On the characteristics of functional magnetic resonance imaging of the brain

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.

Analysis of Resting-State Functional Magnetic Resonance Imaging in Alzheimer's Disease

Alzheimer's disease (AD) has been characterized by widespread network disconnection among brain regions, widely overlapping with the hallmarks of the disease. Functional connectivity has been studied with an upward trend in the last two decades, predominantly in AD among other neuropsychiatric disorders, and presents a potential biomarker with various features that might provide unique contributions to foster our understanding of neural mechanisms of AD. The resting-state functional MRI (rs-fMRI) is usually used to measure the blood-oxygen-level-dependent signals that reflect the brain's functional connectivity. Nevertheless, the rs-fMRI is still underutilized, which might be due to the fairly complex acquisition and analytic methodology. In this chapter, we presented the common methods that have been applied in rs-fMRI literature, focusing on the studies on individuals in the continuum of AD. The key methodological aspects will be addressed that comprise acquiring, processing, and interpreting rs-fMRI data. More, we discussed the current and potential implications of rs-fMRI in AD.

Multimodal magnetic resonance scans of patients with mild cognitive impairment

The advancement of neuroimaging technology offers a pivotal reference for the early detection of mild cognitive impairment (MCI), a significant area of focus in contemporary cognitive function research. Structural MRI scans present visual and quantitative manifestations of alterations in brain tissue, whereas functional MRI scans depict the metabolic and functional state of brain tissues from diverse perspectives. As various magnetic resonance techniques possess both strengths and constraints, this review examines the methodologies and outcomes of multimodal magnetic resonance technology in MCI diagnosis, laying the groundwork for subsequent diagnostic and therapeutic interventions for MCI.

Machine-Learning Methods for Speech and Handwriting Detection Using Neural Signals: A Review

Brain-Computer Interfaces (BCIs) have become increasingly popular in recent years due to their potential applications in diverse fields, ranging from the medical sector (people with motor and/or communication disabilities), cognitive training, gaming, and Augmented Reality/Virtual Reality (AR/VR), among other areas. BCI which can decode and recognize neural signals involved in speech and handwriting has the potential to greatly assist individuals with severe motor impairments in their communication and interaction needs. Innovative and cutting-edge advancements in this field have the potential to develop a highly accessible and interactive communication platform for these people. The purpose of this review paper is to analyze the existing research on handwriting and speech recognition from neural signals. So that the new researchers who are interested in this field can gain thorough knowledge in this research area. The current research on neural signal-based recognition of handwriting and speech has been categorized into two main types: invasive and non-invasive studies. We have examined the latest papers on converting speech-activity-based neural signals and handwriting-activity-based neural signals into text data. The methods of extracting data from the brain have also been discussed in this review. Additionally, this review includes a brief summary of the datasets, preprocessing techniques, and methods used in these studies, which were published between 2014 and 2022. This review aims to provide a comprehensive summary of the methodologies used in the current literature on neural signal-based recognition of handwriting and speech. In essence, this article is intended to serve as a valuable resource for future researchers who wish to investigate neural signal-based machine-learning methods in their work.

Application of DTI and fMRI in moyamoya disease

Moyamoya disease (MMD) is a chronic and progressive cerebrovascular stenosis or occlusive disease that occurs near Willis blood vessels. Diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) are used to detect the microstructure of white matter and the function of gray matter, respectively. The damage of these structures will lead to the change of cognitive level in patients with moyamoya disease. In this paper, the principles of DTI and fMRI, their applications and challenges in moyamoya disease are reviewed.

Brain Structural and Functional Alterations in Multiple Sclerosis-Related Fatigue: A Systematic Review

Fatigue is one of the most disabling symptoms of multiple sclerosis (MS); it influences patients’ quality of life. The etiology of fatigue is complex, and its pathogenesis is still unclear and debated. The objective of this review was to describe potential brain structural and functional dysfunctions underlying fatigue symptoms in patients with MS. To reach this purpose, a systematic review was conducted of published studies comparing functional brain activation and structural brain in MS patients with and without fatigue. Electronic databases were searched until 24 February 2021. The structural and functional outcomes were extracted from eligible studies and tabulated. Fifty studies were included: 32 reported structural brain differences between patients with and without fatigue; 14 studies described functional alterations in patients with fatigue compared to patients without it; and four studies showed structural and functional brain alterations in patients. The results revealed structural and functional abnormalities that could correlate to the symptom of fatigue in patients with MS. Several studies reported the differences between patients with fatigue and patients without fatigue in terms of conventional magnetic resonance imaging (MRI) outcomes and brain atrophy, specifically in the thalamus. Functional studies showed abnormal activation in the thalamus and in some regions of the sensorimotor network in patients with fatigue compared to patients without it. Patients with fatigue present more structural and functional alterations compared to patients without fatigue. Specifically, abnormal activation and atrophy of the thalamus and some regions of the sensorimotor network seem linked to fatigue.

Abnormal percent amplitude of fluctuation changes in patients with monocular blindness: A resting-state functional magnetic resonance imaging study

PURPOSE

Previous studies on monocular blindness (MB) have mainly focused on concept and impact. The present study measured spontaneous brain activity in MB patients using the percentage of amplitude fluctuation (PerAF) method.

METHODS

Twenty-nine patients with MB (21 male and 8 female) and 29 age-, gender-, and weight-matched healthy controls (HCs) were recruited. All participants underwent resting state functional magnetic resonance imaging (rs-fMRI). The PerAF method was used to analyze the data and evaluate the spontaneous regional brain activity. The ability of PerAF values to distinguish patients with MB from HCs was analyzed using receiver operating characteristic (ROC) curves, and correlation analysis was used to assess the relationship between PerAF values of brain regions and the Hospital Anxiety and Depression Scale (HADS) scores.

RESULTS

PerAF values in Occipital_Mid_L/Occipital_Mid_R/Cingulum_ Mid_L were significantly lower in patients with MB than in controls. Conversely, values in the Frontal_Sup_Orb_L/Frontal_Inf_Orb_L/Temporal _Inf_L/Frontal_Inf_Oper_L were significantly higher in MB patients than in HCs. And the AUC of ROC curves were follows: 0.904, (p < 0.0001; 95%CI: 0.830-0.978) for Frontal_Sup_Orb_L/Frontal_Inf_Orb_L; Temporal_Inf_L 0.883, (p < 0.0001; 95% CI: 0.794-0.972); Frontal_Inf_Oper_L 0.964, (p < 0.0001; 95% CI: 0.924-1.000), and 0.893 (p < 0.0001; 95% CI: 0.812-0.973) for Occipital_Mid_L; Occipital_Mid_R 0.887, (p < 0.0001; 95% CI: 0.802-0.971); Cingulum_Mid_L 0.855, (p < 0.0001; 95% CI: 0.750-0.960).

CONCLUSION

The results of our study show abnormal activity in some brain regions in patients with MB, indicating that these patients may be at risk of disorder related to these brain regions. These results may reflect the neuropathological mechanisms of MB and facilitate early MB diagnoses.

