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Using gradient-echo echo-planar MRI, a local signal increase of 4.3 +/- 0.3% is observed in the human brain during task activation, suggesting a local decrease in blood deoxyhemoglobin concentration and an increase in blood oxygenation. Images highlighting areas of signal enhancement temporally correlated to the task are created.
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... In 1990, the advent of T2 * weighted functional magnetic resonance imaging (fMRI) enabled the detection of hyperemic increases in cerebral blood flow coupled to regional neuronal activation as an increase in the signal intensity level (Ogawa and Lee, 1990;Bandettini et al., 1992;Kwong et al., 1992;Ogawa et al., 1992;Buxton, 2012). According to current understanding, activated neurons stimulate the regional neurovascular unit, triggering dilatation of regional pre-capillary sphincters, which increases pulsatile blood flow after a response delay of 3-6 s (Biswal et al., 2003;Kucewicz et al., 2007). ...
... The enhanced inflow of oxygenated blood balloons the cortical veins that drain the activated area, thus reducing the local paramagnetic deoxyhemoglobin concentration, in conjunction with an increased blood volume (Ogawa and Lee, 1990;Buxton, 2012). Together these changes in blood circulation lower T2 * dephasing of regional (peri)vascular water proton spins, which is detectable as an increase in the blood oxygen level dependent (BOLD) signal intensity level downstream from activated areas (Bandettini et al., 1992;Ogawa et al., 1992;Buxton, 2012). ...
... The fMRI BOLD signal response knowledge indicates that in activated brain regions, an increase in fMRI T2 * weighted signal intensity that is sensitive to the reducing deoxyhemoglobin concentrations and increasing blood volume in the draining venules after some 3-5 s (Ogawa and Lee, 1990;Bandettini et al., 1992;Ogawa et al., 1992;Buxton, 2012). In agreement to the previous data, the detected BOLD FB signal response peak lag in the V1 was on average 3.7 s as measured from the end of activation ( Figure 1A). ...
The physiological pulsations that drive tissue fluid homeostasis are not well characterized during brain activation. Therefore, we used fast magnetic resonance encephalography (MREG) fMRI to measure full band (0-5 Hz) blood oxygen level-dependent (BOLD FB) signals during a dynamic visual task in 23 subjects. This revealed brain activity in the very low frequency (BOLD VLF) as well as in cardiac and respiratory bands. The cardiovascular hemodynamic envelope (CHe) signal correlated significantly with the visual BOLD VLF response, considered as an independent signal source in the V1-V2 visual cortices. The CHe preceded the canonical BOLD VLF response by an average of 1.3 (± 2.2) s. Physiologically, the observed CHe signal could mark increased regional cardiovascular pulsatility following vasodilation.
Magnetic susceptibility of tissue can provide valuable information about its chemical composition and microstructural organization. However, the relation between the magnetic microstructure and the measurable Larmor frequency shift is only understood for a few idealized cases. Here we analyze the microstructure formed by magnetized, NMR‐invisible infinite cylinders suspended in an NMR‐reporting fluid. Through simulations, we scrutinize various geometries of mesoscopic Lorentz cavities, inclusions, and show that the cavity size should be approximately one order of magnitude larger than the width of the inclusions. We also analytically derive the Larmor frequency shift for a population of cylinders with arbitrary orientation dispersion and show that it is determined by the l = 2 Laplace expansion coefficients P2m of the cylinders’ orientation distribution function. Our work underscores the need to account for microstructural organization when estimating magnetic tissue properties.
... Functional MRI (fMRI) is the main MRI method for studying functional connections in the human brain. Developed in the early 1990s, fMRI first used contrast agents administrated intravenously ( Belliveau et al., 1991), then exploited correlations in blood oxygen level dependent (BOLD) signals, based on different magnetic susceptibilities of oxygenated and deoxygenated hemoglobin to detect functional correlations between brain regions ( Ogawa et al., 1990Ogawa et al., , 1992Bandettini et al., 1992;Kwong et al., 1992). Functional MRI includes two main methods: resting-state fMRI (rsfMRI), measuring correlations in spontaneous activity between brain regions in resting subjects, and task-evoked fMRI (tfMRI), trying to detect functionally distinct brain regions during various tasks such as visuomotor or cognitive processes (Glasser et al., 2016). ...
... Functional MRI includes two main methods: resting-state fMRI (rsfMRI), measuring correlations in spontaneous activity between brain regions in resting subjects, and task-evoked fMRI (tfMRI), trying to detect functionally distinct brain regions during various tasks such as visuomotor or cognitive processes (Glasser et al., 2016). Almost 30 years ago, human fMRI studies were mostly performed at 1.5T with a spatial resolution of 3-4 mm ( Bandettini et al., 1992;Kwong et al., 1992). Since then, the spatial resolution of fMRI has been largely improved, such as the achievement of 0.65-mm resolution in the human brain at 7T ( Heidemann et al., 2012), but this is still not sufficient to study how individual neurons are connected to generate brain functions. ...
Our knowledge of the brain has evolved over millennia in philosophical, experimental and theoretical phases. We suggest that the next phase is simulation neuroscience. The main drivers of simulation neuroscience are big data generated at multiple levels of brain organization and the need to integrate these data to trace the causal chain of interactions within and across all these levels. Simulation neuroscience is currently the only methodology for systematically approaching the multiscale brain. In this review, we attempt to reconstruct the deep historical paths leading to simulation neuroscience, from the first observations of the nerve cell to modern efforts to digitally reconstruct and simulate the brain. Neuroscience began with the identification of the neuron as the fundamental unit of brain structure and function and has evolved towards understanding the role of each cell type in the brain, how brain cells are connected to each other, and how the seemingly infinite networks they form give rise to the vast diversity of brain functions. Neuronal mapping is evolving from subjective descriptions of cell types towards objective classes, subclasses and types. Connectivity mapping is evolving from loose topographic maps between brain regions towards dense anatomical and physiological maps of connections between individual genetically distinct neurons. Functional mapping is evolving from psychological and behavioral stereotypes towards a map of behaviors emerging from structural and functional connectomes. We show how industrialization of neuroscience and the resulting large disconnected datasets are generating demand for integrative neuroscience, how the scale of neuronal and connectivity maps is driving digital atlasing and digital reconstruction to piece together the multiple levels of brain organization, and how the complexity of the interactions between molecules, neurons, microcircuits and brain regions is driving brain simulation to understand the interactions in the multiscale brain.
... Functional magnetic resonance imaging (fMRI) based on the blood oxygenation level dependent (BOLD) contrast  has gained a prominent position in neuroscience for imaging brain activation and studying effective connectivity during task performance 6 . Moreover, the same fMRI technique can be employed to map the functional connectivity of various neural networks based on the temporal coherence of low-frequency spontaneous BOLD fluctuation  in a brain at rest state. ...
... However, a fundamental neuroscience question related to the fMRI methodology, i.e., how the BOLD signal inferences the underlying neural activity and the associated neurophysiological changes in space and time, remains unanswered, especially at microscopic and mesoscopic scales. The BOLD contrast originates from the magnetic susceptibility effect induced by the oxygenation level change of the hemoglobin inside blood vessels, thus, having a relatively slow response time to neuronal activity change in a range of few seconds  , and its quantity is determined by the complex interplays of the hemodynamic changes in cerebral blood flow and volume and the oxygen metabolic rate change driven by either evoked or spontaneous neuronal activity 1,7,27,28 . Although the fMRI BOLD signal has served as a surrogate of the brain activity, its quantitative transformation to the underlying neural activity can vary significantly at different scales and brain conditions. ...
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.
