI signal formation

Recent advances in functional magnetic resonance imaging (fMRI) at ultra-high field (≥7 tesla), novel hardware, and data analysis methods have enabled detailed research on neurovascular function, such as cortical layer-specific activity, in both human and nonhuman species. A widely used fMRI technique relies on the blood oxygen level-dependent (BOLD) signal. BOLD fMRI offers insights into brain function by measuring local changes in cerebral blood volume, cerebral blood flow, and oxygen metabolism induced by increased neuronal activity. Despite its potential, interpreting BOLD fMRI data is challenging as it is only an indirect measurement of neuronal activity. Computational modeling can help interpret BOLD data by simulating the BOLD signal formation. Current developments have focused on realistic 3D vascular models based on rodent data to understand the spatial and temporal BOLD characteristics. While such rodent-based vascular models highlight the impact of the angioarchitecture on the BOLD signal amplitude, anatomical differences between the rodent and human vasculature necessitate the development of human-specific models. Therefore, a computational framework integrating human cortical vasculature, hemodynamic changes, and biophysical properties is essential. Here, we present a novel computational approach: a three-dimensional VAscular MOdel based on Statistics (3D VAMOS), enabling the investigation of the hemodynamic fingerprint of the BOLD signal within a model encompassing a fully synthetic human 3D cortical vasculature and hemodynamics. Our algorithm generates microvascular and macrovascular architectures based on morphological and topological features from the literature on human cortical vasculature. By simulating specific oxygen saturation states and biophysical interactions, our framework characterizes the intravascular and extravascular signal contributions across cortical depth and voxel-wise levels for gradient-echo and spin-echo readouts. Thereby, the 3D VAMOS computational framework demonstrates that using human characteristics significantly affects the BOLD fingerprint, making it an essential step in understanding the fundamental underpinnings of layer-specific fMRI experiments.

Brain atrophy, reduced cerebral perfusion, arterial stiffening, and wall thickening with aging coincide with stimulus-specific changes in fMRI-BOLD responses

The aim of this study was to investigate how aging affects blood flow and structure of the brain. It was hypothesized older individuals would have lower gray matter volume (GMV), resting cerebral blood flow (CBF0), and depressed responses to isometabolic and neurometabolic stimuli. In addition, increased carotid-femoral pulse-wave velocity (PWV), carotid intima-media thickness (IMT), and decreased brachial flow-mediated dilation (FMD) would be associated with lower CBF0, cerebrovascular reactivity (CVR), and GMV. Brain scans (magnetic resonance imaging) and cardiovascular examinations were conducted in young (age = 24 ± 3 yr, range = 22-28 yr; n = 13) and old (age = 71 ± 4 yr; range = 67-82 yr, n = 14) participants, and CBF0, CVR [isometabolic % blood oxygen level-dependent (BOLD) in response to a breath hold (BH)], brain activation patterns during a working memory task (neurometabolic %BOLD response to N-back trial), GMV, PWV, IMT, and FMD were measured. CBF0 and to a lesser extent CVRBH were lower in the old group (P ≤ 0.050); however, the increase in the %BOLD response to the memory task was not blunted (P ≥ 0.2867). Age-related differential activation patterns during the working memory task were characterized by disinhibition of the default mode network in the old group (P < 0.0001). Linear regression analyses revealed PWV, and IMT were negatively correlated with CBF0, CVRBH, and GMV across age groups, but within the old group alone only the relationships between PWV-CVRBH and IMT-GMV remained significant (P ≤ 0.0183). These findings suggest the impacts of age on cerebral %BOLD responses are stimulus specific, brain aging involves alterations in cerebrovascular and possibly neurocognitive control, and arterial stiffening and wall thickening may serve a role in cerebrovascular aging.NEW & NOTEWORTHY Cerebral perfusion was lower in old versus young adults. %Blood oxygen level-dependent (BOLD) responses to an isometabolic stimulus and gray matter volume were decreased in old versus young adults and associated with arterial stiffening and wall thickening. The increased %BOLD response to a neurometabolic stimulus appeared unaffected by age; however, the old group displayed disinhibition of the default mode network during the stimulus. Thus, age-related alterations in cerebral %BOLD responses were stimulus specific and related to arterial remodeling.

Multimodal surface coils for low field MR imaging

Low field MRI is safer and more cost effective than the high field MRI. One of the inherent problems of low field MRI is its low signal-to-noise ratio or sensitivity. In this work, we introduce a multimodal surface coil technique for signal excitation and reception to improve the RF magnetic field (B 1 ) efficiency and potentially improve MR sensitivity. The proposed multimodal surface coil consists of multiple identical resonators that are electromagnetically coupled to form a multimodal resonator. The field distribution of its lowest frequency mode is suitable for MR imaging applications. The prototype multimodal surface coils are built, and the performance is investigated and validated through numerical simulation, standard RF measurements and tests, and comparison with the conventional surface coil at low fields. Our results show that the B 1 efficiency of the multimodal surface coil outperforms that of the conventional surface coil which is known to offer the highest B 1 efficiency among all coil categories, i.e., volume coil, half-volume coil and surface coil. In addition, in low-field MRI, the required low-frequency coils often use large value capacitance to achieve the low resonant frequency which makes frequency tuning difficult. The proposed multimodal surface coil can be conveniently tuned to the required low frequency for low-field MRI with significantly reduced capacitance value, demonstrating excellent low-frequency operation capability over the conventional surface coil.

Adaptive smoothing of retinotopic maps based on Teichmüller parametrization

Retinotopic mapping, the mapping between visual inputs on the retina and neural responses on the cortical surface, is one of the fundamental topics in visual neuroscience. In human studies, retinotopic maps are conventionally constructed and processed by decoding blood oxygenation-level dependent (BOLD) functional magnetic resonance imaging (fMRI) responses to designed visual stimuli on the cortical surface. However, these methods frequently generate retinotopic maps that do not preserve topology, contradicting a fundamental property of retinotopic maps observed in neurophysiology. To address this problem, we propose an integrated approach to simultaneously refine the flattening from the 3D cortical surface to the 2D parametric space and adaptively smooth retinotopic perception centers in the visual space to make the retinotopic maps topological. One key element of the approach is the enhanced error tolerant Teichmüller mapping, which refines the parametrization by minimizing angle distortions and maximizing alignment to noisy landmarks. We validated our overall approach with synthetic and real retinotopic mapping datasets and applied it to compute cortical magnification factor (CMF). The results showed that the proposed approach was superior to other conventional retinotopic mapping methods in predicting BOLD fMRI time series and preserving topology.

Mapping cerebral perfusion in mice under various anesthesia levels using highly sensitive BOLD MRI with transient hypoxia

Cerebral perfusion is critical for the early detection of neurological diseases and for effectively monitoring disease progression and treatment responses. Mouse models are widely used in brain research, often under anesthesia, which can affect vascular physiology. However, the impact of anesthesia on regional cerebral blood volume and flow in mice has not been thoroughly investigated. In this study, we have developed a whole-brain perfusion MRI approach by using a 5-second nitrogen gas stimulus under inhalational anesthetics to induce transient BOLD dynamic susceptibility contrast (DSC). This method proved to be highly sensitive, repeatable within each imaging session, and across four weekly sessions. Relative cerebral blood volumes measured by BOLD DSC agree well with those by contrast agents. Quantitative cerebral blood volume and flow metrics were successfully measured in mice under dexmedetomidine and various isoflurane doses using both total vasculature-sensitive gradient-echo and microvasculature-sensitive spin-echo BOLD MRI. Dexmedetomidine reduces cerebral perfusion, while isoflurane increases cerebral perfusion in a dose-dependent manner.