Arterial blood stealing as a mechanism of negative BOLD response: From the steady-flow with nonlinear phase separation to a windkessel-based model

Blood Oxygen Level Dependent (BOLD) signal indirectly characterizes neuronal activity by measuring hemodynamic and metabolic changes in the nearby microvasculature. A deeper understanding of how localized changes in electrical, metabolic and hemodynamic factors translate into a BOLD signal is crucial for the interpretation of functional brain imaging techniques. While positive BOLD responses (PBR) are widely considered to be linked with neuronal activation, the origins of negative BOLD responses (NBR) have remained largely unknown. As NBRs are sometimes observed in close proximity of regions with PBR, a blood "stealing" effect, i.e., redirection of blood from a passive periphery to the area with high neuronal activity, has been postulated. In this study, we used the Hagen-Poiseuille equation to model hemodynamics in an idealized microvascular network that account for the particulate nature of blood and nonlinearities arising from the red blood cell (RBC) distribution (i.e., the Fåhraeus, Fåhraeus-Lindqvist and the phase separation effects). Using this detailed model, we evaluate determinants driving this "stealing" effect in a microvascular network with geometric parameters within physiological ranges. Model simulations predict that during localized cerebral blood flow (CBF) increases due to neuronal activation-hyperemic response, blood from surrounding vessels is reallocated towards the activated region. This stealing effect depended on the resistance of the microvasculature and the uneven distribution of RBCs at vessel bifurcations. A parsimonious model consisting of two-connected windkessel regions sharing a supplying artery was proposed to simulate the stealing effect with a minimum number of parameters. Comparison with the detailed model showed that the parsimonious model can reproduce the observed response for hematocrit values within the physiological range for different species. Our novel parsimonious model promise to be of use for statistical inference (top-down analysis) from direct blood flow measurements (e.g., arterial spin labeling and laser Doppler/Speckle flowmetry), and when combined with theoretical models for oxygen extraction/diffusion will help account for some types of NBRs.

Maternal perinatal anxiety and neural responding to infant affective signals: Insights, challenges, and a road map for neuroimaging research

Anxiety symptoms are common among women during pregnancy and the postpartum period, potentially having detrimental effects on both mother and child's well-being. Perinatal maternal anxiety interferes with a core facet of adaptive caregiving: mothers' sensitive responsiveness to infant affective communicative 'cues.' This review summarizes the current research on the neural correlates of maternal processing of infant cues in the presence of perinatal anxiety, outlines its limitations, and offers next steps to advance future research. Functional neuroimaging studies examining the neural circuitry involved in, and electrophysiological studies examining the temporal dynamics of, processing infant cues during pregnancy and postpartum are reviewed. Studies have generally indicated mixed findings, although emerging themes suggest that anxiety may be implicated in several stages of processing infant cues- detection, interpretation, and reaction- contingent upon cue valence. Limitations include inconsistent designs, lack of differentiation between anxiety and depression symptoms, and limited consideration of parenting-specific (versus domain-general) anxiety. Future studies should incorporate longitudinal investigation of multiple levels of analysis spanning neural, cognitive, and observed aspects of sensitive caregiving.

Neurovascular Coupling in Development and Disease: Focus on Astrocytes

Neurovascular coupling is a crucial mechanism that matches the high energy demand of the brain with a supply of energy substrates from the blood. Signaling within the neurovascular unit is responsible for activity-dependent changes in cerebral blood flow. The strength and reliability of neurovascular coupling form the basis of non-invasive human neuroimaging techniques, including blood oxygen level dependent (BOLD) functional magnetic resonance imaging. Interestingly, BOLD signals are negative in infants, indicating a mismatch between metabolism and blood flow upon neural activation; this response is the opposite of that observed in healthy adults where activity evokes a large oversupply of blood flow. Negative neurovascular coupling has also been observed in rodents at early postnatal stages, further implying that this is a process that matures during development. This rationale is consistent with the morphological maturation of the neurovascular unit, which occurs over a similar time frame. While neurons differentiate before birth, astrocytes differentiate postnatally in rodents and the maturation of their complex morphology during the first few weeks of life links them with synapses and the vasculature. The vascular network is also incomplete in neonates and matures in parallel with astrocytes. Here, we review the timeline of the structural maturation of the neurovascular unit with special emphasis on astrocytes and the vascular tree and what it implies for functional maturation of neurovascular coupling. We also discuss similarities between immature astrocytes during development and reactive astrocytes in disease, which are relevant to neurovascular coupling. Finally, we close by pointing out current gaps in knowledge that must be addressed to fully elucidate the mechanisms underlying neurovascular coupling maturation, with the expectation that this may also clarify astrocyte-dependent mechanisms of cerebrovascular impairment in neurodegenerative conditions in which reduced or negative neurovascular coupling is noted, such as stroke and Alzheimer’s disease.

Estimation of simultaneous BOLD and dynamic FDG metabolic brain activations using a multimodality concatenated ICA (mcICA) method

Simultaneous magnetic resonance and positron emission tomography provides an opportunity to measure brain haemodynamics and metabolism in a single scan session, and to identify brain activations from multimodal measurements in response to external stimulation. However, there are few analysis methods available for jointly analysing the simultaneously acquired blood-oxygen-level dependant functional MRI (fMRI) and 18-F-fluorodeoxyglucose functional PET (fPET) datasets. In this work, we propose a new multimodality concatenated ICA (mcICA) method to identify joint fMRI-fPET brain activations in response to a visual stimulation task. The mcICA method produces a fused map from the multimodal datasets with equal contributions of information from both modalities, measured by entropy. We validated the method in silico, and applied it to an in vivo visual stimulation experiment. The mcICA method estimated the activated brain regions in the visual cortex modulated by both BOLD and FDG signals. The mcICA provides a fully data-driven analysis approach to analyse cerebral haemodynamic response and glucose uptake signals arising from exogenously induced neuronal activity.

Quality and denoising in real-time functional magnetic resonance imaging neurofeedback: A methods review

Neurofeedback training using real-time functional magnetic resonance imaging (rtfMRI-NF) allows subjects voluntary control of localised and distributed brain activity. It has sparked increased interest as a promising non-invasive treatment option in neuropsychiatric and neurocognitive disorders, although its efficacy and clinical significance are yet to be determined. In this work, we present the first extensive review of acquisition, processing and quality control methods available to improve the quality of the neurofeedback signal. Furthermore, we investigate the state of denoising and quality control practices in 128 recently published rtfMRI-NF studies. We found: (a) that less than a third of the studies reported implementing standard real-time fMRI denoising steps, (b) significant room for improvement with regards to methods reporting and (c) the need for methodological studies quantifying and comparing the contribution of denoising steps to the neurofeedback signal quality. Advances in rtfMRI-NF research depend on reproducibility of methods and results. Notably, a systematic effort is needed to build up evidence that disentangles the various mechanisms influencing neurofeedback effects. To this end, we recommend that future rtfMRI-NF studies: (a) report implementation of a set of standard real-time fMRI denoising steps according to a proposed COBIDAS-style checklist (https://osf.io/kjwhf/), (b) ensure the quality of the neurofeedback signal by calculating and reporting community-informed quality metrics and applying offline control checks and (c) strive to adopt transparent principles in the form of methods and data sharing and support of open-source rtfMRI-NF software. Code and data for reproducibility, as well as an interactive environment to explore the study data, can be accessed at https://github.com/jsheunis/quality-and-denoising-in-rtfmri-nf.