The purpose of this study is to explain the implementation process and benefits of functional near-infrared spectroscopy (fNIRS), a neurometric assessment method in the field of social sciences. Although the application of fNIRS in fields such as psychology and neuroscience is discussed in the literature (Fronda and Balconi, 2022; Hu and Shepley, 2022), limited research has been conducted on its application in the social sciences (Krampe et al., 2018a; Mehlhose, 2022). Based on this gap, the origin of the fNIRS technique and its opportunities for social sciences are detailed in the first section of the research.
In the second part of the study, on the basis of the Rowley and Slack (2004) systematic review model, fNIRS-based research in social science disciplines (management, organizational behaviour, marketing, economics, and finance) was reviewed and a roadmap for future research was attempted to be developed.
... Functional magnetic resonance imaging (fMRI) detects the blood oxygenation level dependent (BOLD) signal (Ogawa et al., 1990a, b) as a surrogate measure of neural activity (Bandettini et al. 1992;Kwong et al. 1992;Ogawa et al. 1992). Despite its wide use for cognitive sciences, fMRI is commonly recognized to only be sensitive to very slow (<0.2 Hz) fluctuations in neural activity. ...
The stomach and the brain interact closely with each other. Their interactions are central to digestive functions and the “gut feeling”. The neural pathways that mediate the stomach-brain interactions include the vagus nerve and the thoracic nerve. Through these nerves, the stomach can relay neural signals to a number of brain regions that span a central gastric network. This gastric network allows the brain to monitor and regulate gastric physiology and allows the stomach to influence emotion and cognition. Impairment of this gastric network may lead to both gastric and neurological disorders, e.g., anxiety, gastroparesis, functional dyspepsia, and obesity. However, the structural constituents and functional roles of the central gastric network remain unclear. In my dissertation research, I leveraged complementary techniques to characterize the central gastric network in rats across a wide range of scales and different gastric states. I used functional magnetic resonance imaging (fMRI) to map blood-oxygen-level-dependent (BOLD) activity synchronized with gastric electrical activity and to map brain activations induced by electrical stimulation applied to the vagus nerve or its afferent terminals on the stomach. I also used neurophysiology to characterize gastric neurons in the brainstem in response to gastric electrical stimulation. My results suggest that gastric neurons in the brainstem are selective to the orientation of gastric electrical stimulation. This electrical stimulation can also evoke neural activity beyond the brainstem and drive fast blood oxygenation level dependent (BOLD) activity in the central gastric network, primarily covering the cingulate cortex, somatosensory cortex, motor cortex, and insular cortex. Stimulating the vagus nerve – the primary neural pathway between the stomach and the brain, can evoke BOLD responses across widespread brain regions partially overlapped with the brain network evoked by gastric electrical stimulation. BOLD activity within the gastric network is also coupled to intrinsic gastric activity. Specifically, gastric slow waves are synchronized with the BOLD activity in the central gastric network. The synchronization manifests itself as the phase-coupling between BOLD activity and gastric slow waves as well as the correlation between BOLD activity and power fluctuations of gastric slow waves. This synchronization is primarily supported by the vagus nerve and varies across the postprandial and fasting states. My dissertation research contributes to the foundation of mapping and characterizing the central and peripheral mechanisms of gastric interoception and sheds new light on where and how to stimulate the peripheral nerves to modulate stomach-brain interactions.
... Gradient-echo (GE) blood oxygenation level-dependent (BOLD) with T2 * weighting is one of the most 2 commonly used fMRI contrasts due to its high sensitivity and acquisition efficiency (Bandettini et al., 1992;3 Kwong et al., 1992;Ogawa et al., 1990). However, the signal change of GE BOLD contains a mixture of 4 contribution from both macro-and micro-vessels. ...
Spin-echo (SE) BOLD fMRI has high microvascular specificity, but its most common acquisition method, SE-EPI, suffers from T2' contrast contamination with undesirable draining vein bias. To address this, in this study, we extended a recently developed multi-shot EPI technique, Echo-Planar Time-resolved Imaging (EPTI), to laminar SE-fMRI at 7T to obtain pure spin-echo BOLD contrast with minimal T2' contamination for improved specificity. We also developed a framework to simultaneously obtain a series of asymmetric SE (ASE) images with varying T2' weightings, and extracted from the same data equivalent conventional SE multi-shot EPI images with different ETLs, to investigate the T2'-induced macrovascular contribution across the spin-echo readout. A low-rank spatiotemporal subspace reconstruction was implemented for the SE-EPTI acquisition, which incorporates corrections for both shot-to-shot phase variations and dynamic B0 drifts. SE-EPTI was used in a visual task fMRI experiment to demonstrate that i) the pure SE image provided by EPTI results in the highest microvascular specificity; ii) the ASE EPTI image series, with a graded introduction of T2' weightings at time points farther away from the pure SE, show a gradual sensitivity increase accompanied by a larger and larger draining vein bias; iii) a longer ETL in the conventional SE EPI acquisition will induce more draining vein bias. Consistent results were observed across multiple subjects, demonstrating the robustness of the proposed technique for SE-BOLD fMRI with high specificity.
... Deoxyhemoglobin is paramagnetic, while oxyhemoglobin is diamagnetic, and therefore deoxyhemoglobin creates a stronger magnetic field inhomogeneity which results a weaker signal. Therefore, the most popular fMRI method is named Bloodoxygen-level dependent (BOLD) (Bandettini, et al., 1992;Ogawa, et al., 1990). The change of intensity of the BOLD signal which relates to neural activity is usually less than 5%. ...
Psychedelics can induce eyes-closed imagery in which various visions can be experienced. These visions vary from simple geometrical patterns, to more complex imagery, to full immersion within “other realms”. Past studies suggest that the visual cortex is involved in processing these visions, yet these studies were limited into investigation of activity. In this thesis, the aim was to expand on the involvement of the visual cortex by investigating processes that are beyond simple activation maps, such as functional connectivity and dynamics. In study 1, it was hypothesized that the visual cortex will show increased functional connectivity with many cortical and subcortical regions. This was investigated with 15 subjects that were scanned using fMRI under the influence of 75 µg of LSD or placebo. The results of this study showed increased resting state functional connectivity (RSFC) between the primary visual cortex and many cortical and subcortical regions. This result correlated with subjective ratings of psychedelic imagery and with occipital alpha power suppression measured with MEG, which is a reliable neural correlate of the intensity of the psychedelic state. It study 2, it was hypothesized that connectivity within the visual cortex would match its retinotopic architecture. Retinotopic mapping is the representation of the visual field (the world we observe) in the visual cortex – e.g. areas which are near to each other in the visual field will be near each other in the visual cortex. In this study, it was found that under LSD (same procedure as study 1), with eyes closed, connectivity patterns between different subregions of the visual cortex matched the retinotopic mapping of these regions, suggesting that the visual system behaves as if it is seeing spatially localized input, with eyes-closed under LSD. In study 3, it was hypothesized that during the onset phase of psychedelic imagery, the activation of subregions of the visual cortex will be from low level to high level areas, which is according to the subjective dynamics of the experience – i.e. from simple to complex. This was tested in 9 subjects that were scanned in the fMRI during the onset or “come-up” phase - i.e. 3 minutes post (1 min) infusion of 2mg psilocybin IV - which has a particularly fast onset. Results in this study revealed that during the onset phase the BOLD dynamics of regions within the ventral stream are organized by the hierarchy of regions. Overall, study 1 and 2 revealed that, with eyes closed, under LSD, communication patterns between visual cortex and the rest of the brain and within the visual cortex match the kind of processing known to occur during regular vision. This adds to a body of knowledge supporting the view that the visual cortex is particularly engaged under the influence of psychedelics, and by measuring patterns of connectivity, we were able to provide strong support for the view that abnormal activity in the visual cortex underlies psychedelic imagery.