Predicting the macrovascular contribution to resting-state fMRI functional connectivity at 3 Tesla: A model-informed approach

Macrovascular biases have been a long-standing challenge for fMRI, limiting its ability to detect spatially specific neural activity. Recent experimental studies, including our own (Huck et al., 2023; Zhong et al., 2023), found substantial resting-state macrovascular BOLD fMRI contributions from large veins and arteries, extending into the perivascular tissue at 3 T and 7 T. The objective of this study is to demonstrate the feasibility of predicting, using a biophysical model, the experimental resting-state BOLD fluctuation amplitude (RSFA) and associated functional connectivity (FC) values at 3 Tesla. We investigated the feasibility of both 2D and 3D infinite-cylinder models as well as macrovascular anatomical networks (mVANs) derived from angiograms. Our results demonstrate that: 1) with the availability of mVANs, it is feasible to model macrovascular BOLD FC using both the mVAN-based model and 3D infinite-cylinder models, though the former performed better; 2) biophysical modelling can accurately predict the BOLD pairwise correlation near to large veins (with R 2 ranging from 0.53 to 0.93 across different subjects), but not near to large arteries; 3) compared with FC, biophysical modelling provided less accurate predictions for RSFA; 4) modelling of perivascular BOLD connectivity was feasible at close distances from veins (with R 2 ranging from 0.08 to 0.57), but not arteries, with performance deteriorating with increasing distance. While our current study demonstrates the feasibility of simulating macrovascular BOLD in the resting state, our methodology may also apply to understanding task-based BOLD. Furthermore, these results suggest the possibility of correcting for macrovascular bias in resting-state fMRI and other types of fMRI using biophysical modelling based on vascular anatomy.

Mitigation of Fetal Irradiation Injury from Mid-Gestation Total Body Radiation with Mitochondrial-Targeted GS-Nitroxide JP4-039

Victims of a radiation terrorist event will include pregnant women and unborn fetuses. Mitochondrial dysfunction and oxidative stress are key pathogenic factors of fetal irradiation injury. The goal of this preclinical study is to investigate the efficacy of mitigating fetal irradiation injury by maternal administration of the mitochondrial-targeted gramicidin S (GS)- nitroxide radiation mitigator, JP4-039. Pregnant female C57BL/6NTac mice received 3 Gy total body ionizing irradiation (TBI) at mid-gestation embryonic day 13.5 (E13.5). Using novel time- and-motion-resolved 4D in utero magnetic resonance imaging (4D-uMRI), we found TBI caused extensive injury to the fetal brain that included cerebral hemorrhage, loss of cerebral tissue, and hydrocephalus with excessive accumulation of cerebrospinal fluid (CSF). Histopathology of the fetal mouse brain showed broken cerebral vessels and elevated apoptosis. Further use of novel 4D Oxy-wavelet MRI capable of probing in vivo mitochondrial function in intact brain revealed significant reduction of mitochondrial function in the fetal brain after 3Gy TBI. This was validated by ex vivo Oroboros mitochondrial respirometry. Maternal administration JP4-039 one day after TBI (E14.5), which can pass through the placental barrier, significantly reduced fetal brain radiation injury and improved fetal brain mitochondrial respiration. This also preserved cerebral brain tissue integrity and reduced cerebral hemorrhage and cell death. As JP4-039 administration did not change litter sizes or fetus viability, together these findings indicate JP4-039 can be deployed as a safe and effective mitigator of fetal radiation injury from mid-gestational in utero ionizing radiation exposure.

One Sentence Summary

Mitochondrial-targeted gramicidin S (GS)-nitroxide JP4-039 is safe and effective radiation mitigator for mid-gestational fetal irradiation injury.

An MRI Compatible Data Acquisition Device for Rat Brain Recording Inside 16.4T Magnet

Concurrent recording of neural activities and functional magnetic resonance imaging (fMRI) data is useful for studying the neurovascular coupling relationship. This article presents a low-noise, frequency-shaping based neural recorder chip that is insensitive to radio frequency (RF) pulses and gradient echo artifacts under strong magnetic environment. To support simultaneous recording of local field potentials (LFPs), extracellular spikes, and fMRI data, a magnetic resonance imaging (MRI) compatible data acquisition (DAQ) device based on the designed recorder chip is developed with multiple circuit optimization techniques. Bench-top measurement shows that the designed DAQ device has 4.5 μV input-referred noise integrated from 300 Hz to 3000 Hz, which is not greatly affected by electromagnetic interference (EMI) at ultrahigh magnetic field (UMF, 16.4 T). In animal experiments, the designed DAQ device has been demonstrated to be capable of acquiring both the LFPs and extracellular spikes from a rat's brain before, during, and after MRI scanning. Besides, no obvious artifacts are seen from the designed DAQ device at multiple typical MRI scanning modes, and the system recovery time after gradient artifacts is reduced from more than 25 ms to less than 5 ms. The proposed DAQ device architecture based on the frequency-shaping neural recorder chip is MRI compatible and can provide highly competitive performance for concurrent recording of neural activities and fMRI data.

Covert consciousness

Covert consciousness is a state of residual awareness following severe brain injury or neurological disorder that evades routine bedside behavioral detection. Patients with covert consciousness have preserved awareness but are incapable of self-expression through ordinary means of behavior or communication. Growing recognition of the limitations of bedside neurobehavioral examination in reliably detecting consciousness, along with advances in neurotechnologies capable of detecting brain states or subtle signs indicative of consciousness not discernible by routine examination, carry promise to transform approaches to classifying, diagnosing, prognosticating and treating disorders of consciousness. Here we describe and critically evaluate the evolving clinical category of covert consciousness, including approaches to its diagnosis through neuroimaging, electrophysiology, and novel behavioral tools, its prognostic relevance, and open questions pertaining to optimal clinical management of patients with covert consciousness recovering from severe brain injury.

Impairment of cerebral vascular reactivity and resting blood flow in early-staged transgenic AD mice: in vivo optical imaging studies

Background

Alzheimer's disease (AD) is a neurodegenerative disorder with progressive cognitive decline in aging individuals that poses a significant challenge to patients due to an incomplete understanding of its etiology and lack of effective interventions. While "the Amyloid Cascade Hypothesis," the abnormal accumulation of amyloid-β in the brain, has been the most prevalent theory for AD, mounting evidence from clinical and epidemiological studies suggest that defects in cerebral vessels and hypoperfusion appear prior to other pathological manifestations and might contribute to AD, leading to "the Vascular Hypothesis." However, assessment of structural and functional integrity of the cerebral vasculature in vivo in the brain from AD rodent models has been challenging owing to the limited spatiotemporal resolution of conventional imaging technologies.

Methods

We employed two in vivo imaging technologies, i.e., Dual-Wavelength Imaging (DWI) and Optical Coherence Tomography (OCT), to evaluate cerebrovascular reactivity (CVR; responsiveness of blood vessels to vasoconstriction as triggered by cocaine) in a relatively large field of view of the cortex in vivo, and 3D quantitative cerebrovascular blood flow (CBF) imaging in living transgenic AD mice at single vessel resolution.

Results

Our results showed significantly impaired CVR and reduced CBF in basal state in transgenic AD mice compared to non-transgenic littermates in an early stage of AD progression. Changes in total hemoglobin (Δ[HbT]) in response to vasoconstriction were significantly attenuated in AD mice, especially in arteries and tissue, and the recovery time of Δ[HbT] after vasoconstriction was shorter for AD than WT in all types of vessels and cortical tissue, thereby indicating hypoperfusion and reduced vascular flexibility. Additionally, our 3D OCT images revealed that CBF velocities in arteries were slower and that the microvascular network was severely disrupted in the brain of AD mice.