A response-locking protocol to boost sensitivity for fMRI-based neurochronometry

The timeline of brain‐wide neural activity relative to a behavioral event is crucial when decoding the neural implementation of a cognitive process. Yet, fMRI assesses neural processes indirectly via delayed and regionally variable hemodynamics. This method‐inherent temporal distortion impacts the interpretation of behavior‐linked neural timing. Here we describe a novel behavioral protocol that aims at disentangling the BOLD dynamics of the pre‐ and post‐response periods in response time tasks. We tested this response‐locking protocol in a perceptual decision‐making (random dot) task. Increasing perceptual difficulty produced expected activity increases over a broad network involving the lateral/medial prefrontal cortex and the anterior insula. However, response‐locking revealed a previously unreported functional dissociation within this network. preSMA and anterior premotor cortex (prePMV) showed post‐response activity modulations while anterior insula and anterior cingulate cortex did not. Furthermore, post‐response BOLD activity at preSMA showed a modulation in timing but not amplitude while this pattern was reversed at prePMV. These timeline dissociations with response‐locking thus revealed three functionally distinct sub‐networks in what was seemingly one shared distributed network modulated by perceptual difficulty. These findings suggest that our novel response‐locked protocol could boost the timing‐related sensitivity of fMRI.

Functional MRI in Children: Current Clinical Applications

Functional magnetic resonance imaging has become a critical research tool for evaluating brain function during active tasks and resting states. This has improved our understanding of developmental trajectories in children as well as the plasticity of neural networks in disease states. In the clinical setting, functional maps of eloquent cortex in patients with brain lesions and/or epilepsy provides crucial information for presurgical planning. Although children are inherently challenging to scan in this setting, preparing them appropriately and providing adequate resources can help achieve useful clinical data. This article will review the basic underlying physiologic aspects of functional magnetic resonance imaging, review clinically relevant research applications, describe known validation data compared to gold standard techniques and detail future directions of this technology.

Diffusion tensor imaging combined with T2 mapping to quantify changes in the skeletal muscle associated with training and endurance exercise in competitive triathletes

OBJECTIVES

Diffusion tensor magnetic resonance imaging (DTI) and T2 mapping enable the detection of exercise-induced changes in the skeletal muscle microenvironment. This study prospectively quantified DTI metrics and T2 relaxation times of thigh muscles in competitive triathletes at rest and following a triathlon race in comparison with sedentary controls.

METHODS

Twenty-two triathletes (males N = 16, females N = 6) and twenty-three controls (males N = 16, females N = 7) underwent magnetic resonance imaging (MRI) on a 3 T system at baseline (time point 1; 72 h at rest). Twelve triathletes (males N = 8, females N = 4) underwent a second scan (time point 2; 3 h of completing a triathlon race). The tensor eigenvalues (λ₁, λ₂, λ₃), mean diffusivity (MD), fractional anisotropy (FA), and T2 times were compared between controls and triathletes at time point 1 and triathletes at time points 1 and 2 using independent and paired t tests.

RESULTS

In comparison with the controls at time point 1, the T2 times of rectus femoris (RF, p < 0.02), adductor magnus (AM, p = 0.02), biceps femoris (BF, p < 0.001), semitendinosus (ST, p = 0.005), and semimembranosus (SM, p = 0.003) muscles were significantly increased in triathletes. At time point 2 in triathletes, the average tensor metrics (MD, λ₃/ λ₁) of BF, ST, and SM muscles increased (p < 0.05) and FA values in ST and SM muscles decreased (p < 0.03). T2 times were not significantly changed between both time points in triathletes.

CONCLUSION

Our results indicate that this multiparametric MRI protocol allows detection and quantification of changes in the skeletal muscle microenvironment caused by endurance training and acute strenuous exercise.

KEY POINTS

• Endurance training results in changes to the skeletal microstructure, which can be quantified using MRI-based diffusion tensor imaging. • The combined application of MRI diffusion tensor imaging and T2 mapping allows the differentiation of microstructural changes caused by active exercise or endurance training. • Environmental adaptations of the skeletal muscle caused by physical training are influenced by gender.

Axial variation of deoxyhemoglobin density as a source of the low-frequency time lag structure in blood oxygenation level-dependent signals

Perfusion-related information is reportedly embedded in the low-frequency component of a blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signal. The blood-propagation pattern through the cerebral vascular tree is detected as an interregional lag variation of spontaneous low-frequency oscillations (sLFOs). Mapping of this lag, or phase, has been implicitly treated as a projection of the vascular tree structure onto real space. While accumulating evidence supports the biological significance of this signal component, the physiological basis of the “perfusion lag structure,” a requirement for an integrative resting-state fMRI-signal model, is lacking. In this study, we conducted analyses furthering the hypothesis that the sLFO is not only largely of systemic origin, but also essentially intrinsic to blood, and hence behaves as a virtual tracer. By summing the small fluctuations of instantaneous phase differences between adjacent vascular regions, a velocity response to respiratory challenges was detected. Regarding the relationship to neurovascular coupling, the removal of the whole lag structure, which can be considered as an optimized global-signal regression, resulted in a reduction of inter-individual variance while preserving the fMRI response. Examination of the T2* and S₀, or non-BOLD, components of the fMRI signal revealed that the lag structure is deoxyhemoglobin dependent, while paradoxically presenting a signal-magnitude reduction in the venous side of the cerebral vasculature. These findings provide insight into the origin of BOLD sLFOs, suggesting that they are highly intrinsic to the circulating blood.

Gradient-echo and spin-echo blood oxygenation level-dependent functional MRI at ultrahigh fields of 9.4 and 15.2 Tesla

Purpose

Sensitivity and specificity of blood oxygenation level–dependent (BOLD) functional MRI (fMRI) is sensitive to magnetic field strength and acquisition methods. We have investigated gradient‐echo (GE)‐ and spin‐echo (SE)‐BOLD fMRI at ultrahigh fields of 9.4 and 15.2  Tesla.

Methods

BOLD fMRI experiments responding to forepaw stimulation were performed with 3 echo times (TE) at each echo type and B₀ in α‐chloralose–anesthetized rats. The contralateral forelimb somatosensory region was selected for quantitative analyses.