... To enable robust observations of brain activity, fast T2 * -weighted imaging sequences play a crucial role in measuring dynamic changes in the BOLD signal. This is why echo planar imaging (EPI, (Mansfield, 1977)) has been used for fMRI acquisitions since the first reports of functional imaging experiments (Kwong, et al., 1992) (Bandettini, et al., 1992). However, even with fast imaging techniques and low-resolution protocols, volume acquisition times can be long when whole-brain coverage is required. ...
The sensitivity to subject motion is one of the major challenges in functional MRI (fMRI) studies in which a precise alignment of images from different time points is required to allow reliable quantification of brain activation throughout the scan. Especially the long measurement times and laborious fMRI tasks add to the amount of subject motion found in typical fMRI measurements, even when head restraints are used. In case of moving subjects, prospective motion correction can maintain the relationship between spatial image information and subject anatomy by constantly adapting the image slice positioning to follow the subject in real time. Image-based prospective motion correction is well-established in fMRI studies and typically computes the motion estimates based on a volume-to-volume image registration, resulting in low temporal resolution. This study combines fMRI using simultaneous multislice imaging with multislice-to-volume-based image registration to allow sub-TR motion detection with subsequent real-time adaption of the imaging system. Simultaneous multislice imaging is widely used in fMRI studies and, together with multislice-to-volume-based image registration algorithms, enables computing suitable motion states after only a single readout by registering the simultaneously excited slices to a reference volume acquired at the start of the measurement. The technique is evaluated in three human BOLD fMRI studies (n = 1, 5, and 1) to explore different aspects of the method. It is compared to conventional, volume-to-volume-based prospective motion correction as well as retrospective motion correction methods. Results show a strong reduction in retrospectively computed residual motion parameters of up to 50% when comparing the two prospective motion correction techniques. An analysis of temporal signal-to-noise ratio as well as brain activation results shows high consistency between the results before and after additional retrospective motion correction when using the proposed technique, indicating successful prospective motion correction. The comparison of absolute tSNR values does not show an improvement compared to using retrospective motion correction alone. However, the improved temporal resolution may provide improved tSNR in the presence of more exaggerated intra-volume motion.
... Ainsi le signal BOLD augmente suite à l'activation neuronale (Figure I-3). C'est la découverte de cet effet BOLD qui a permis de réaliser dans les années 1990 les premières images du cerveau en fonctionnement (Belliveau et al. 1991;Bandettini et al. 1992;Kwong et al. 1992). L'IRM fonctionnelle permet aujourd'hui des études très poussées en neurosciences à la fois chez des sujets sains ou malades, que ce soit chez l'Homme ou chez des modèles animaux, notamment chez le petit animal . ...
Mes travaux de thèse portent sur l’application de l’imagerie fUS (functional ultrasound imaging) à l’imagerie cérébrale préclinique chez le petit animal. Le but était de transformer cette technique d’imagerie cérébrale récente en un véritable outil de quantification de l’état cérébral. Les objectifs principaux ont été de démontrer la faisabilité de l’imagerie fUS chez le petit animal non anesthésié ainsi que de passer du modèle rat au modèle souris - modèle de choix en imagerie préclinique en neurosciences - de surcroît de façon non invasive. J’ai tout d’abord mis au point une nouvelle séquence d’imagerie ultrasonore ultrarapide (Multiplane Wave imaging), permettant d’améliorer le rapport signal-à-bruit des images grâce à l’augmentation virtuelle de l’amplitude du signal émis, sans diminuer la cadence ultrarapide d’acquisition. Dans un deuxième temps j’ai démontré la possibilité d’imager le cerveau de la souris et du jeune rat anesthésiés par échographie Doppler ultrarapide, de manière transcrânienne et complètement non invasive, sans chirurgie ni injection d’agents de contraste. J’ai ensuite mis au point un montage expérimental, une séquence ultrasonore et un protocole expérimental permettant de réaliser de l’imagerie fUS de manière minimalement invasive chez des souris éveillées et libres de leurs mouvements. Enfin, j’ai démontré la possibilité d’utiliser le fUS pour étudier la connectivité fonctionnelle du cerveau au repos (sans stimulus) chez des souris éveillées ou sédatées. L’imagerie fUS et la combinaison « modèle souris » + « minimalement invasif » + « animal éveillé » + « connectivité fonctionnelle » constituent un outil précieux pour la communauté des neuroscientifiques travaillant sur des modèles animaux pathologiques ou de nouvelles molécules pharmacologiques
... NVC can be defined as a process that links the change in regional neuronal activity to the local cerebral blood flow (CBF) (Raichle, 1998). A tight coupling exists between the changes in the neuronal activity and the changes in CBF caused by functional stimulation (Villringer and Dirnagl, 1995), which is the basis for currently available functional neuroimaging techniques, including position emission tomography (PET) ( Terpogossian et al., 1975;Fox and Raichle, 1984;Ollinger and Fessler, 1997), intrinsic signal optical imaging (ISOI) ( Grinvald et al., 1988), functional magnetic resonance imaging (fMRI) ( Ogawa et al., 1990;Bandettini et al., 1992), and functional near-infrared spectroscopy (fNIRS) (Hoshi and Tamura, 1993;Villringer et al., 1993;Kim et al., 2017). ...
A tight coupling between the neuronal activity and the cerebral blood flow (CBF) is the motivation of many hemodynamic response (HR)-based neuroimaging modalities. The increase in neuronal activity causes the increase in CBF that is indirectly measured by HR modalities. Upon functional stimulation, the HR is mainly categorized in three durations: (i) initial dip, (ii) conventional HR (i.e., positive increase in HR caused by an increase in the CBF), and (iii) undershoot. The initial dip is a change in oxygenation prior to any subsequent increase in CBF and spatially more specific to the site of neuronal activity. Despite additional evidence from various HR modalities on the presence of initial dip in human and animal species (i.e., cat, rat, and monkey); the existence/occurrence of an initial dip in HR is still under debate. This article reviews the existence and elusive nature of the initial dip duration of HR in intrinsic signal optical imaging (ISOI), functional magnetic resonance imaging (fMRI), and functional near-infrared spectroscopy (fNIRS). The advent of initial dip and its elusiveness factors in ISOI and fMRI studies are briefly discussed. Furthermore, the detection of initial dip and its role in brain-computer interface using fNIRS is examined in detail. The best possible application for the initial dip utilization and its future implications using fNIRS are provided.
... Систематизация данных о релаксационных свойствах крови позволяет построить эмпирические зависимости величины изменения сигнала ЯМР при BOLD фМРТ от диаметра сосуда, насыщенности крови кислородом, а также величины магнитного поля. Кроме того величина BOLD-отклика будет зависеть от используемой импульсной последовательности вследствие различных механизмов релаксации, детектируемых в последовательностях на основе спинового  и градиентного  эха. Анализ полученных зависимостей показывает, что при использовании последовательности на основе градиентного эха не существует таких условий (Рис. ...
Increasing the static magnetic field strength into the realm of ultrahigh fields (7 T and higher) is the central trend in modern magnetic resonance (MR) imaging. The use of ultrahigh fields in MR-imaging leads to numerous effects some of them raising the image quality, some degrading, some previously undetected in lower fields. This review aims to outline the main consequences of introducing ultrahigh fields in MR-imaging, including new challenges and the proposed solutions, as well as new scanning possibilities unattainable at lower field strengths (below 7 T).
... Functional MRI (fMRI) has significantly enhanced our knowledge about human brain function (Bandettini, Wong, Hinks, Tikofsky, & Hyde, 1992;Kwong et al., 1992;Ogawa et al., 1992), especially in recent years when fMRI data has been used to quantify the brain as a complex network (Rubinov & Sporns, 2010;Bullmore & Sporns, 2009). Although fMRI-based network analyses have led to several new insights into the spatial and temporal nature of large-scale brain network activity (Hutchison et al., 2013;Preti, Bolton, & Van De Ville, 2017), many early fMRI network studies treat spatial and temporal information as separate entities, meaning that brain regions are not interconnected across time and space. ...