Conclusions

These results suggest significant vascular impairment in basal CBF and dynamic CVR in the neurovascular network in a rodent model of AD at an early stage of the disease. These cutting-edge in vivo optical imaging tools offer an innovative venue for detecting early neurovascular dysfunction in relation to AD pathology and pave the way for clinical translation of early diagnosis and elucidation of AD pathogenesis in the future.

A selection and targeting framework of cortical locations for line-scanning fMRI

Depth-resolved functional magnetic resonance imaging (fMRI) is an emerging field growing in popularity given the potential of separating signals from different computational processes in cerebral cortex. Conventional acquisition schemes suffer from low spatial and temporal resolutions. Line-scanning methods allow depth-resolved fMRI by sacrificing spatial coverage to sample blood oxygenated level-dependent (BOLD) responses at ultra-high temporal and spatial resolution. For neuroscience applications, it is critical to be able to place the line accurately to (1) sample the right neural population and (2) target that neural population with tailored stimuli or tasks. To this end, we devised a multi-session framework where a target cortical location is selected based on anatomical and functional properties. The line is then positioned according to this information in a separate second session, and we tailor the experiment to focus on the target location. Anatomically, the precision of the line placement was confirmed by projecting a nominal representation of the acquired line back onto the surface. Functional estimates of neural selectivities in the line, as quantified by a visual population-receptive field model, resembled the target selectivities well for most subjects. This functional precision was quantified in detail by estimating the distance between the visual field location of the targeted vertex and the location in visual cortex (V1) that most closely resembled the line-scanning estimates; this distance was on average ~5.5 mm. Given the dimensions of the line, differences in acquisition, session, and stimulus design, this validates that line-scanning can be used to probe local neural sensitivities across sessions. In summary, we present an accurate framework for line-scanning MRI; we believe such a framework is required to harness the full potential of line-scanning and maximize its utility. Furthermore, this approach bridges canonical fMRI experiments with electrophysiological experiments, which in turn allows novel avenues for studying human physiology non-invasively.

Denoising task-correlated head motion from motor-task fMRI data with multi-echo ICA

Motor-task functional magnetic resonance imaging (fMRI) is crucial in the study of several clinical conditions, including stroke and Parkinson's disease. However, motor-task fMRI is complicated by task-correlated head motion, which can be magnified in clinical populations and confounds motor activation results. One method that may mitigate this issue is multi-echo independent component analysis (ME-ICA), which has been shown to separate the effects of head motion from the desired BOLD signal but has not been tested in motor-task datasets with high amounts of motion. In this study, we collected an fMRI dataset from a healthy population who performed a hand grasp task with and without task-correlated amplified head motion to simulate a motor-impaired population. We analyzed these data using three models: single-echo (SE), multi-echo optimally combined (ME-OC), and ME-ICA. We compared the models' performance in mitigating the effects of head motion on the subject level and group level. On the subject level, ME-ICA better dissociated the effects of head motion from the BOLD signal and reduced noise. Both ME models led to increased t-statistics in brain motor regions. In scans with high levels of motion, ME-ICA additionally mitigated artifacts and increased stability of beta coefficient estimates, compared to SE. On the group level, all three models produced activation clusters in expected motor areas in scans with both low and high motion, indicating that group-level averaging may also sufficiently resolve motion artifacts that vary by subject. These findings demonstrate that ME-ICA is a useful tool for subject-level analysis of motor-task data with high levels of task-correlated head motion. The improvements afforded by ME-ICA are critical to improve reliability of subject-level activation maps for clinical populations in which group-level analysis may not be feasible or appropriate, for example in a chronic stroke cohort with varying stroke location and degree of tissue damage.

Region- and time- specific effects of ketamine on cerebral blood flow: a randomized controlled trial

There is intriguing evidence suggesting that ketamine might have distinct acute and delayed neurofunctional effects, as its acute administration transiently induces schizophrenia-like symptoms, while antidepressant effects slowly emerge and are most pronounced 24 h after administration. Studies attempting to characterize ketamine's mechanism of action by using blood oxygen level dependent (BOLD) imaging have yielded inconsistent results regarding implicated brain regions and direction of effects. This may be due to intrinsic properties of the BOLD contrast, while cerebral blood flow (CBF), as measured with arterial spin labeling, is a single physiological marker more directly related to neural activity. As effects of acute ketamine challenge are sensitive to modulation by pretreatment with lamotrigine, which inhibits glutamate release, a combination of these approaches should be particularly suited to offer novel insights. In total, 75 healthy participants were investigated in a double blind, placebo-controlled, randomized, parallel-group study and underwent two scanning sessions (acute/post 24 h.). Acute ketamine administration was associated with higher perfusion in interior frontal gyrus (IFG) and dorsolateral prefrontal cortex (DLPFC), but no other investigated brain region. Inhibition of glutamate release by pretreatment with lamotrigine abolished ketamine's effect on perfusion. At the delayed time point, pretreatment with lamotrigine was associated with lower perfusion in IFG. These findings underscore the idea that regionally selective patterns of CBF changes reflect proximate effects of modulated glutamate release on neuronal activity. Furthermore, region- specific sustained effects indicate both a swift restoration of disturbed homeostasis in DLPFC as well changes occurring beyond the immediate effects on glutamate signaling in IFG.

Confounding Effects on the Performance of Machine Learning Analysis of Static Functional Connectivity Computed from rs-fMRI Multi-site Data

Resting-state functional magnetic resonance imaging (rs-fMRI) is a non-invasive imaging technique widely used in neuroscience to understand the functional connectivity of the human brain. While rs-fMRI multi-site data can help to understand the inner working of the brain, the data acquisition and processing of this data has many challenges. One of the challenges is the variability of the data associated with different acquisitions sites, and different MRI machines vendors. Other factors such as population heterogeneity among different sites, with variables such as age and gender of the subjects, must also be considered. Given that most of the machine-learning models are developed using these rs-fMRI multi-site data sets, the intrinsic confounding effects can adversely affect the generalizability and reliability of these computational methods, as well as the imposition of upper limits on the classification scores. This work aims to identify the phenotypic and imaging variables producing the confounding effects, as well as to control these effects. Our goal is to maximize the classification scores obtained from the machine learning analysis of the Autism Brain Imaging Data Exchange (ABIDE) rs-fMRI multi-site data. To achieve this goal, we propose novel methods of stratification to produce homogeneous sub-samples of the 17 ABIDE sites, as well as the generation of new features from the static functional connectivity values, using multiple linear regression models, ComBat harmonization models, and normalization methods. The main results obtained with our statistical models and methods are an accuracy of 76.4%, sensitivity of 82.9%, and specificity of 77.0%, which are 8.8%, 20.5%, and 7.5% above the baseline classification scores obtained from the machine learning analysis of the static functional connectivity computed from the ABIDE rs-fMRI multi-site data.

Is the Brainstem Activation Different Between Healthy Young Male and Female Volunteers at Initiation of Voiding? A High Definition 7-Tesla Magnetic Resonance Imaging Study

PURPOSE

Assessing brainstem function in humans through typical neuroimaging modalities has been challenging. Our objective was to evaluate brain and brainstem activation patterns during initiation of voiding in healthy males and females utilizing a 7 Tesla magnetic resonance imaging (MRI) scanner and a noninvasive brain-bladder functional MRI (fMRI) protocol.