Results

At 9.4 T and 15.2 T, average baseline T₂^* (n = 9) was 26.6 and 17.1 msec, whereas baseline T₂ value (n = 9) was 35.7 and 24.5 msec, respectively. Averaged stimulation‐induced ΔR₂^* was –1.72 s^–1 at 9.4 T and –3.09 s^–1 at 15.2 T, whereas ΔR₂ was –1.19 s^–1 at 9.4 T and –1.97 s^–1 at 15.2 T. At the optimal TE of tissue T₂^* or T₂, BOLD percent changes were slightly higher at 15.2 T than at 9.4 T (GE: 7.4% versus 6.4% and SE: 5.7% versus 5.4%). The ΔR₂^* and ΔR₂ ratio of 15.2 T to 9.4 T was 1.8 and 1.66, respectively. The ratio of the macrovessel‐containing superficial to microvessel‐dominant parenchymal BOLD signal was 1.73 to 1.76 for GE‐BOLD versus 1.13 to 1.19 for SE‐BOLD, indicating that the SE‐BOLD contrast is less sensitive to macrovessels than GE‐BOLD.

Conclusion

SE‐BOLD fMRI improves spatial specificity to microvessels compared to GE‐BOLD at both fields. BOLD sensitivity is similar at the both fields and can be improved at ultrahigh fields only for thermal‐noise–dominant ultrahigh‐resolution fMRI.

Optogenetic astrocyte activation evokes BOLD fMRI response with oxygen consumption without neuronal activity modulation

Functional magnetic resonance imaging (fMRI) based on the blood oxygenation level-dependent (BOLD) signal has been used to infer sites of neuronal activation in the brain. A recent study demonstrated, however, unexpected BOLD signal generation without neuronal excitation, which led us to hypothesize the presence of another cellular source for BOLD signal generation. Collective assessment of optogenetic activation of astrocytes or neurons, fMRI in awake mice, electrophysiological measurements, and histochemical detection of neuronal activation, coherently suggested astrocytes as another cellular source. Unexpectedly, astrocyte-evoked BOLD signal accompanied oxygen consumption without modulation of neuronal activity. Imaging mass spectrometry of brain sections identified synthesis of acetyl-carnitine via oxidative glucose metabolism at the site of astrocyte-, but not neuron-evoked BOLD signal. Our data provide causal evidence that astrocytic activation alone is able to evoke BOLD signal response, which may lead to reconsideration of current interpretation of BOLD signal as a marker of neuronal activation.

Implications of structural and functional brain changes in amyotrophic lateral sclerosis

INTRODUCTION

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease that causes progressive muscle weakness and disability, eventually leading to death. Heterogeneity of disease has become a major barrier to understanding key clinical questions such as prognosis and disease spread, and has disadvantaged clinical trials in search of therapeutic intervention. Patterns of disease have been explored through recent advances in neuroimaging, elucidating structural, molecular and functional changes. Unique brain signatures have emerged that have lent a greater understanding of critical disease mechanisms, offering opportunities to improve diagnosis, guide prognosis, and establish candidate biomarkers to direct future therapeutic strategies. Areas covered: This review explores patterns of cortical and subcortical change in ALS through advanced neuroimaging techniques and discusses the implications of these findings. Expert commentary: Cortical and subcortical signatures and patterns of atrophy are now consistently recognised, providing important pathophysiological insight into this heterogenous disease. The spread of cortical change, particularly involving frontotemporal networks, correlates with cognitive impairment and poorer prognosis. Cortical differences are also evident between ALS phenotypes and genotypes, which may partly explain the heterogeneity of prognosis. Ultimately, multimodal approaches with larger cohorts will be needed to provide sensitive biomarkers of disease spread at the level of the individual patient.

Establishing upper limits on neuronal activity-evoked pH changes with APT-CEST MRI at 7 T

Purpose

To detect neuronal activity–evoked pH changes by amide proton transfer–chemical exchange saturation transfer (APT‐CEST) MRI at 7 T.

Methods

Three healthy subjects participated in the study. A low‐power 3‐dimensional APT‐CEST sequence was optimized through the Bloch‐McConnell equations. pH sensitivity of the sequence was estimated both in phantoms and in vivo. The feasibility of pH–functional MRI was tested in Bloch‐McConnell‐simulated data using the optimized sequence. In healthy subjects, the visual stimuli were used to evoke transient pH changes in the visual cortex, and a 3‐dimensional APT‐CEST volume was acquired at the pH‐sensitive frequency offset of 3.5 ppm every 12.6 s.

Results

In theory, a three‐component general linear model was capable of separating the effects of blood oxygenation level–dependent contrast and pH. The Bloch‐McConnell equations indicated that a change in pH of 0.03 should be measurable at the experimentally determined temporal signal‐to‐noise ratio of 108. However, only a blood oxygenation level–dependent effect in the visual cortex could be discerned during the visual stimuli experiments performed in the healthy subjects.

Conclusions

The results of this study suggest that if indeed there are any transient brain pH changes in response to visual stimuli, those are under 0.03 units pH change, which is extremely difficult to detect using the existent techniques. Magn Reson Med 80:126–136, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

A proof-of-concept study for developing integrated two-photon microscopic and magnetic resonance imaging modality at ultrahigh field of 16.4 tesla

Functional magnetic resonance imaging (fMRI) based on the blood oxygen level dependent (BOLD) contrast has gained a prominent position in neuroscience for imaging neuronal activity and studying effective brain connectivity under working state and functional connectivity at resting state. However, the fundamental questions in regards to fMRI technology: how the BOLD signal inferences the underlying microscopic neuronal activity and physiological changes and what is the ultimate specificity of fMRI for functional mapping of microcircuits, remain unanswered. The capability of simultaneous fMRI measurement and functional microscopic imaging in a live brain thus holds the key to link the microscopic and mesoscopic neural dynamics to the macroscopic brain activity at the central nervous system level. Here we report the first demonstration to integrate high-resolution two-photon fluorescence microscopy (TPM) with a 16.4 tesla MRI system, which proves the concept and feasibility for performing simultaneous high-resolution fMRI and TPM imaging at ultrahigh magnetic field.

Foundations of layer-specific fMRI and investigations of neurophysiological activity in the laminarized neocortex and olfactory bulb of animal models

Laminar organization of neuronal circuits is a recurring feature of how the brain processes information. For instance, different layers compartmentalize different cell types, synaptic activities, and have unique intrinsic and extrinsic connections that serve as units for specialized signal processing. Functional MRI is an invaluable tool to investigate laminar processing in the in vivo human brain, but it measures neuronal activity indirectly by way of the hemodynamic response. Therefore, the accuracy of high-resolution laminar fMRI depends on how precisely it can measure localized microvascular changes nearest to the site of evoked activity. To determine the specificity of fMRI responses to the true neurophysiological responses across layers, the flexibility to invasive procedures in animal models has been necessary. In this review, we will examine different fMRI contrasts and their appropriate uses for layer-specific fMRI, and how localized laminar processing was examined in the neocortex and olfactory bulb. Through collective efforts, it was determined that microvessels, including capillaries, are regulated within single layers and that several endogenous and contrast-enhanced fMRI contrast mechanisms can separate these neural-specific vascular changes from the nonspecific, especially cerebral blood volume-weighted fMRI with intravenous contrast agent injection. We will also propose some open questions that are relevant for the successful implementation of layer-specific fMRI and its potential future directions to study laminar processing when combined with optogenetics.