Large-scale brain dynamics measures repeating spatiotemporal connectivity patterns that reflect a range of putative different brain states that underlie the dynamic repertoire of brain functions. The role of transition between brain networks is poorly understood and whether switching between these states is important for behavior has been little studied. Our aim here is to model switching between functional brain networks using multilayer network methods and test for associations between model parameters and behavioral measures. We calculated time-resolved functional MRI (fMRI) connectivity from one-hour long data recordings in 1003 healthy human adults from the Human Connectome Project. The time-resolved fMRI connectivity data was used to generate a spatiotemporal multilayer modularity model enabling us to quantify network switching which we define as the rate at which each brain region transits between different fMRI networks. We found i) an inverse relationship between network switching and connectivity dynamics −defined as the difference in variance between time-resolved fMRI connectivity signals and phase randomized surrogates−; ii) brain connectivity was lower during intervals of network switching; iii) brain areas with frequent network switching had greater temporal complexity; iv) brain areas with high network switching were located in association cortices; and v) using cross-validated Elastic Net regression, network switching predicted inter-subject variation in working memory performance, planning/reasoning and amount of sleep. Our findings shed new light on the importance of brain dynamics predicting task performance and amount of sleep. The ability to switch between network configurations thus appears to be a fundamental feature of optimal brain function.
... Most fMRI studies are based on the BOLD technique ( Bandettini et al., 1992;Kwong et al., 1992;Ogawa et al., 1992) which offers a large sensitivity and easy of implementation. However, due to the complex nature of the BOLD effect, the quantitative interpretation of this fMRI signal can be problematic. ...
Measurement of the dynamic coupling between spontaneous Blood Oxygenation Level Dependent (BOLD) and cerebral blood flow (CBF) fluctuations has been recently proposed as a method to probe resting-state brain physiology. Here we investigated how the dynamic BOLD-CBF coupling during resting-state is affected by aging. Fifteen young subjects and 17 healthy elderlies were studied using a dual-echo pCASL sequence. We found that the dynamic BOLD-CBF coupling was markedly reduced in elderlies, in particular in the left supramarginal gyrus, an area known to be involved in verbal working memory and episodic memory. Moreover, correcting for temporal shift between BOLD and CBF timecourses resulted in an increased correlation of the two signals for both groups, but with a larger increase for elderlies. However, even after temporal shift correction, a significantly decreased correlation was still observed for elderlies in the left supramarginal gyrus, indicating that the age-related dynamic BOLD-CBF uncoupling in this region is more pronounced and can be only partially explained with a simple time-shift between the two signals. Interestingly, these results were observed in a group of elderlies with normal cognitive functions, suggesting that the study of dynamic BOLD-CBF coupling during resting-state is a promising technique, potentially able to provide early biomarkers of functional changes in the aging brain.
З використанням функціональної магнітно-резонансної томографїї визначена ефективность передопераційного фМРТ дослідження щодо локалізації зони рухової активації для попередження рухового неврологічного дефіциту при хірургічних втручанях з приводу внутришньомозкових пухлин півкуль великого мозку.
... Positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) are used in both basic and clinical research as an indicator of brain health, structurally and dynamically. In fMRI the most common measurement for evaluating changes in functional brain activity is the blood-oxygen-level dependent (BOLD) signal ( Ogawa et al., 1990;Bandettini et al., 1992), and in PET it is the cerebral metabolic rate for glucose (CMRglc) ( Phelps et al., 1979). Both depend on mapping energy expenditure during pre-and postsynaptic neuronal signaling, events that lead to a rapid need for oxygen and glucose from the vascular system (Attwell and Laughlin, 2001). ...
Functional magnetic resonance imaging (fMRI) is widely used in investigations of normal cognition and brain disease and in various clinical applications. Pharmacological fMRI (pharma-fMRI) is a relatively new application, which is being used to elucidate the effects and mechanisms of pharmacological modulation of brain activity. Characterizing the effects of neuropharmacological agents on regional brain activity using fMRI is challenging because drugs modulate neuronal function in a wide variety of ways, including through receptor agonist, antagonist, and neurotransmitter reuptake blocker events. Here we review current knowledge on neurotransmitter-mediated blood-oxygen-level dependent (BOLD) fMRI mechanisms as well as recently updated methodologies aimed at more fully describing the effects of neuropharmacologic agents on the BOLD signal. We limit our discussion to dopaminergic signaling as a useful lens through which to analyze and interpret neurochemical-mediated changes in the hemodynamic BOLD response. We also discuss the need for future studies that use multi-modal approaches to expand the understanding and application of pharma-fMRI.
... Functional brain imaging aims at studying the function and dysfunction of the brain by monitoring its functional dynamics over time. Such modalities include, for instance, functional magnetic resonance imaging (fMRI) ( Bandettini et al., 1992;Kwong et al., 1992;Ogawa et al., 1992), positron emission tomography (PET) ( Ter-Pogossian et al., 1975), electroencephalography (EEG) ( He et al., 1987;Michel and He, 2011; Niedermeyer and da Silva, 2005), and magnetoencephalography (MEG) ( Cohen, 1972;Hämäläinen et al., 1993). Among these modalities, EEG is noninvasive, inexpensive, easy to set up and is readily available in most clinical settings ( Niedermeyer and da Silva, 2005). ...
The goal of this study is to investigate the performance, merits and limitations of source imaging using intracranial EEG (iEEG) recordings and to compare its accuracy to the results of EEG source imaging. Accuracy in this study, is measured both by determining the location and inter-nodal connectivity of underlying brain networks.
Systematic computer simulation studies are conducted to evaluate iEEG-based source imaging vs. EEG-based source imaging, and source imaging using both EEG and iEEG. To test the source imaging models, networks of inter-connected nodes (in terms of activity) are simulated. The location of the network nodes is randomly selected within a realistic geometry head model and a connectivity link is created among these nodes based on a multi-variate auto-regressive (MVAR) model. Then the forward problem is solved to calculate the potentials at the electrodes and noise (white and correlated) is added to these simulated potentials to simulate realistic measurements. Subsequently, the inverse problem is solved and an algorithm based on principle component analysis is performed on the estimated source activities to determine the location of the simulated network nodes. The activity of these nodes (over time), is then extracted, and used to estimate the connectivity links among the mentioned nodes using Granger causality analysis.
Source imaging based on iEEG recordings may or may not improve the accuracy in localization, depending on the number and location of active nodes relative to iEEG electrodes and to other nodes within the network. However, our simulation results suggest that combining EEG and iEEG modalities (simultaneous scalp and intracranial recordings) can improve the imaging accuracy significantly.
While iEEG source imaging is useful in estimating the exact location of sources near the iEEG electrodes, combining EEG and iEEG recordings can achieve a more accurate imaging due to the high spatial coverage of the scalp electrodes and the added near field information provided by the iEEG electrodes.
The present results suggest the feasibility of localizing brain electrical sources from iEEG recordings and improving EEG source localization using simultaneous EEG and iEEG recordings to cover the whole brain. The hybrid EEG and iEEG source imaging can assist the clinicians when unequivocal decisions about determining the epileptogenic zone cannot be reached using a single modality.
... Functional magnetic resonance imaging (FMRI) is one of the main tools used to investigate the functions of the human brain. The most commonly employed strategy is to investigate how the blood oxygenation level dependent (BOLD) signal changes as a function of stimuli and/or tasks [Bandettini et al., 1992;Frahm et al., 1992;Kwong et al., 1992;Ogawa et al., 1992]. One of the aims of these types of studies is to localize the regions of the brain that become activated during certain stimuli and/or tasks. ...