METHODS

Twenty healthy adult volunteers (10 males and 10 females) with no history of urinary symptoms were recruited. Each volunteer underwent a clinic uroflow and postvoid residual assessment and was asked to consume water prior to entering the scanner. Anatomical and diffusion tensor images were obtained first, followed by a blood oxygenation level dependent (BOLD) resting-state fMRI (rs-fMRI) during the empty bladder. Subjects indicated when they felt the urge to void, and a full bladder rs-fMRI was obtained. Once completed, the subjects began 5 voiding cycles, where the first 7.5 seconds of each voiding cycle was identified as "initiation of voiding." BOLD activation maps were generated, and regions of interests with a t-value greater than 2.1 were deemed statistically significant.

RESULTS

We present 5 distinct regions within the periaqueductal gray (PAG) and pontine micturition center (PMC) with statistically significant activation associated with an initiation of voiding in both men and women, 3 within the PAG and 2 within the PMC. Several additional areas in the brain also demonstrated activation as well. When comparing males to females, there was an overall lower BOLD activation seen in females throughout all regions, with the exception of the caudate lobe.

CONCLUSION

Our study effectively defines regions within the PAG and PMC involved in initiation of voiding in healthy volunteers. To our knowledge, this is the first study investigating differences between male and female brainstem activation utilizing an ultra-high definition 7T MRI.

In Vivo Imaging of Tumor Hypoxia by Maintaining Green Fluorescence of 9-Aminoanthracene Under Hypoxic Conditions

In this study, 9-aminoanthracene (9AA) was used as a new fluorescence reagent for the in vivo imaging of tumor hypoxia by taking advantage of the maintenance of its green fluorescence under hypoxic conditions. As 9AA is insoluble in water, polyethylene glycol (PEG)-400 was used to dissolve 9AA in saline. Each organ was successfully stained with 9AA, as observed by green fluorescence using in vivo imaging, following intragastric administration of a 9AA PEG-saline solution in mice. Therefore, the intragastric administration of 9AA can be used for in vivo imaging of normal mice. Tumor hypoxia staining using the 9AA fluorescence method was evaluated by in vivo imaging of mice subcutaneously transplanted with Ehrlich ascites carcinoma cells and compared with conventional pimonidazole (PIMO) staining under hypoxic conditions. The tumor sections were stained with green fluorescence derived from 9AA and the same sections corresponded to hypoxic areas upon immunohistochemical staining with PIMO.

Connectomics as a prognostic tool of functional outcome in glioma surgery of the supplementary motor area: illustrative case

BACKGROUND

The supplementary motor area (SMA) is essential in facilitating the commencement and coordination of complex self-initiated movements. Its complex functional connectivity poses a great risk for postoperative neurological deterioration. SMA syndrome can occur after tumor resection and comprises hemiakinesia and akinetic mutism (often, but unpredictably temporary). Although awake surgery is preferred for mapping and monitoring eloquent areas, connectomics is emerging as a novel technique to tailor neurosurgical approaches and predict functional prognosis, as illustrated in this case.

OBSERVATIONS

The authors report on a patient presenting with recurrent oligodendroglioma after subtotal resection 7 years earlier. After extensive neuropsychological and neuroradiological assessment (including connectomics), awake surgery was indicated. No intraoperative deficits were recorded; however, the patient presented with postoperative right-sided akinesia and mutism. Postoperative neuroimaging demonstrated the connectome overlapping the preoperative one, and indeed, neurological symptoms resolved after 3 days.

LESSONS

Comparison of the pre- and postoperative connectome can be used to objectively evaluate surgical outcomes and assess patient prognosis. To the best of the authors' knowledge, this is the first case demonstrating the feasibility of quantitative functional connectivity analysis as a prognostic tool for neurological improvement after surgery. A better understanding of brain networks is instrumental for improving diagnosis, prognosis, and treatment of neuro-oncological patients.

Cerebral oxygen metabolism from MRI susceptibility

This article provides an overview of MRI methods exploiting magnetic susceptibility properties of blood to assess cerebral oxygen metabolism, including the tissue oxygen extraction fraction (OEF) and the cerebral metabolic rate of oxygen (CMRO2). The first section is devoted to describing blood magnetic susceptibility and its effect on the MRI signal. Blood circulating in the vasculature can have diamagnetic (oxyhemoglobin) or paramagnetic properties (deoxyhemoglobin). The overall balance between oxygenated and deoxygenated hemoglobin determines the induced magnetic field which, in turn, modulates the transverse relaxation decay of the MRI signal via additional phase accumulation. The following sections of this review then illustrate the principles underpinning susceptibility-based techniques for quantifying OEF and CMRO2. Here, it is detailed whether these techniques provide global (OxFlow) or local (Quantitative Susceptibility Mapping - QSM, calibrated BOLD - cBOLD, quantitative BOLD - qBOLD, QSM+qBOLD) measurements of OEF or CMRO2, and what signal components (magnitude or phase) and tissue pools they consider (intravascular or extravascular). Validations studies and potential limitations of each method are also described. The latter include (but are not limited to) challenges in the experimental setup, the accuracy of signal modeling, and assumptions on the measured signal. The last section outlines the clinical uses of these techniques in healthy aging and neurodegenerative diseases and contextualizes these reports relative to results from gold-standard PET.

QSM Throughout the Body

Magnetic materials in tissue, such as iron, calcium, or collagen, can be studied using quantitative susceptibility mapping (QSM). To date, QSM has been overwhelmingly applied in the brain, but is increasingly utilized outside the brain. QSM relies on the effect of tissue magnetic susceptibility sources on the MR signal phase obtained with gradient echo sequence. However, in the body, the chemical shift of fat present within the region of interest contributes to the MR signal phase as well. Therefore, correcting for the chemical shift effect by means of water-fat separation is essential for body QSM. By employing techniques to compensate for cardiac and respiratory motion artifacts, body QSM has been applied to study liver iron and fibrosis, heart chamber blood and placenta oxygenation, myocardial hemorrhage, atherosclerotic plaque, cartilage, bone, prostate, breast calcification, and kidney stone.

Imaging the brain and vascular reactions to headache treatments: a systematic review

BACKGROUND

Neuroimaging studies have made an important contribution to our understanding of headache pathophysiology. This systematic review aims to provide a comprehensive overview and critical appraisal of mechanisms of actions of headache treatments and potential biomarkers of treatment response disclosed by imaging studies.

MAIN BODY

We performed a systematic literature search on PubMed and Embase databases for imaging studies investigating central and vascular effects of pharmacological and non-pharmacological treatments used to abort and prevent headache attacks. Sixty-three studies were included in the final qualitative analysis. Of these, 54 investigated migraine patients, 4 cluster headache patients and 5 patients with medication overuse headache. Most studies used functional magnetic resonance imaging (MRI) (n = 33) or molecular imaging (n = 14). Eleven studies employed structural MRI and a few used arterial spin labeling (n = 3), magnetic resonance spectroscopy (n = 3) or magnetic resonance angiography (n = 2). Different imaging modalities were combined in eight studies. Despite of the variety of imaging approaches and results, some findings were consistent. This systematic review suggests that triptans may cross the blood-brain barrier to some extent, though perhaps not sufficiently to alter the intracranial cerebral blood flow. Acupuncture in migraine, neuromodulation in migraine and cluster headache patients, and medication withdrawal in patients with medication overuse headache could promote headache improvement by reverting headache-affected pain processing brain areas. Yet, there is currently no clear evidence for where each treatment acts, and no firm imaging predictors of efficacy. This is mainly due to a scarcity of studies and heterogeneous treatment schemes, study designs, subjects, and imaging techniques. In addition, most studies used small sample sizes and inadequate statistical approaches, which precludes generalizable conclusions.