Overview of quantitative susceptibility mapping

Magnetic susceptibility describes the magnetizability of a material to an applied magnetic field and represents an important parameter in the field of MRI. With the recently introduced method of quantitative susceptibility mapping (QSM) and its conceptual extension to susceptibility tensor imaging (STI), the non-invasive assessment of this important physical quantity has become possible with MRI. Both methods solve the ill-posed inverse problem to determine the magnetic susceptibility from local magnetic fields. Whilst QSM allows the extraction of the spatial distribution of the bulk magnetic susceptibility from a single measurement, STI enables the quantification of magnetic susceptibility anisotropy, but requires multiple measurements with different orientations of the object relative to the main static magnetic field. In this review, we briefly recapitulate the fundamental theoretical foundation of QSM and STI, as well as computational strategies for the characterization of magnetic susceptibility with MRI phase data. In the second part, we provide an overview of current methodological and clinical applications of QSM with a focus on brain imaging. Copyright © 2016 John Wiley & Sons, Ltd.

Resting state fMRI: A review on methods in resting state connectivity analysis and resting state networks

The inquisitiveness about what happens in the brain has been there since the beginning of humankind. Functional magnetic resonance imaging is a prominent tool which helps in the non-invasive examination, localisation as well as lateralisation of brain functions such as language, memory, etc. In recent years, there is an apparent shift in the focus of neuroscience research to studies dealing with a brain at 'resting state'. Here the spotlight is on the intrinsic activity within the brain, in the absence of any sensory or cognitive stimulus. The analyses of functional brain connectivity in the state of rest have revealed different resting state networks, which depict specific functions and varied spatial topology. However, different statistical methods have been introduced to study resting state functional magnetic resonance imaging connectivity, yet producing consistent results. In this article, we introduce the concept of resting state functional magnetic resonance imaging in detail, then discuss three most widely used methods for analysis, describe a few of the resting state networks featuring the brain regions, associated cognitive functions and clinical applications of resting state functional magnetic resonance imaging. This review aims to highlight the utility and importance of studying resting state functional magnetic resonance imaging connectivity, underlining its complementary nature to the task-based functional magnetic resonance imaging.

Cerebral mechanism of puncturing at He-Mu point combination for functional dyspepsia: study protocol for a randomized controlled parallel trial

Acupuncture is widely used to treat functional dyspepsia with satisfactory outcomes. Combination of the He and Mu acupoints is commonly used and has a synergistic effect on functional dyspepsia; however, its underlying mechanisms remain unclear. Therefore, a randomized controlled parallel clinical trial is currently underway at Chengdu University of Traditional Chinese Medicine, China. This trial is designed to explore the efficacy of and central responses to the He-Mu point combination in patients with functional dyspepsia using functional magnetic resonance imaging. A total of 105 patients with functional dyspepsia will be allocated into 3 groups: the low-He point group (puncturing at Zusanli (ST36)), Mu point group (puncturing at Zhongwan (CV12)), and He-Mu point combination group (puncturing at ST36 and CV12). Every participant will receive 20 sessions of manual acupuncture for 4 weeks. The needles will be inserted perpendicularly to a depth of 1 to 2 cun. The angle of rotation and twisting will range from 90 to 180 degrees, while lifting and thrusting will range from 0.3 to 0.5 cm. The various manipulations will be performed 60 to 90 times per minute. The needles will remain in place for 30 minutes, during which manipulation will be applied every 10 minutes. Magnetic resonance imaging will be performed before and after 20 sessions of acupuncture. The primary outcome is symptom improvement according to the Chinese version of the Nepean Dyspepsia Index. Secondary outcomes include the Leeds dyspepsia questionnaire, Self-Rating Anxiety Scale, Self-Rating Depression Scale, Beck Anxiety Inventory, Beck Depression Inventory, and visual analogue scale scores before and after 10 and 20 sessions of acupuncture. Needle sensation and adverse events will be used to assess the therapeutic effects. This study will promote more widespread awareness of the benefits of acupoint combination in the clinical setting and provide a further explanation of the neuromechanism by which acupuncture at the He-Mu point combination for functional dyspepsia. Registration: Chinese Clinical Trial Registry, ChiCTR-IOR-15006402.

Post-contractile BOLD contrast in skeletal muscle at 7 T reveals inter-individual heterogeneity in the physiological responses to muscle contraction

Muscle blood oxygenation-level dependent (BOLD) contrast is greater in magnitude and potentially more influenced by extravascular BOLD mechanisms at 7 T than it is at lower field strengths. Muscle BOLD imaging of muscle contractions at 7 T could, therefore, provide greater or different contrast than at 3 T. The purpose of this study was to evaluate the feasibility of using BOLD imaging at 7 T to assess the physiological responses to in vivo muscle contractions. Thirteen subjects (four females) performed a series of isometric contractions of the calf muscles while being scanned in a Philips Achieva 7 T human imager. Following 2 s maximal isometric plantarflexion contractions, BOLD signal transients ranging from 0.3 to 7.0% of the pre-contraction signal intensity were observed in the soleus muscle. We observed considerable inter-subject variability in both the magnitude and time course of the muscle BOLD signal. A subset of subjects (n = 7) repeated the contraction protocol at two different repetition times (T_R : 1000 and 2500 ms) to determine the potential of T₁ -related inflow effects on the magnitude of the post-contractile BOLD response. Consistent with previous reports, there was no difference in the magnitude of the responses for the two T_R values (3.8 ± 0.9 versus 4.0 ± 0.6% for T_R  = 1000 and 2500 ms, respectively; mean ± standard error). These results demonstrate that studies of the muscle BOLD responses to contractions are feasible at 7 T. Compared with studies at lower field strengths, post-contractile 7 T muscle BOLD contrast may afford greater insight into microvascular function and dysfunction.

Kinesthetic Feedback During 2DOF Wrist Movements via a Novel MR-Compatible Robot

We demonstrate the interaction control capabilities of the MR-SoftWrist, a novel MR-compatible robot capable of applying accurate kinesthetic feedback to wrist pointing movements executed during fMRI. The MR-SoftWrist, based on a novel design that combines parallel piezoelectric actuation with compliant force feedback, is capable of delivering 1.5 N [Formula: see text] of torque to the wrist of an interacting subject about the flexion/extension and radial/ulnar deviation axes. The robot workspace, defined by admissible wrist rotation angles, fully includes a circle with a 20 deg radius. Via dynamic characterization, we demonstrate capability for transparent operation with low (10% of maximum torque output) backdrivability torques at nominal speeds. Moreover, we demonstrate a 5.5 Hz stiffness control bandwidth for a 14 dB range of virtual stiffness values, corresponding to 25%-125% of the device's physical reflected stiffness in the nominal configuration. We finally validate the possibility of operation during fMRI via a case study involving one healthy subject. Our validation experiment demonstrates the capability of the device to apply kinesthetic feedback to elicit distinguishable kinetic and neural responses without significant degradation of image quality or task-induced head movements. With this study, we demonstrate the feasibility of MR-compatible devices like the MR-SoftWrist to be used in support of motor control experiments investigating wrist pointing under robot-applied force fields. Such future studies may elucidate fundamental neural mechanisms enabling robot-assisted motor skill learning, which is crucial for robot-aided neurorehabilitation.