... Their work (recording intra-and extracellular neural activity in cats and monkeys) is the basis for our understanding of the functional architecture of visual brain areas, especially with respect to the retinotopic organization of recep-metabolic activity (8) and blood flow (9,10) localized to the site of activity. The increase in flow exceeds the metabolic increase and the rate of oxygen extraction from the cerebral microvasculature, which produces an increase in the ratio of oxygenated:deoxygenated hemoglobin (11,12). Deoxyhemoglobin causes attenuation of magnetic resonance signal (13). ...
The neuroanatomy of the mammalian visual system has received considerable attention through electrophysiological study of cats and non-human primates, and through neuroimaging of humans. Canine neuroanatomy, however, has received much less attention, limiting our understanding of canine vision and visual pathways. As an early step in applying blood oxygenation level dependant (BOLD) functional magnetic resonance imaging (fMRI) for veterinary use, we compared visual activity in the thalamus and occipital cortex of anesthetized dogs presented with binocular and monocular visual stimuli. Activity in the left and right thalamus and occipital cortex during monocular stimulation was also compared. Six beagles were presented with a vertical grating visual stimulus and scanned at 4 Tesla. Each dog was scanned twice under each of 3 anesthetic protocols (isoflurane, propofol, and fentanyl/midazolam). We found: 1) significant BOLD activation in the lateral geniculate nucleus (LGN) of the thalamus and the occipital cortex; 2) a significantly larger area of activation in the LGN during monocular stimulation than during binocular stimulation; and 3) that activity in the hemisphere contralateral to the stimulus was not significantly greater than that ipsilateral to it.
... Since its introduction (Bandettini et al., 1992;Kwong et al., 1992;Ogawa et al., 1992), functional magnetic resonance imaging (fMRI) has taken the field of cognitive neuroscience by storm. Here we aim at highlighting the potential for imaging brain function at ultra high fields (UHF, 7 T and above). ...
The ability to measure functional brain responses non-invasively with ultra high field MRI (7 T and above) represents a unique opportunity in advancing our understanding of the human brain. Compared to lower fields (3 T and below), ultra high field MRI has an increased sensitivity, which can be used to acquire functional images with greater spatial resolution, and greater specificity of the blood oxygen level dependent (BOLD) signal to the underlying neuronal responses. Together, increased resolution and specificity enable investigating brain functions at a submillimeter scale, which so far could only be done with invasive techniques. At this mesoscopic spatial scale, perception, cognition and behavior can be probed at the level of fundamental units of neural computations, such as cortical columns, cortical layers, and subcortical nuclei. This represents a unique and distinctive advantage that differentiates ultra high from lower field imaging and that can foster a tighter link between fMRI and computational modeling of neural networks. So far, functional brain mapping at submillimeter scale has focused on the processing of sensory information and on well-known systems for which extensive information is available from invasive recordings in animals. It remains an open challenge to extend this methodology to uniquely human functions and, more generally, to systems for which animal models may be problematic. To succeed, the possibility to acquire high-resolution functional data with large spatial coverage, the availability of computational models of neural processing as well as accurate biophysical modeling of neurovascular coupling at mesoscopic scale all appear necessary.
... It is a closedloop system that uses the BOLD signal from one circumscribed brain region or a network of brain regions, in real-time, to calculate and present feedback (e.g., visual, auditory, or tactile) to participants (e.g., Caria et al., 2007;Sitaram et al., 2007;Rota et al., 2009;Ruiz et al., 2013a). The rtfMRI system comprises of the following subsystems (see An echo planar imaging (EPI) sequence (Bandettini et al., 1992) is used to acquire functional images of the brain (see Figure 1B). Online computation procedures with the data in the k-space such as distortion correction, averaging of the signal, and image reconstruction are performed on the scanner's image reconstruction computer. ...
Cognitive decline is a major concern in the aging population. It is normative to experience some deterioration in cognitive abilities with advanced age such as related to memory performance, attention distraction to interference, task switching, and processing speed. However, intact cognitive functioning in old age is important for leading an independent day-to-day life. Thus, studying ways to counteract or delay the onset of cognitive decline in aging is crucial. The literature offers various explanations for the decline in cognitive performance in aging; among those are age-related gray and white matter atrophy, synaptic degeneration, blood flow reduction, neurochemical alterations, and change in connectivity patterns with advanced age. An emerging literature on neurofeedback and Brain Computer Interface (BCI) reports exciting results supporting the benefits of volitional modulation of brain activity on cognition and behavior. Neurofeedback studies based on real-time functional magnetic resonance imaging (rtfMRI) have shown behavioral changes in schizophrenia and behavioral benefits in nicotine addiction. This article integrates research on cognitive and brain aging with evidence of brain and behavioral modification due to rtfMRI neurofeedback. We offer a state-of-the-art description of the rtfMRI technique with an eye towards its application in aging. We present preliminary results of a feasibility study exploring the possibility of using rtfMRI to train older adults to volitionally control brain activity. Based on these first findings, we discuss possible implementations of rtfMRI neurofeedback as a novel technique to study and alleviate cognitive decline in healthy and pathological aging.
... Since its inception in the early 1990s, blood oxygenation level dependent (BOLD) fMRI has been the predominant tool for functional neuroimaging during task activation and resting state . During the past two decades, considerable progresses have been made to improve the spatial and temporal resolutions of BOLD fMRI. ...
Passband balanced steady state free precession (b-SSFP) fMRI employs the flat portion of the SSFP off-resonance response to obtain microscopic susceptibility changes elicited by changes in blood oxygenation following enhancement in neuronal activity. This technique can reduce geometric distortion and signal dropout while maintaining rapid acquisition and high signal-to-noise ratio (SNR) compared with traditional fMRI techniques. In the study, we developed a novel multi-phase passband b-SSFP fMRI technique that can achieve a spatial resolution of a few mm(3) and a high temporal sampling rate of 50ms per slice at 7 Tesla. This technique was further applied for an event-related (ER) fMRI paradigm. As a comparison, gradient-echo echo-planar imaging (GE-EPI) with similar spatial resolution and temporal sampling rate was carried out for the same ER-fMRI experiment. Experiments with visual cortex stimulation were carried out at 7 Tesla to demonstrate whether the multi-phase b-SSFP technique and GE-EPI are able to differentiate temporal delays in hemodynamic response function (HRF) separated by 100ms in stimulus onset. Consistent with ERP results, the upslope of the HRF of both techniques can differentiate 100ms delay in stimulus onset, with the former showing a lower level of intersubject variability. The present study demonstrated that the multi-phase passband b-SSFP fMRI technique can be applied for resolving neuronal events on the order of 100ms at ultrahigh magnetic fields.
... Functional magnetic resonance imaging (fMRI) methods typically record signal intensity changes based on hemodynamic responses that accompany neuronal activity, through the blood oxygenation level dependent (BOLD) effect . As BOLD responses evolve on the timescale of seconds, spatial encoding must be conducted much more rapidly than in conventional anatomical MRI. The majority of fMRI studies employ single-shot echo planar imaging (EPI)  which, through the use of a raster scan k-space trajectory, typically enables spatial encoding of a single slice in less than 100 ms, and multislice whole-brain coverage in 1-2s. ...