CONCLUSION

Several aspects of headache treatments remain to be elucidated using imaging approaches, such as how pharmacological preventive therapies work, whether treatment-related brain changes may influence therapy effectiveness, and imaging biomarkers of clinical response. In the future, well-designed studies with homogeneous study populations, adequate sample sizes and statistical approaches are needed.

Brightening the Study of Listening Effort with Functional Near-Infrared Spectroscopy: A Scoping Review

Listening effort is a long-standing area of interest in auditory cognitive neuroscience. Prior research has used multiple techniques to shed light on the neurophysiological mechanisms underlying listening during challenging conditions. Functional near-infrared spectroscopy (fNIRS) is growing in popularity as a tool for cognitive neuroscience research, and its recent advances offer many potential advantages over other neuroimaging modalities for research related to listening effort. This review introduces the basic science of fNIRS and its uses for auditory cognitive neuroscience. We also discuss its application in recently published studies on listening effort and consider future opportunities for studying effortful listening with fNIRS. After reading this article, the learner will know how fNIRS works and summarize its uses for listening effort research. The learner will also be able to apply this knowledge toward generation of future research in this area.

Simultaneous multislice imaging with slice-specific z-shim

PURPOSE

To implement slice-specific z-shim in simultaneous multislice (SMS) imaging in order to minimize signal losses in slice-accelerated T₂ *-weighted acquisitions, such as for spinal cord functional neuroimaging.

METHODS

The RF envelopes of the individual slice bands are temporally shifted on the plateau of the slice-selection gradient pulse before being combined to the multiband RF envelope. Thus, optimum z-shims can be realized for each slice of an SMS excitation, which is in contrast to conventional z-shimming. EPI with 2-fold SMS acceleration was performed on a 3T whole-body MR system in phantoms and the cervical spinal cord of healthy volunteers (i) without z-shim, (ii) with conventional z-shim using the average value of the slices of the SMS excitation, and (iii) with optimal, slice-specific z-shims for each slice using envelope shifts.

RESULTS

Phantom experiments demonstrate the equivalence of the envelope shift and conventional z-shimming for non-SMS excitations. With SMS, the best image quality is obtained with "mixed" z-shim, where only the z-shim differences of the slices of an SMS excitation are implemented by an envelope shift while their mean z-shim is applied conventionally with a gradient pulse after the echoes acquired for N/2 ghost correction. In phantoms and in vivo, this setup outperforms the approaches without slice-specific z-shim with respect to signal amplitude and temporal SNR at the expense of slight TE differences (<1 ms) between the slices.

CONCLUSION

With RF envelope shifts, slice-specific z-shims can be combined with SMS imaging, which could improve slice-accelerated functional neuroimaging in the spinal cord.

Differential Laminar Activation Dissociates Encoding and Retrieval in the Human Medial and Lateral Entorhinal Cortex

The hierarchically organized structures of the medial temporal lobe are critically important for episodic memory function. Accumulating evidence suggests dissociable information processing pathways are maintained throughout these structures including in the medial and lateral entorhinal cortex. Cortical layers provide an additional dimension of dissociation as the primary input to the hippocampus derives from layer 2 neurons in the entorhinal cortex, whereas the deeper layers primarily receive output from the hippocampus. Here, novel high-resolution T2-prepared functional MRI methods were successfully used to mitigate susceptibility artifacts typically affecting MRI signals in this region providing uniform sensitivity across the medial and lateral entorhinal cortex. During the performance of a memory task, healthy human subjects (age 25-33 years, mean age 28.2 ± 3.3 years, 4 female) showed differential functional activation in the superficial and deep layers of the entorhinal cortex associated with task-related encoding and retrieval conditions, respectively. The methods provided here offer an approach to probe layer-specific activation in normal cognition and conditions contributing to memory impairment.SIGNIFICANCE STATEMENT This study provides new evidence for differential neuronal activation in the superficial versus deep layers of the entorhinal cortex associated with encoding and retrieval memory processes, respectively, in cognitively normal adults. The study further shows that this dissociation can be observed in both the medial and the lateral entorhinal cortex. The study was achieved by using a novel functional MRI method allowing us to measure robust functional MRI signals in both the medial and lateral entorhinal cortex that was not possible in previous studies. The methodology established here in healthy human subjects lays a solid foundation for subsequent studies investigating layer-specific and region-specific changes in the entorhinal cortex associated with memory impairment in various conditions such as Alzheimer's disease.

Blood oxygenation-level dependent cerebrovascular reactivity imaging as strategy to monitor CSF-hemoglobin toxicity

OBJECTIVES

Cell-free hemoglobin in the cerebrospinal fluid (CSF-Hb) may be one of the main drivers of secondary brain injury after aneurysmal subarachnoid hemorrhage (aSAH). Haptoglobin scavenging of CSF-Hb has been shown to mitigate cerebrovascular disruption. Using digital subtraction angiography (DSA) and blood oxygenation-level dependent cerebrovascular reactivity imaging (BOLD-CVR) the aim was to assess the acute toxic effect of CSF-Hb on cerebral blood flow and autoregulation, as well as to test the protective effects of haptoglobin.

METHODS

DSA imaging was performed in eight anesthetized and ventilated sheep (mean weight: 80.4 kg) at baseline, 15, 30, 45 and 60 minutes after infusion of hemoglobin (Hb) or co-infusion with haptoglobin (Hb:Haptoglobin) into the left lateral ventricle. Additionally, 10 ventilated sheep (mean weight: 79.8 kg) underwent BOLD-CVR imaging to assess the cerebrovascular reserve capacity.

RESULTS

DSA imaging did not show a difference in mean transit time or cerebral blood flow. Whole-brain BOLD-CVR compared to baseline decreased more in the Hb group after 15 minutes (Hb vs Hb:Haptoglobin: -0.03 ± 0.01 vs -0.01 ± 0.02) and remained diminished compared to Hb:Haptoglobin group after 30 minutes (Hb vs Hb:Haptoglobin: -0.03 ± 0.01 vs 0.0 ± 0.01), 45 minutes (Hb vs Hb:Haptoglobin: -0.03 ± 0.01 vs 0.01 ± 0.02) and 60 minutes (Hb vs Hb:Haptoglobin: -0.03 ± 0.02 vs 0.01 ± 0.01).

CONCLUSION

It is demonstrated that CSF-Hb toxicity leads to rapid cerebrovascular reactivity impairment, which is blunted by haptoglobin co-infusion. BOLD-CVR may therefore be further evaluated as a monitoring strategy for CSF-Hb toxicity after aSAH.

BigBrain-MR: a new digital phantom with anatomically-realistic magnetic resonance properties at 100-µm resolution for magnetic resonance methods development

The benefits, opportunities and growing availability of ultra-high field magnetic resonance imaging (MRI) for humans have prompted an expansion in research and development efforts towards increasingly more advanced high-resolution imaging techniques. To maximize their effectiveness, these efforts need to be supported by powerful computational simulation platforms that can adequately reproduce the biophysical characteristics of MRI, with high spatial resolution. In this work, we have sought to address this need by developing a novel digital phantom with realistic anatomical detail up to 100-µm resolution, including multiple MRI properties that affect image generation. This phantom, termed BigBrain-MR, was generated from the publicly available BigBrain histological dataset and lower-resolution in-vivo 7T-MRI data, using a newly-developed image processing framework that allows mapping the general properties of the latter into the fine anatomical scale of the former. Overall, the mapping framework was found to be effective and robust, yielding a diverse range of realistic "in-vivo-like" MRI contrasts and maps at 100-µm resolution. BigBrain-MR was then tested in three imaging applications (motion effects and interpolation, super-resolution imaging, and parallel imaging reconstruction) to investigate its properties, value and validity as a simulation platform. The results consistently showed that BigBrain-MR can closely approximate the behavior of real in-vivo data, more realistically and with more extensive features than a more classic option such as the Shepp-Logan phantom. Its flexibility in simulating different contrast mechanisms and artifacts may also prove valuable for educational applications. BigBrain-MR is therefore deemed a favorable choice to support methodological development and demonstration in brain MRI, and has been made freely available to the community.