Multimodal EEG Recordings, Psychometrics and Behavioural Analysis

High spatial and temporal resolution measurements of neuronal activity are preferably combined. In an overview on how this approach can take shape, multimodal electroencephalography (EEG) is treated in 2 main parts: by experiments without a task and in the experimentally cued working brain. It concentrates first on the alpha rhythm properties and next on data-driven search for patterns such as the default mode network. The high-resolution volumic distributions of neuronal metabolic indices result in distributed cortical regions and possibly relate to numerous nuclei, observable in a non-invasive manner in the central nervous system of humans. The second part deals with paradigms in which nowadays assessment of target-related networks can align level-dependent blood oxygenation, electrical responses and behaviour, taking the temporal resolution advantages of event-related potentials. Evidence-based electrical propagation in serial tasks during performance is now to a large extent attributed to interconnected pathways, particularly chronometry-dependent ones, throughout a chain including a dorsal stream, next ventral cortical areas taking the flow of information towards inferior temporal domains. The influence of aging is documented, and results of the first multimodal studies in neuropharmacology are consistent. Finally a scope on implementation of advanced clinical applications and personalized marker strategies in neuropsychiatry is indicated.

MR Imaging-derived Oxygen-Hemoglobin Dissociation Curves and Fetal-Placental Oxygen-Hemoglobin Affinities

The authors of this study present a noninvasive approach for obtaining MR imaging–based oxygen-hemoglobin dissociation curves and for deriving oxygen tension values at which hemoglobin is 50% saturated and maps for the placenta and fetus in pregnant mice.

Purpose

To generate magnetic resonance (MR) imaging–derived, oxygen-hemoglobin dissociation curves and to map fetal-placental oxygen-hemoglobin affinity in pregnant mice noninvasively by combining blood oxygen level–dependent (BOLD) T2* and oxygen-weighted T1 contrast mechanisms under different respiration challenges.

Materials and Methods

All procedures were approved by the Weizmann Institutional Animal Care and Use Committee. Pregnant mice were analyzed with MR imaging at 9.4 T on embryonic days 14.5 (eight dams and 58 fetuses; imprinting control region ICR strain) and 17.5 (21 dams and 158 fetuses) under respiration challenges ranging from hyperoxia to hypoxia (10 levels of oxygenation, 100%–10%; total imaging time, 100 minutes). A shorter protocol with normoxia to hyperoxia was also performed (five levels of oxygenation, 20%–100%; total imaging time, 60 minutes). Fast spin-echo anatomic images were obtained, followed by sequential acquisition of three-dimensional gradient-echo T2*- and T1-weighted images. Automated registration was applied to align regions of interest of the entire placenta, fetal liver, and maternal liver. Results were compared by using a two-tailed unpaired Student t test. R1 and R2* values were derived for each tissue. MR imaging–based oxygen-hemoglobin dissociation curves were constructed by nonlinear least square fitting of 1 minus the change in R2*divided by R2*at baseline as a function of R1 to a sigmoid-shaped curve. The apparent P50 (oxygen tension at which hemoglobin is 50% saturated) value was derived from the curves, calculated as the R1 scaled value (x) at which the change in R2* divided by R2*at baseline scaled (y) equals 0.5.

Results

The apparent P50 values were significantly lower in fetal liver than in maternal liver for both gestation stages (day 14.5: 21% ± 5 [P = .04] and day 17.5: 41% ± 7 [P < .0001]). The placenta showed a reduction of 18% ± 4 in mean apparent P50 values from day 14.5 to day 17.5 (P = .003). Reproduction of the MR imaging–based oxygen-hemoglobin dissociation curves with a shorter protocol that excluded the hypoxic periods was demonstrated.

Conclusion

MR imaging–based oxygen-hemoglobin dissociation curves and oxygen-hemoglobin affinity information were derived for pregnant mice by using 9.4-T MR imaging, which suggests a potential to overcome the need for direct sampling of fetal or maternal blood.

Online supplemental material is available for this article.

7 tesla FMRI reveals systematic functional organization for binocular disparity in dorsal visual cortex

The binocular disparity between the views of the world registered by the left and right eyes provides a powerful signal about the depth structure of the environment. Despite increasing knowledge of the cortical areas that process disparity from animal models, comparatively little is known about the local architecture of stereoscopic processing in the human brain. Here, we take advantage of the high spatial specificity and image contrast offered by 7 tesla fMRI to test for systematic organization of disparity representations in the human brain. Participants viewed random dot stereogram stimuli depicting different depth positions while we recorded fMRI responses from dorsomedial visual cortex. We repeated measurements across three separate imaging sessions. Using a series of computational modeling approaches, we report three main advances in understanding disparity organization in the human brain. First, we show that disparity preferences are clustered and that this organization persists across imaging sessions, particularly in area V3A. Second, we observe differences between the local distribution of voxel responses in early and dorsomedial visual areas, suggesting different cortical organization. Third, using modeling of voxel responses, we show that higher dorsal areas (V3A, V3B/KO) have properties that are characteristic of human depth judgments: a simple model that uses tuning parameters estimated from fMRI data captures known variations in human psychophysical performance. Together, these findings indicate that human dorsal visual cortex contains selective cortical structures for disparity that may support the neural computations that underlie depth perception.

Comparing within-subject classification and regularization methods in fMRI for large and small sample sizes

In recent years, a variety of multivariate classifier models have been applied to fMRI, with different modeling assumptions. When classifying high-dimensional fMRI data, we must also regularize to improve model stability, and the interactions between classifier and regularization techniques are still being investigated. Classifiers are usually compared on large, multisubject fMRI datasets. However, it is unclear how classifier/regularizer models perform for within-subject analyses, as a function of signal strength and sample size. We compare four standard classifiers: Linear and Quadratic Discriminants, Logistic Regression and Support Vector Machines. Classification was performed on data in the linear kernel (covariance) feature space, and classifiers are tuned with four commonly-used regularizers: Principal Component and Independent Component Analysis, and penalization of kernel features using L₁ and L₂ norms. We evaluated prediction accuracy (P) and spatial reproducibility (R) of all classifier/regularizer combinations on single-subject analyses, over a range of three different block task contrasts and sample sizes for a BOLD fMRI experiment. We show that the classifier model has a small impact on signal detection, compared to the choice of regularizer. PCA maximizes reproducibility and global SNR, whereas Lp -norms tend to maximize prediction. ICA produces low reproducibility, and prediction accuracy is classifier-dependent. However, trade-offs in (P,R) depend partly on the optimization criterion, and PCA-based models are able to explore the widest range of (P,R) values. These trends are consistent across task contrasts and data sizes (training samples range from 6 to 96 scans). In addition, the trends in classifier performance are consistent for ROI-based classifier analyses.