Echo planar imaging (EPI) suffers from geometric distortions caused by magnetic field inhomogeneities, which can be time-varying as a result of small amounts of head motion that occur over seconds and minutes during fMRI experiments, also known as “dynamic geometric distortion”. Phase Labeling for Additional Coordinate Encoding (PLACE) is a promising technique for geometric distortion correction without reduced temporal resolution and in principle can be used to correct for motion-induced dynamic geometric distortion. PLACE requires at least two EPI images of the same anatomy that are ideally acquired with no variation in the magnetic field inhomogeneities. However, head motion and lung ventilation during the respiratory cycle can cause changes in magnetic field inhomogeneities within the EPI pair used for PLACE. In this work, we exploited dynamic off-resonance in k-space (DORK) and averaging to correct the within EPI pair magnetic field inhomogeneities; and hence proposed a combined technique (DORK+PLACE+averaging) to mitigate dynamic geometric distortion in EPI-based fMRI while preserving the temporal resolution. The performance of the combined DORK, PLACE and averaging technique was characterized through several imaging experiments involving test phantoms and six healthy adult volunteers. Phantom data illustrate reduced temporal standard deviation of fMRI signal intensities after use of combined dynamic PLACE, DORK and averaging compared to the standard processing and static geometric distortion correction. The combined technique also substantially improved the temporal standard deviation and activation maps obtained from human fMRI data in comparison to the results obtained by standard processing and static geometric distortion correction, highlighting the utility of the approach.
... Parallel advances extended the range of evaluations to cellular metabolism by localized MR spectroscopy (cf. Chapter 40), adding a biochemical dimension to anatomic imaging (Bachelard 1997). Functional aspects became available through magnetic resonance angiography, perfusion studies, diffusion contrast, and magnetization transfer techniques. ...
Noninvasive methods for studying metabolic and functional properties of the central nervous system provide new tools for understanding the human brain at the system level. As a bridging technology between basic neurobiologic research in (transgenic) animals, system-oriented studies in humans, and medical applications to patients with neurologic disease, magnetic resonance is expected to gain further importance in linking advances in molecular neurobiology and neurogenetics to cerebral metabolism and physiology and even beyond to human brain function.
... Since its discovery more than two decades ago (Bandettini et al., 1992; Kwong et al., 1992; Ogawa et al., 1992), non-invasive functional magnetic resonance imaging (fMRI) has evolved to become a primary method to study human brain function. The majority of fMRI experiments have been conducted using the blood oxygenation level dependent (BOLD) method (Ogawa et al., 1990), relying on T 2 * changes in gradient-echo based echo-planar imaging (GE-EPI, Mansfield, 1977) acquisitions. ...
Functional magnetic resonance imaging (fMRI) allows studying human brain function non-invasively up to the spatial resolution of cortical columns and layers. Most fMRI acquisitions rely on the blood oxygenation level dependent (BOLD) contrast employing T(*) 2 weighted 2D multi-slice echo-planar imaging (EPI). At ultra-high magnetic field (i.e., 7 T and above), it has been shown experimentally and by simulation, that T2 weighted acquisitions yield a signal that is spatially more specific to the site of neuronal activity at the cost of functional sensitivity. This study compared two T2 weighted imaging sequences, inner-volume 3D Gradient-and-Spin-Echo (3D-GRASE) and 2D Spin-Echo EPI (SE-EPI), with evaluation of their imaging point-spread function (PSF), functional specificity, and functional sensitivity at sub-millimeter resolution. Simulations and measurements of the imaging PSF revealed that the strongest anisotropic blurring in 3D-GRASE (along the second phase-encoding direction) was about 60% higher than the strongest anisotropic blurring in 2D SE-EPI (along the phase-encoding direction). In a visual paradigm, the BOLD sensitivity of 3D-GRASE was found to be superior due to its higher temporal signal-to-noise ratio (tSNR). High resolution cortical depth profiles suggested that the contrast mechanisms are similar between the two sequences, however, 2D SE-EPI had a higher surface bias owing to the higher T(*) 2 contribution of the longer in-plane EPI echo-train for full field of view compared to the reduced field of view of zoomed 3D-GRASE.
There is emerging evidence that sampling the blood-oxygen-level-dependent (BOLD) response with high temporal resolution opens up new avenues to study the in vivo functioning of the human brain with functional magnetic resonance imaging. Because the speed of sampling and the signal level are intrinsically connected in magnetic resonance imaging via the T1 relaxation time, optimization efforts usually must make a trade-off to increase the temporal sampling rate at the cost of the signal level. We present a method, which combines a sparse event-related stimulus paradigm with subsequent data reshuffling to achieve high temporal resolution while maintaining high signal levels (HiHi). The proof-of-principle is presented by separately measuring the single-voxel time course of the BOLD response in both the primary visual and primary motor cortices with 100-ms temporal resolution.
Resting-state functional MRI (rs-fMRI) studies have revealed specific low-frequency hemodynamic signal fluctuations (<0.1 Hz) in the brain, which could be related to neuronal oscillations through the neurovascular coupling mechanism. Given the vascular origin of the fMRI signal, it remains challenging to separate the neural correlates of global rs-fMRI signal fluctuations from other confounding sources. However, the slow-oscillation detected from individual vessels by single-vessel fMRI presents strong correlation to neural oscillations. Here, we use recurrent neural networks (RNNs) to predict the future temporal evolution of the rs-fMRI slow oscillation from both rodent and human brains. The RNNs trained with vessel-specific rs-fMRI signals encode the unique brain oscillatory dynamic feature, presenting more effective prediction than the conventional autoregressive model. This RNN-based predictive modeling of rs-fMRI datasets from the Human Connectome Project (HCP) reveals brain state-specific characteristics, demonstrating an inverse relationship between the global rs-fMRI signal fluctuation with the internal default-mode network (DMN) correlation. The RNN prediction method presents a unique data-driven encoding scheme to specify potential brain state differences based on the global fMRI signal fluctuation, but not solely dependent on the global variance.
We reviewed recent animal studies of neurovascular coupling with in vivo two-photon excitation laser scanning fluorescence microscopy (two-photon microscopy). Two-photon microscopy was introduced into the field of biomedical imaging by Denk et al. in 1990. Since then, the technique has enabled us to directly observe the cell-to-cell interactions involved in neurovascular coupling in in vivo animal brains. Recent studies have shown that neurovascular coupling is accompanied by two microvascular events, (i) an increase of red blood cell speed in brain capillaries at the region of evoked neural activity, and (ii) vasodilation of the upstream pre-capillary and penetrating arterioles. However, the physiological mechanism regulating these microvascular responses and their consequences for central nervous system function remain incompletely understood. Future studies with in vivo two-photon imaging must address these issues with multiple live cell imaging approach. A deeper understanding of neurovascular coupling mechanism will have broad implications for the study of neurodegenerative disorders and brain aging.
Neuroergonomics is to provide the design of effective human machine systems by determining tendencies and characteristics of humans, and to try to understand brain. In neuroergonomics, it is important not to take a snapshot of the brain but to monitor it during the study. Neuroimaging techniques (NTs) are used to display the brain during the study. The NTs selection problem includes many qualitative criteria that decision makers have difficulties in making decision and they have uncertainty. The aim of this study is to evaluate the NTs by using AHP and TOPSIS methods based on Intuitionistic Fuzzy Set (IFS). IFS provides information on the membership, non-membership and hesitancy functions. It is useful tool to deal with uncertainty and fuzziness of complex problems. Because of these features and obtain to a more complete evaluation and more precise results, IF-AHP&TOPSIS method is appropriate for the problem of the NTs selection. In this regard, IF-AHP method is used to determine the criteria weights and then IF-TOPSIS method is conducted for ranking alternatives, the comparison analysis was performed using IF-VIKOR method. As a result of the literature review, it seen that there is no study about the evaluation of NTs before.