Improving T2*-weighted human cortico-spinal acquisitions with a dedicated algorithm for region-wise shimming

Cortico-spinal fMRI acquisitions aim to investigate direct interactions between brain and spinal cord, e.g. during motor output or pain processing, by covering both regions in a single measurement. Due to their large distance and location in the body, a dynamic shim update of constant and linear shim terms is required when using echo-planar imaging (EPI) to achieve reasonable image quality in both target regions. A previously presented approach with region-wise shim settings is based on a standard single-region shim algorithm and suffers from (i) non-optimal shim settings because it combines linear and second-order shim terms optimized for different volumes, and (ii) significant user interactions making it rather cumbersome, time consuming, and error-prone. Here, a dedicated ("CoSpi") shim algorithm for cortico-spinal fMRI is presented that performs joint optimization of static second-order shim terms and one set of linear and constant shim terms for each region in a single run and with minimal user interaction. Field map and T2*-weighted EPI measurements were performed on a clinical 3 T whole-body MR system in water phantoms and five healthy volunteers using the conventional region-wise and CoSpi shim settings as well as "gold standard" shim settings optimized for one of the target regions only. With CoSpi shim settings, (i) overall field inhomogeneity was reduced by about 65% / 75% (brain / spinal cord volume) compared to the conventional region-wise approach and in vivo was within 5% of the values obtained with the single-volume shim settings, (ii) geometric distortions derived from voxel displacement maps were reduced on average by about 35% / 70%, (iii) the temporal SNR determined from an EPI time series that may reflect the impact of through-slice dephasing, was increased by about 17% / 10%, and (iv) the variation of the mean field between slices, a measure targeting the predisposition to insufficient fat saturation and GRAPPA-related ghosting artifacts, was reduced by about 90% / 45%. Thus, the presented algorithm not only speeds up and simplifies the shim procedure considerably, but also provides a better field homogeneity and image quality, which both could help to significantly improve the applicability of cortico-spinal fMRI.

Monitoring kidney size to interpret MRI-based assessment of renal oxygenation in acute pathophysiological scenarios

AIM

Tissue hypoxia is an early key feature of acute kidney injury. Assessment of renal oxygenation using magnetic resonance imaging (MRI) markers T₂ and T₂ * enables insights into renal pathophysiology. This assessment can be confounded by changes in the blood and tubular volume fractions, occurring upon pathological insults. These changes are mirrored by changes in kidney size (KS). Here, we used dynamic MRI to monitor KS for physiological interpretation of T₂ * and T₂ changes in acute pathophysiological scenarios.

METHODS

KS was determined from T₂ *, T₂ mapping in rats. Six interventions that acutely alter renal tissue oxygenation were performed directly within the scanner, including interventions that change the blood and/or tubular volume. A biophysical model was used to estimate changes in O₂ saturation of hemoglobin from changes in T₂ * and KS.

RESULTS

Upon aortic occlusion KS decreased; this correlated with a decrease in T₂ *, T₂ . Upon renal vein occlusion KS increased; this negatively correlated with a decrease in T₂ *, T₂ . Upon simultaneous occlusion of both vessels KS remained unchanged; there was no correlation with decreased T₂ *, T₂ . Hypoxemia induced mild reductions in KS and T₂ *, T₂ . Administration of an X-ray contrast medium induced sustained KS increase, with an initial increase in T₂ *, T₂ followed by a decrease. Furosemide caused T₂ *, T₂ elevation and a minor increase in KS. Model calculations yielded physiologically plausible calibration ratios for T₂ *.

CONCLUSION

Monitoring KS allows physiological interpretation of acute renal oxygenation changes obtained by T₂ *, T₂ . KS monitoring should accompany MRI-oximetry, for new insights into renal pathophysiology and swift translation into human studies.

What imaging has revealed about migraine and chronic migraine

Although migraine pathophysiology is not yet entirely understood, it is now established that migraine should be viewed as a complex neurological disease, which involves the interplay of different brain networks and the release of signaling molecules, instead of a pure vascular disorder. The field of migraine research has also progressed significantly due to the advancement of brain imaging techniques. Numerous studies have investigated the relation between migraine pathophysiology and cerebral hemodynamic changes, showing that vascular changes are neither necessary nor sufficient to cause the migraine pain. Abnormal function and structure of key cortical, subcortical, and brainstem regions involved in multisensory, including pain, processing have been shown to occur in migraine patients during both an acute attack and the interictal phase. Whether brain imaging alterations represent a predisposing trait or are the consequence of the recurrence of headache attacks is still a matter of debate. It is highly likely that brain functional and structural alterations observed in migraine patients derive from the interaction between predisposing brain traits and experience-dependent responses. Neuroimaging studies have also enriched our knowledge of the mechanisms responsible for migraine chronification and have shed light on the mechanisms of actions of acute and preventive migraine treatments.

The Role of fMRI in Drug Development: An Update

Functional magnetic resonance imaging (fMRI) of the brain is a technology that holds great potential for increasing the efficiency of drug development for the central nervous system (CNS). In preclinical studies and both early- and late-phase human trials, fMRI has the potential to improve cross-species translation of drug effects, help to de-risk compounds early in development, and contribute to the portfolio of evidence for a compound's efficacy and mechanism of action. However, to date, the utilization of fMRI in the CNS drug development process has been limited. The purpose of this chapter is to explore this mismatch between potential and utilization. This chapter provides introductory material related to fMRI and drug development, describes what is required of fMRI measurements for them to be useful in a drug development setting, lists current capabilities of fMRI in this setting and challenges faced in its utilization, and ends with directions for future development of capabilities in this arena. This chapter is the 5-year update of material from a previously published workshop summary (Carmichael et al., Drug DiscovToday 23(2):333-348, 2018).

Mouse Brain MRI: Including In Vivo, Ex Vivo, and fcMRI for the Study of Microcephaly

With its sensitivity to soft tissue, MRI is a powerful tool for the study of the neuroanatomical manifestations of a variety of conditions, such as microcephaly-related morbidities that are not easily visualized by other imaging techniques, such as CT. In addition to structural imaging, more recently, researchers have found changes in brain function in a wide range of neurological conditions-highlighting the utility of MRI for the study of microcephaly.In this methods chapter, basic mouse preparation and the acquisition of data for in vivo anatomical MRI will be discussed. Additionally, we will provide our protocol for the perfusion and fixation of brain tissue with gadolinium contrast agent. Following that, the process of optimization of system parameters will be shown for anatomical imaging of in vivo and ex vivo brain tissue. Lastly, the chapter will detail a protocol for fcMRI along with a discussion of considerations specific to functional imaging.