Brain sparing in fetal mice: BOLD MRI and Doppler ultrasound show blood redistribution during hypoxia

Mice reproduce many features of human pregnancy and have been widely used to model disorders of pregnancy. However, it has not been known whether fetal mice reproduce the physiologic response to hypoxia known as brain sparing, where blood flow is redistributed to preserve oxygenation of the brain at the expense of other fetal organs. In the present study, blood oxygen level-dependent (BOLD) magnetic resonance imaging (MRI) and Doppler ultrasound were used to determine the effect of acute hypoxia on the fetal blood flow in healthy, pregnant mice. As the maternal inspired gas mixture was varied between 100% and 8% oxygen on the timescale of minutes, the BOLD signal intensity decreased by 44±18% in the fetal liver and by 12±7% in the fetal brain. Using Doppler ultrasound measurements, mean cerebral blood velocity was observed to rise by 15±8% under hypoxic conditions relative to hyperoxia. These findings are consistent with active regulation of cerebral oxygenation and clearly show brain sparing in fetal mice.

Solid MRI contrast agents for long-term, quantitative in vivo oxygen sensing

Targeted MRI contrast agents have proven useful in research and clinical studies for highlighting specific metabolites and biomarkers [Davies GL, et al. (2013) Chem Commun (Camb) 49(84):9704-9721] but their applicability in serial imaging is limited owing to a changing concentration postinjection. Solid enclosures have previously been used to keep the local concentration of contrast agent constant, but the need to surgically implant these devices limits their use [Daniel K, et al. (2009) Biosens Bioelectron 24(11):3252-3257]. This paper describes a novel class of contrast agent that comprises a responsive material for contrast generation and an injectable polymeric matrix for structural support. Using this principle, we have designed a contrast agent sensitive to oxygen, which is composed of dodecamethylpentasiloxane as the responsive material and polydimethylsiloxane as the matrix material. A rodent inspired-gas model demonstrated that these materials are functionally stable in vivo for at least 1 mo, which represents an order of magnitude improvement over an injection of liquid siloxane [Kodibagkar VD, et al. (2006) Magn Reson Med 55(4):743-748]. We also observed minimal adverse tissue reactions or migration of contrast agents from the initial injection site. This class of contrast agents, thus, represented a new and complementary method to monitor chronic diseases by MRI.

What do differences between multi-voxel and univariate analysis mean? How subject-, voxel-, and trial-level variance impact fMRI analysis

Multi-voxel pattern analysis (MVPA) has led to major changes in how fMRI data are analyzed and interpreted. Many studies now report both MVPA results and results from standard univariate voxel-wise analysis, often with the goal of drawing different conclusions from each. Because MVPA results can be sensitive to latent multidimensional representations and processes whereas univariate voxel-wise analysis cannot, one conclusion that is often drawn when MVPA and univariate results differ is that the activation patterns underlying MVPA results contain a multidimensional code. In the current study, we conducted simulations to formally test this assumption. Our findings reveal that MVPA tests are sensitive to the magnitude of voxel-level variability in the effect of a condition within subjects, even when the same linear relationship is coded in all voxels. We also find that MVPA is insensitive to subject-level variability in mean activation across an ROI, which is the primary variance component of interest in many standard univariate tests. Together, these results illustrate that differences between MVPA and univariate tests do not afford conclusions about the nature or dimensionality of the neural code. Instead, targeted tests of the informational content and/or dimensionality of activation patterns are critical for drawing strong conclusions about the representational codes that are indicated by significant MVPA results.

Specificity of stimulus-evoked fMRI responses in the mouse: the influence of systemic physiological changes associated with innocuous stimulation under four different anesthetics

Functional magnetic resonance (fMRI) in mice has become an attractive tool for mechanistic studies, for characterizing models of human disease, and for evaluation of novel therapies. Yet, controlling the physiological state of mice is challenging, but nevertheless important as changes in cardiovascular parameters might affect the hemodynamic readout which constitutes the basics of the fMRI signal. In contrast to rats, fMRI studies in mice report less robust brain activation of rather widespread character to innocuous sensory stimulation. Anesthesia is known to influence the characteristics of the fMRI signal. To evaluate modulatory effects imposed by the anesthesia on stimulus-evoked fMRI responses, we compared blood oxygenation level dependent (BOLD) and cerebral blood volume (CBV) signal changes to electrical hindpaw stimulation using the four commonly used anesthetics isoflurane, medetomidine, propofol and urethane. fMRI measurements were complemented by assessing systemic physiological parameters throughout the experiment. Unilateral stimulation of the hindpaw elicited widespread fMRI responses in the mouse brain displaying a bilateral pattern irrespective of the anesthetic used. Analysis of magnitude and temporal profile of BOLD and CBV signals indicated anesthesia-specific modulation of cerebral hemodynamic responses and differences observed for the four anesthetics could be largely explained by their known effects on animal physiology. Strikingly, independent of the anesthetic used our results reveal that fMRI responses are influenced by stimulus-induced cardiovascular changes, which indicate an arousal response, even to innocuous stimulation. This may mask specific fMRI signal associated to the stimulus. Hence, studying the processing of peripheral input in mice using fMRI techniques constitutes a major challenge and adapted paradigms and/or alternative fMRI readouts should also be considered when studying sensory processing in mice.

BOLD MRI in the brain of fetal sheep at 3T during experimental hypoxia

PURPOSE

To calculate regional fetal brain oxygen saturation (sO2) during hypoxia in sheep.

MATERIALS AND METHODS

Eight pregnant ewes were examined at a 3T MR-scanner using blood oxygenation level-dependent magnetic resonance imaging (BOLD-MRI) to measure signal intensity changes of the fetal brain during a control period and a period of induced hypoxia. Regions of interest were placed in the fetal cerebrum to assess ΔR2* from GRE signal intensity plateaus (S(control), S(hypoxia)) and the relation between ΔR2* and ΔpO2 was analyzed. A probe was placed surgically in the fetal brain to directly measure local pO2 as a reference standard. Baseline and hypoxic pO2 values were recorded and compared (ΔpO2).

RESULTS

Mean fetal brain pO2 decreased from 14.3 mmHg (95% confidence interval [CI]: 10-19) to 3.4 mmHg (95% CI: 2-5) during hypoxia (mean ΔpO2 = 10.9 mmHg and ΔR2* = -5s(-1)). A significant correlation between ΔR2* and ΔpO2 was noted (r = 0.93, P < 0.001), and conversion of pO2 into sO2 resulted in a linear regression coefficient of (-0.14 ± 0.01)s(-1)/% (r(2) = 0.91).

CONCLUSION

Measured fetal brain BOLD-MRI was compared and converted to pO2, followed by calculation of cerebral sO2.