In recent years, data-driven machine learning (ML) algorithms have seen increased use to study brain activity fMRI time series. Giving mathematical solutions by constructing quantitative models has proved to be a reliable approach to overcome clinical obstacles. These algorithms provide non-invasive tools to analyze brain activity and pave the way to discover biomedical results that can guide physicians to make more precise clinical predictions. One goal of this dissertation was to facilitate noninvasive localization of the epileptic focus. We designed a deep learning algorithm to classify the patients by using some of the interactivity coefficients as the input of a neural network (NN) and introduced parsimony constraints to build a very restricted MLP to avoid overfitting. Intra/Inter-region connections obtained from resting-state fMRI showed a strong association to clinical diagnosis of seizure onset zone at the lobe level. The results may improve the surgical outcomes as successful seizure surgery is predicated upon the ability to localize the seizure onset zone. We also narrowed down and detected a more accurate focus within each lobe. Another goal of the dissertation was to combine spectral analysis of graph Laplacians with simulated annealing to automatically generate optimized clustering of time series by minimizing the clustering cost function. We explained and implemented this method on cortex parcels. Additionally, Graph Mining algorithms have been investigated with the achievement of binary classification. We applied a Frequent Subgraph Mining algorithm to mine the frequent subgraphs in a graph data set of brain activity and then achieved feature vectors to represent the graphs. The method was successful in some binary classification tasks. It also provided useful information about the functional connectivity of patients in the same class and helped to gain a deeper insight into the topological differences between different patients with different focuses.
Neuroimaging techniques are widely used to investigate the function of the human brain, but none are currently able to accurately localize neuronal activity with both high spatial and temporal specificity. Here, a new in vivo MRI acquisition and analysis technique based on the spin‐lock mechanism is developed to noninvasively image local magnetic field oscillations resulting from neuroelectric activity in specifiable frequency bands.
Simulations, phantom experiments, and in vivo experiments using an eyes‐open/eyes‐closed task in 8 healthy volunteers were performed to demonstrate its sensitivity and specificity for detecting oscillatory neuroelectric activity in the alpha‐band (8‐12 Hz). A comprehensive postprocessing procedure was designed to enhance the neuroelectric signal, while minimizing any residual hemodynamic and physiological confounds.
The phantom results show that this technique can detect 0.06‐nT magnetic field oscillations, while the in vivo results demonstrate that it can image task‐based modulations of neuroelectric oscillatory activity in the alpha‐band. Multiple control experiments and a comparison with conventional BOLD functional MRI suggest that the activation was likely not due to any residual hemodynamic or physiological confounds.
These initial results provide evidence suggesting that this new technique has the potential to noninvasively and directly image neuroelectric activity in the human brain in vivo. With further development, this approach offers the promise of being able to do so with a combination of spatial and temporal specificity that is beyond what can be achieved with existing neuroimaging methods, which can advance our ability to study the functions and dysfunctions of the human brain.
To study large sets of interacting time series, we combine spectral analysis of graph Laplacians with simulated annealing to automatically generate optimized clustering of time series, by minimization of cost functions characterizing clustering quality. We apply these techniques to evaluation of connectivity between cortex regions, via analysis of cortex activity recordings by sequences of 3-dimensional fMRI images.
Les mécanismes précis à l’origine de la dépression ne sont pas encore élucidés. L’avènement des techniques de neuro-imagerie fonctionnelle telle que l’imagerie par résonance magnétique fonctionnelle (fMRI) fournit un outil puissant permettant non seulement de définir les circuits neurobiologiques perturbés dans la dépression, mais aussi de mieux comprendre la contribution de chaque région. Les objectifs de ce travail ont consisté à mettre en évidence : (i) les clusters neuronaux impliqués dans l’évaluation hédonique d’un odorat, (ii) les anomalies cérébrales fonctionnelles sous-tendant les déficits olfactifs dans l’épisode de dépression caractérisée (EDC) et (iii) les modulations de ces anomalies suite à un traitement d’antidépresseur. Trente-huit patients dépressifs et trente sujets sains ont été sélectionnés pour réaliser un examen de fMRI comprenant trois tâches olfactives, les trois odeurs sont la menthe crépue (odeur agréable), bois de santal (odeur neutre) et le lie de vin (odeur désagréable). D’après notre étude nous avons conclu que les patients déprimés présentent des anomalies de fonctionnement dans le thalamus qui peut être considéré un marqueur efficace pour le pronostic de la dépression. De plus, la fMRI constitue un bon outil pour juger de l’efficacité du traitement antidépresseur.
Background and purpose:
The goal of this study was to assess changes in the resting-state networks (RSNs) of patients with multiple sclerosis (MS) after a cognitive rehabilitation program (CRP), by retrospectively analyzing functional magnetic resonance imaging (fMRI) studies using the classical block design.
Fifteen patients with MS (2 primary progressive, 3 relapsing-remitting, 10 secondary progressive) were scanned before and after the CRP on a 1.5T MRI scanner. In addition, patients underwent pre- and post-CRP neuropsychological assessment using a battery of standardized tests. Five healthy individuals were scanned at the same time points to confirm the test-retest reliability of the imaging technique. For each study, the individual fMRI blocks of rest were merged to produce a "pseudo"-resting-state (pseudo-RS) of 3 minutes duration. RS studies were analyzed with the MELODIC toolbox. A dual regression analysis was applied to estimate the longitudinal changes in RSNs of patients and test controls relative to a set of predefined RSNs used as templates.
In healthy individuals, there were no significant differences in RSN results between the two time points studied. In the group of patients with MS, significant differences were found post-CRP in the visual medial, cerebellar, auditory, and frontal-executive RSNs. Furthermore, synchronization increases in the frontal-executive RSN were associated with cognitive improvement on neuropsychological testing.
Results obtained using a pseudo-RS approach to analyze data from block-design fMRI studies suggest that a CRP of 5 weeks' duration induces measurable changes in specific RSNs of patients with MS.
Functional neuroimaging techniques, first positron emission tomography (PET) and later functional MRI (fMRI), have revolutionized cognitive neuroscience. These tools have also greatly improved our understanding of how language is implemented in the brain. Almost from the beginning, fMRI was also applied as a tool for language mapping in surgical practice because of its obvious benefits: high-resolution whole-brain mapping without the need for invasive procedures. Other clinical applications that have been investigated, although less frequently, are the use of fMRI as a tool to help diagnose or understand diseases that lack clear neuroanatomical characteristics or as a predictor for language outcome after stroke (see Chap. 9).
Mitochondrial function is critical to maintain high rates of oxidative metabolism supporting energy demands of both spontaneous and evoked neuronal activity in the brain. Mitochondria not only regulate energy metabolism, but also influence neuronal signaling. Regulation of “energy metabolism” and “neuronal signaling” (i.e. neurometabolic coupling), which are coupled rather than independent can be understood through mitochondria’s integrative functions of calcium ion (Ca²⁺) uptake and cycling. While mitochondrial Ca²⁺ do not affect hemodynamics directly, neuronal activity changes are mechanistically linked to functional hyperemic responses (i.e. neurovascular coupling). Early in vitro studies lay the foundation of mitochondrial Ca²⁺ homeostasis and its functional roles within cells. However, recent in vivo approaches indicate mitochondrial Ca²⁺ homeostasis as maintained by the role of mitochondrial Ca²⁺ uniporter (mCU) influences system-level brain activity as measured by a variety of techniques. Based on earlier evidence of subcellular cytoplasmic Ca²⁺ microdomains and cellular bioenergetic states, a mechanistic model of Ca²⁺ mobilization is presented to understand systems-level neurovascular and neurometabolic coupling. This integrated view from molecular and cellular to the systems level, where mCU plays a major role in mitochondrial and cellular Ca²⁺ homeostasis, may explain the wide range of activation-induced coupling across neuronal activity, hemodynamic, and metabolic responses.