Improved laminar specificity and sensitivity by combining SE and GE BOLD signals

The most widely used gradient-echo (GE) blood oxygenation level-dependent (BOLD) contrast has high sensitivity, but low specificity due to draining vein contributions, while spin-echo (SE) BOLD approach at ultra-high magnetic fields is highly specific to neural active sites but has lower sensitivity. To obtain high specificity and sensitivity, we propose to utilize a vessel-size-sensitive filter to the GE-BOLD signal, which suppresses macrovascular contributions and to combine selectively retained microvascular GE-BOLD signals with the SE-BOLD signals. To investigate our proposed idea, fMRI with 0.8 mm isotropic resolution was performed on the primary motor and sensory cortices in humans at 7 T by implementing spin- and gradient-echo (SAGE) echo planar imaging (EPI) acquisition. Microvascular-passed sigmoidal filters were designed based upon the vessel-size-sensitive ΔR₂*/ΔR₂ value for retaining GE-BOLD signals originating from venous vessels with ≤ 45 μm and ≤ 65 μm diameter. Unlike GE-BOLD fMRI, the laminar profile of SAGE-BOLD fMRI with the vessel-size-sensitive filter peaked at ∼ 1.0 mm from the surface of the primary motor and sensory cortices, demonstrating an improvement of laminar specificity over GE-BOLD fMRI. Also, the functional sensitivity of SAGE BOLD at middle layers (0.75-1.5 mm) was improved by ∼ 80% to ∼100% when compared with SE BOLD. In summary, we showed that combined GE- and SE-BOLD fMRI with the vessel-size-sensitive filter indeed yielded improved laminar specificity and sensitivity and is therefore an excellent tool for high spatial resolution ultra-high filed (UHF)-fMRI studies for resolving mesoscopic functional units.

The "Effort Elephant" in the Room: What Is Effort, Anyway?

Despite decades of research in the fields of judgment and decision-making, social psychology, cognitive psychology, human-machine interaction, behavioral economics, and neuroscience, we still do not know what "cognitive effort" is. The definitions in use are often imprecise and sometimes diametrically opposed. Researchers with different assumptions talk past each other, and many aspects of effort conservation remain untested and difficult to measure. In this article, we explain why effort is so difficult to pin down and why it is important that researchers develop consensus on precise definitions. Next, we describe major "hidden" sources of miscommunication: areas in which researchers disagree in their underlying assumptions about the nature of effort without realizing it. We briefly review a number of methods used to both measure and manipulate the effortfulness of thinking and highlight why they often produce contradictory findings. We conclude by reviewing existing perspectives on cognitive effort and integrating them to suggest a common framework for communicating about effort as a limited cognitive resource.

Review of the Research Progress of Human Brain Oxygen Extraction Fraction by Magnetic Resonance Imaging

In recent years, the incidence of cerebrovascular diseases (CVD) is increasing, which seriously endangers human health. The study on hemodynamics of cerebrovascular disease can help us to understand, prevent, and treat the disease. As one of the important parameters of human cerebral hemodynamics and tissue metabolism, OEF (oxygen extraction fraction) is of great value in central nervous system diseases. The use of BOLD (blood oxygen level dependent) effect offers the possibility to study cerebral hemodynamic and metabolic characteristics by MRI (magnetic resonance imaging) measurements. Therefore, this paper reviews the hemodynamic parameters of brain tissue, discusses the principles and methods of quantitative BOLD-based MRI measurements of OEF, and discusses the advantages and disadvantages of each method.

Static and dynamic BOLD fMRI components along white matter fibre tracts and their dependence on the orientation of the local diffusion tensor axis relative to the B0-field

Recent studies have reported functional MRI (fMRI) activation within cerebral white matter (WM) using blood-oxygenation-level-dependent (BOLD) contrast. Many blood vessels in WM run parallel to the fibre bundles, and other studies observed dependence of susceptibility contrast-based measures of blood volume on the local orientation of the fibre bundles relative to the magnetic field or B₀ axis. Motivated by this, we characterized the dependence of gradient-echo BOLD fMRI on fibre orientation (estimated by the local diffusion tensor) relative to the B₀ axis to test whether the alignment between bundles and vessels imparts an orientation dependence on resting-state BOLD fluctuations in the WM. We found that the baseline signal level of the T₂*-weighted data is 11% higher in voxels containing fibres parallel to B₀ than those containing perpendicular fibres, consistent with a static influence of either fibre or vessel orientation on local T₂* values. We also found that BOLD fluctuations in most bundles exhibit orientation effects expected from oxygenation changes, with larger amplitudes from voxels containing perpendicular fibres. Different magnitudes of this orientation effect were observed across the major WM bundles, with inferior fasciculus, corpus callosum and optic radiation exhibiting 14-19% higher fluctuations in voxels containing perpendicular compared to parallel fibres.

Increase in thalamic cerebral blood flow is associated with antidepressant effects of ketamine in major depressive disorder

Ketamine is a promising treatment option for patients with Major Depressive Disorder (MDD) and has become an important research tool to investigate antidepressant mechanisms of action. However, imaging studies attempting to characterise ketamine's mechanism of action using blood oxygen level-dependent signal (BOLD) imaging have yielded inconsistent results- at least partly due to intrinsic properties of the BOLD contrast, which measures a complex signal related to neural activity. To circumvent the limitations associated with the BOLD signal, we used arterial spin labelling (ASL) as an unambiguous marker of neuronal activity-related changes in cerebral blood flow (CBF). We measured CBF in 21 MDD patients at baseline and 24 h after receiving a single intravenous infusion of subanesthetic ketamine and examined relationships with clinical outcomes. Our findings demonstrate that increase in thalamus perfusion 24 h after ketamine administration is associated with greater improvement of depressive symptoms. Furthermore, lower thalamus perfusion at baseline is associated both with larger increases in perfusion 24 h after ketamine administration and with stronger reduction of depressive symptoms. These findings indicate that ASL is not only a useful tool to broaden our understanding of ketamine's mechanism of action but might also have the potential to inform treatment decisions based on CBF-defined regional disruptions.

What has vision science taught us about functional MRI?

In the domain of human neuroimaging, much attention has been paid to the question of whether and how the development of functional magnetic resonance imaging (fMRI) has advanced our scientific knowledge of the human brain. However, the opposite question is also important; how has our knowledge of the visual system advanced our understanding of fMRI? Here, we discuss how and why scientific knowledge about the human and animal visual system has been used to answer fundamental questions about fMRI as a brain measurement tool and how these answers have contributed to scientific discoveries beyond vision science.

A flow-diffusion model of oxygen transport for quantitative mapping of cerebral metabolic rate of oxygen (CMRO2) with single gas calibrated fMRI

One promising approach for mapping CMRO₂ is dual-calibrated functional MRI (dc-fMRI). This method exploits the Fick Principle to combine estimates of CBF from ASL, and OEF derived from BOLD-ASL measurements during arterial O₂ and CO₂ modulations. Multiple gas modulations are required to decouple OEF and deoxyhemoglobin-sensitive blood volume. We propose an alternative single gas calibrated fMRI framework, integrating a model of oxygen transport, that links blood volume and CBF to OEF and creates a mapping between the maximum BOLD signal, CBF and OEF (and CMRO₂). Simulations demonstrated the method's viability within physiological ranges of mitochondrial oxygen pressure, P_mO₂, and mean capillary transit time. A dc-fMRI experiment, performed on 20 healthy subjects using O₂ and CO₂ challenges, was used to validate the approach. The validation conveyed expected estimates of model parameters (e.g., low P_mO₂), with spatially uniform OEF maps (grey matter, GM, OEF spatial standard deviation ≈ 0.13). GM OEF estimates obtained with hypercapnia calibrated fMRI correlated with dc-fMRI (r = 0.65, p = 2·10^-3). For 12 subjects, OEF measured with dc-fMRI and the single gas calibration method were correlated with whole-brain OEF derived from phase measures in the superior sagittal sinus (r = 0.58, p = 0.048; r = 0.64, p = 0.025 respectively). Simplified calibrated fMRI using hypercapnia holds promise for clinical application.