Comparing the Microvascular Specificity of the 3- and 7-T BOLD Response Using ICA and Susceptibility-Weighted Imaging

In functional MRI it is desirable for the blood-oxygenation level dependent (BOLD) signal to be localized to the tissue containing activated neurons rather than the veins draining that tissue. This study addresses the dependence of the specificity of the BOLD signal – the relative contribution of the BOLD signal arising from tissue compared to venous vessels – on magnetic field strength. To date, studies of specificity have been based on models or indirect measures of BOLD sensitivity such as signal to noise ratio and relaxation rates, and assessment has been made in isolated vein and tissue voxels. The consensus has been that ultra-high field systems not only significantly increase BOLD sensitivity but also specificity, that is, there is a proportionately reduced signal contribution from draining veins. Specificity was not quantified in prior studies, however, due to the difficulty of establishing a reliable network of veins in the activated volume. In this study we use a map of venous vessel networks extracted from 7 T high resolution Susceptibility-Weighted Images to quantify the relative contributions of micro- and macro-vasculature to functional MRI results obtained at 3 and 7 T. High resolution measurements made here minimize the contribution of physiological noise and Independent Component Analysis (ICA) is used to separate activation from technical, physiological, and motion artifacts. ICA also avoids the possibility of timing-dependent bias from different micro- and macro-vasculature responses. We find a significant increase in the number of activated voxels at 7 T in both the veins and the microvasculature – a BOLD sensitivity increase – with the increase in the microvasculature being higher. However, the small increase in sensitivity at 7 T was not significant. For the experimental conditions of this study, our findings do not support the hypothesis of an increased specificity of the BOLD response at ultra-high field.

The Virtual Brain: a simulator of primate brain network dynamics

We present The Virtual Brain (TVB), a neuroinformatics platform for full brain network simulations using biologically realistic connectivity. This simulation environment enables the model-based inference of neurophysiological mechanisms across different brain scales that underlie the generation of macroscopic neuroimaging signals including functional MRI (fMRI), EEG and MEG. Researchers from different backgrounds can benefit from an integrative software platform including a supporting framework for data management (generation, organization, storage, integration and sharing) and a simulation core written in Python. TVB allows the reproduction and evaluation of personalized configurations of the brain by using individual subject data. This personalization facilitates an exploration of the consequences of pathological changes in the system, permitting to investigate potential ways to counteract such unfavorable processes. The architecture of TVB supports interaction with MATLAB packages, for example, the well known Brain Connectivity Toolbox. TVB can be used in a client-server configuration, such that it can be remotely accessed through the Internet thanks to its web-based HTML5, JS, and WebGL graphical user interface. TVB is also accessible as a standalone cross-platform Python library and application, and users can interact with the scientific core through the scripting interface IDLE, enabling easy modeling, development and debugging of the scientific kernel. This second interface makes TVB extensible by combining it with other libraries and modules developed by the Python scientific community. In this article, we describe the theoretical background and foundations that led to the development of TVB, the architecture and features of its major software components as well as potential neuroscience applications.

Connective field modeling

The traditional way to study the properties of visual neurons is to measure their responses to visually presented stimuli. A second way to understand visual neurons is to characterize their responses in terms of activity elsewhere in the brain. Understanding the relationships between responses in distinct locations in the visual system is essential to clarify this network of cortical signaling pathways. Here, we describe and validate connective field modeling, a model-based analysis for estimating the dependence between signals in distinct cortical regions using functional magnetic resonance imaging (fMRI). Just as the receptive field of a visual neuron predicts its response as a function of stimulus position, the connective field of a neuron predicts its response as a function of activity in another part of the brain. Connective field modeling opens up a wide range of research opportunities to study information processing in the visual system and other topographically organized cortices.

Biophysical and physiological origins of blood oxygenation level-dependent fMRI signals

After its discovery in 1990, blood oxygenation level-dependent (BOLD) contrast in functional magnetic resonance imaging (fMRI) has been widely used to map brain activation in humans and animals. Since fMRI relies on signal changes induced by neural activity, its signal source can be complex and is also dependent on imaging parameters and techniques. In this review, we identify and describe the origins of BOLD fMRI signals, including the topics of (1) effects of spin density, volume fraction, inflow, perfusion, and susceptibility as potential contributors to BOLD fMRI, (2) intravascular and extravascular contributions to conventional gradient-echo and spin-echo BOLD fMRI, (3) spatial specificity of hemodynamic-based fMRI related to vascular architecture and intrinsic hemodynamic responses, (4) BOLD signal contributions from functional changes in cerebral blood flow (CBF), cerebral blood volume (CBV), and cerebral metabolic rate of O(2) utilization (CMRO(2)), (5) dynamic responses of BOLD, CBF, CMRO(2), and arterial and venous CBV, (6) potential sources of initial BOLD dips, poststimulus BOLD undershoots, and prolonged negative BOLD fMRI signals, (7) dependence of stimulus-evoked BOLD signals on baseline physiology, and (8) basis of resting-state BOLD fluctuations. These discussions are highly relevant to interpreting BOLD fMRI signals as physiological means.

Large enhancement of perfusion contribution on fMRI signal

The perfusion contribution to the total functional magnetic resonance imaging (fMRI) signal was investigated using a rat model with mild hypercapnia at 9.4 T, and human subjects with visual stimulation at 4 T. It was found that the total fMRI signal change could be approximated as a linear superposition of 'true' blood oxygenation level-dependent (BOLD; T(2)/T(2)(*)) effect and the blood flow-related (T(1)) effect. The latter effect was significantly enhanced by using short repetition time and large radiofrequency pulse flip angle and became comparable to the 'true' BOLD signal in response to a mild hypercapnia in the rat brain, resulting in an improved contrast-to-noise ratio (CNR). Bipolar diffusion gradients suppressed the intravascular signals but had no significant effect on the flow-related signal. Similar results of enhanced fMRI signal were observed in the human study. The overall results suggest that the observed flow-related signal enhancement is likely originated from perfusion, and this enhancement can improve CNR and the spatial specificity for mapping brain activity and physiology changes. The nature of mixed BOLD and perfusion-related contributions in the total fMRI signal also has implication on BOLD quantification, in particular, the BOLD calibration model commonly used to estimate the change of cerebral metabolic rate of oxygen.

BOLD fMRI investigation of the rat auditory pathway and tonotopic organization

Rodents share general anatomical, physiological and behavioral features in the central auditory system with humans. In this study, monaural broadband noise and pure tone sounds are presented to normal rats and the resulting hemodynamic responses are measured with blood oxygenation level-dependent (BOLD) fMRI using a standard spin-echo echo planar imaging sequence (without sparse temporal sampling). The cochlear nucleus (CN), superior olivary complex, lateral lemniscus, inferior colliculus (IC), medial geniculate body and primary auditory cortex, all major auditory structures, are activated by broadband stimulation. The CN and IC BOLD signal changes increase monotonically with sound pressure level. Pure tone stimulation with three distinct frequencies (7, 20 and 40 kHz) reveals the tonotopic organization of the IC. The activated regions shift from dorsolateral to ventromedial IC with increasing frequency. These results agree with electrophysiology and immunohistochemistry findings, indicating the feasibility of auditory fMRI in rats. This is the first fMRI study of the rodent ascending auditory pathway.