Toward Completely Sampled Extracellular Neural Recording During fMRI

This work aims to estimate severe fMRI scanning artifacts in extracellular neural recordings made at ultrahigh magnetic field strengths in order to remove the artifact interferences and uncover the complete neural electrophysiology signal. We build on previous work that used PCA to denoise EEG recorded during fMRI, adapting it to cover the much larger frequency range (1-6000 Hz) of the extracellular field potentials (EFPs) observed by extracellular neural recordings. We examine the singular value decomposition (SVD)-PCA singular value shrinkage (SVS) and compare two shrinkage rules and a sliding template subtraction approach. Additionally, we present a new technique for estimating the singular value upper bounds in spontaneous neural activity recorded in the isoflurane anesthetized rat that uses the temporal first difference of the neural signal. The approaches are tested on artificial datasets to examine their efficacy in detecting extracellular action potentials (EAPs: 300-6000 Hz) recorded during fMRI gradient interferences. Our results indicate that it is possible to uncover the EAPs recorded during gradient interferences. The methods are then tested on natural (non-artificial) datasets recorded from the cortex of isoflurane anesthetized rats, where both local field potential (LFP: 1-300 Hz) and EAP signals are analyzed. The SVS methods are shown to be advantageous compared to sliding template subtraction, especially in the high frequency range corresponding to EAPs. Our novel approach moves us towards simultaneous fMRI and completely sampled neural recording (1-6000Hz with no temporal gaps), providing the opportunity for further study of spontaneous brain function and neurovascular coupling at ultrahigh field in the isoflurane anesthetized rat.

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.

NeoRS: A Neonatal Resting State fMRI Data Preprocessing Pipeline

Resting state functional MRI (rsfMRI) has been shown to be a promising tool to study intrinsic brain functional connectivity and assess its integrity in cerebral development. In neonates, where functional MRI is limited to very few paradigms, rsfMRI was shown to be a relevant tool to explore regional interactions of brain networks. However, to identify the resting state networks, data needs to be carefully processed to reduce artifacts compromising the interpretation of results. Because of the non-collaborative nature of the neonates, the differences in brain size and the reversed contrast compared to adults due to myelination, neonates can’t be processed with the existing adult pipelines, as they are not adapted. Therefore, we developed NeoRS, a rsfMRI pipeline for neonates. The pipeline relies on popular neuroimaging tools (FSL, AFNI, and SPM) and is optimized for the neonatal brain. The main processing steps include image registration to an atlas, skull stripping, tissue segmentation, slice timing and head motion correction and regression of confounds which compromise functional data interpretation. To address the specificity of neonatal brain imaging, particular attention was given to registration including neonatal atlas type and parameters, such as brain size variations, and contrast differences compared to adults. Furthermore, head motion was scrutinized, and motion management optimized, as it is a major issue when processing neonatal rsfMRI data. The pipeline includes quality control using visual assessment checkpoints. To assess the effectiveness of NeoRS processing steps we used the neonatal data from the Baby Connectome Project dataset including a total of 10 neonates. NeoRS was designed to work on both multi-band and single-band acquisitions and is applicable on smaller datasets. NeoRS also includes popular functional connectivity analysis features such as seed-to-seed or seed-to-voxel correlations. Language, default mode, dorsal attention, visual, ventral attention, motor and fronto-parietal networks were evaluated. Topology found the different analyzed networks were in agreement with previously published studies in the neonate. NeoRS is coded in Matlab and allows parallel computing to reduce computational times; it is open-source and available on GitHub (https://github.com/venguix/NeoRS). NeoRS allows robust image processing of the neonatal rsfMRI data that can be readily customized to different datasets.

Task- and resting-state fMRI studies in multiple sclerosis: From regions to systems and time-varying analysis. Current status and future perspective

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Functional MRI is able to detect adaptive and maladaptive abnormalities at different MS stages.

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Increased fMRI activity is a feature of early MS, while progressive exhaustion of adaptive mechanisms is detected later on in the disease.

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Collapse of long-range connections and impaired hub integration characterize MS network reorganization.

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Time-varying connectivity analysis provides useful and complementary pieces of information to static functional connectivity.

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New perspectives might be the use of multimodal MRI and artificial intelligence.

Multiple sclerosis (MS) is a neurological disorder affecting the central nervous system and features extensive functional brain changes that are poorly understood but relate strongly to clinical impairments. Functional magnetic resonance imaging (fMRI) is a non-invasive, powerful technique able to map activity of brain regions and to assess how such regions interact for an efficient brain network. FMRI has been widely applied to study functional brain changes in MS, allowing to investigate functional plasticity consequent to disease-related structural injury. The first studies in MS using active fMRI tasks mainly aimed to study such plastic changes by identifying abnormal activity in salient brain regions (or systems) involved by the task. In later studies the focus shifted towards resting state (RS) functional connectivity (FC) studies, which aimed to map large-scale functional networks of the brain and to establish how MS pathology impairs functional integration, eventually leading to the hypothesized network collapse as patients clinically progress. This review provides a summary of the main findings from studies using task-based and RS fMRI and illustrates how functional brain alterations relate to clinical disability and cognitive deficits in this condition. We also give an overview of longitudinal studies that used task-based and RS fMRI to monitor disease evolution and effects of motor and cognitive rehabilitation. In addition, we discuss the results of studies using newer technologies involving time-varying FC to investigate abnormal dynamism and flexibility of network configurations in MS. Finally, we show some preliminary results from two recent topics (i.e., multimodal MRI analysis and artificial intelligence) that are receiving increasing attention. Together, these functional studies could provide new (conceptual) insights into disease stage-specific mechanisms underlying progression in MS, with recommendations for future research.

Ultrashort time-to-echo T2* and T2* relaxometry for evaluation of lumbar disc degeneration: a comparative study

Background

To compare potential of ultrashort time-to-echo (UTE) T2* mapping and T2* values from T2*-weighted imaging for assessing lumbar intervertebral disc degeneration (IVDD),with Pfirrmann grading as a reference standard.

Methods

UTE-T2* and T2* values of 366 lumbar discs (L1/2-L5/S1) in 76 subjects were measured in 3 segmented regions: anterior annulus fibrosus, nucleus pulposus (NP), and posterior annulus fibrosus. Lumbar intervertebral discs were divided into 3 categories based on 5-level Pfirrmann grading: normal (Pfirrmann grade I),early disc degeneration (Pfirrmann grades II-III), and advanced disc degeneration (Pfirrmann grades IV-V). Regional differences between UTE-T2* and T2* relaxometry and correlation with degeneration were statistically analyzed.

Results

UTE-T2* and T2*value correlated negatively with Pfirrmann grades (P < 0.001). In NP, correlations with Pfirrmann grade were high with UTE-T2* values (r =  − 0.733; P < 0.001) and moderate with T2* values (r = -0.654; P < 0.001). Diagnostic accuracy of detecting early IVDD was better with UTE-T2* mapping than T2* mapping (P < 0.05),with receiver operating characteristic analysis area under the curve of 0.715–0.876.

Conclusions

UTE-T2* relaxometry provides another promising magnetic resonance imaging sequence for quantitatively evaluate lumbar IVDD and was more accurate than T2*mapping in the earlier stage degenerative process.