Contrast-to-noise ratio (CNR) in blood oxygenation level-dependent (BOLD) based functional MRI (fMRI) studies is a fundamental parameter to determine statistical significance and therefore to map functional activation in the brain. The CNR is defined here as BOLD contrast with respect to temporal fluctuation. In this study, a theoretical noise model based on oxygenation-sensitive MRI signal formation is proposed. No matter what the noise sources may be in the signal acquired by a gradient-echo echo-planar imaging pulse sequence, there are only three noise elements: apparent spin density fluctuations, S(0)(t); transverse relaxation rate fluctuations, R(2) (*)(t); and thermal noise, n(t). The noise contributions from S(0)(t), R(2) (*)(t), and n(t) to voxel time course fluctuations were evaluated as a function of echo time (TE) at 3 T. Both noise contributions caused by S(0)(t) and R(2) (*)(t) are significantly larger than that of thermal noise when TE = 30 ms. In addition, the fluctuations between S(0)(t) and R(2) (*)(t) are cross-correlated and become a noise factor that is large enough and cannot be ignored. The experimentally measured TE dependences of noise, temporal signal-to-noise ratio, and BOLD CNR in finger-tapping activation regions were consistent with the proposed model. Furthermore, the proposed theoretical models not only unified previously proposed BOLD CNR models, but also provided mechanisms for interpreting apparent controversies and limitations that exist in the literature.
In the two decades since its discovery, functional magnetic resonance imaging (fMRI) has seen a revolution in its ability to image brain function, going from early experiments demonstrating relatively course images of activity in the visual cortex, to mapping cortical columns, and to “brain reading” that constructs mental experiences of an individual, all using the fact that we were endowed with a complex paramagnetic molecule sequestered in our blood vessels and that neuronal activity has spatially-specific metabolic and physiologic consequences. These developments owe their success in part to significant improvements in our understanding of underlying mechanisms operative in functional imaging. These mechanisms and how they come into different data collection schemes are reviewed in this chapter. At the same time, we have seen major advances and refinements in instrumentation, which are also touched upon in this chapter, such as the introduction of ultrahigh field instruments with ever increasing capabilities, novel data acquisition strategies, and new image analysis methods, all of which also dramatically improve data quality. Some of these developments have not yet been incorporated into routine use. If history is a guide, however, the fantastically dynamic nature of the MR methodology, and the very large amount of effort committed to this field of research would predict that in a decade or two, fMRI may be performed using totally different approaches and provide substantially better information than the richness we experience with techniques at the cutting edge today.
Functional MRI (fMRI) allows non-invasive indirect measurement of neuronal activity and imaging of activated cortical areas. Measurements are based on the fact that brain stimulation is correlated with an increased local brain metabolism. This metabolic activity causes local changes of the magnetic properties of blood, which can be imaged by fMRI due to a hemodynamic effect (changes in blood flow and blood volume).
With echo-planar imaging (EPI) images may be acquired in less than 1 s , providing many advantages relevant to clinical diagnosis. In addition to the practical virtues of faster image acquisition and reduced sensitivity to motion artifact, the technique allows investigation of physiological processes such as diffusion and perfusion.
Blood oxygenation level-dependent (BOLD) MRI, arterial spin labeling (ASL) and dynamic contrast enhancement (DCE) are current magnetic resonance imaging (MRI) techniques allowing the non-invasive functional assessment of peripheral microvasculature in healthy and diseased individuals. The functional imaging of skeletal muscle microvasculature helps to understand muscular and vascular physiology and alterations of microcirculation under certain pathological conditions such as peripheral arterial occlusive disease, diabetes mellitus, chronic compartment syndrome and rheumatic disorders. BOLD MRI uses blood as an endogenous contrast agent provided by the different magnetic properties of oxy- and deoxyhemoglobin. The BOLD contrast in skeletal muscle tissue primarily arises from the microcirculation yielding a very sensitive tool for alterations of the physiological oxygen supply and demand. However, the complex nature of the BOLD contrast’s origin also entails a variety of variables complicating the interpretation of BOLD signal changes. ASL’s ability to directly measure muscle perfusion may prove to be a powerful tool for the evaluation of disease progression and the evaluation of therapies aimed at improving muscle perfusion. As is the case with BOLD MRI, this holds particularly true for patients who are unable to receive contrast agents, a collective which is often afflicted with vascular impairments. Dynamic contrast enhanced MRI may contribute considerably to objectively evaluate many musculoskeletal diseases through its ability to measure multiple microvascular properties. The potential of these three MRI methods to non-invasively assess disease severity and the efficacy of new therapeutic strategies, such as stem cell and gene therapy, renders them as very appealing future research targets.
Cognitive neuroscience is a discipline that attempts to determine the neural mechanisms underlying cognitive processes. Specifically, cognitive neuroscientists test hypotheses about brain-behavior relationships organized along two conceptual domains: functional specialization-the idea that functional modules exist within the brain, that is, areas of the cerebral cortex that are specialized for a specific cognitive process, and functional integration-the idea that a cognitive process can be an emergent property of interactions among a network of brain regions that suggests that a brain region can play a different role across many functions.
The field of drug development and discovery encounters a number of challenges in identifying effective therapeutics to treat central nervous system (CNS) diseases. Experimental methods such as pharmacokinetic/pharmacodynamic (PK/PD) modeling and behavioral testing have been the conventional means to assess drug efficacy. Here we introduce functional Magnetic Resonance Imaging (fMRI) as a complimentary technique that can be implemented to assess the effectiveness of a therapeutic in CNS disease. FMRI has the unique ability to characterize the de novo drug effect on specific CNS targets, as is done in Positron Emission Tomography, as well as determine how neuronal substrates or networks are influenced by the therapeutic of interest during sensory stimulation or cognitive and motor tasks. Furthermore, fMRI measures can easily be related to the results obtained from conventional standards, such as PK/PD modeling. FMRI is believed to be a promising experimental method that can assist in defining drug effect in early stages of drug development and discovery; and thus, improve the go-no-go decision-making process of newly identified drugs to treat CNS disease.
Functional magnetic resonance imaging (fMRI) and particularly resting state fMRI (rs-fMRI) is widely used to investigate resting state brain networks (RSNs) on the systems level. Echo planar imaging (EPI) is the state-of-the-art imaging technique for most fMRI studies. Therefore, improvements of EPI might lead to increased sensitivity for a large amount of studies performed every day. A number of developments to shorten acquisition time have been recently proposed and the multiband technique, allowing the simultaneous acquisition of multiple slices yielding an equivalent reduction of measurement time, is the most promising among them. While the prospect to significantly reduce acquisition time by means of high multiband acceleration factors (M) appears tempting, signal quality parameters and the sensitivity to detect common RSNs with increasing M-factor have only been partially investigated up to now. In this study, we therefore acquired rs-fMRI data from 20 healthy volunteers to systematically investigate signal characteristics and sensitivity for brain network activity in datasets with increasing M-factor, M = 2 − 4. Combined with an inplane, sensitivity encoding (SENSE), acceleration factor, S = 2, we applied a maximal acceleration factor of 8 (S2×M4). Our results suggest that an M-factor of 2 (total acceleration of 4) only causes negligible SNR decrease but reveals common RSN with increased sensitivity and stability. Further M-factor increase produced random artifacts as revealed by signal quality measures that may affect interpretation of RSNs under common scanning conditions. Given appropriate hardware, a mb-EPI sequence with a total acceleration of 4 significantly reduces overall scanning time and clearly increases sensitivity to detect common RSNs. Together, our results suggest mb-EPI at moderate acceleration factors as a novel standard for fMRI that might increase our understanding of network dynamics in healthy and diseased brains.
Functional magnetic resonance imaging (fMRI) provides noninvasive localisation and lateralisation of specific brain functions by measuring local hemodynamic changes coupled to neuronal activation. Different magnetic properties of oxygenated (diamagnetic) and deoxygenated (paramagnetic) hemoglobin are exploited to generate the blood oxygen level dependent (BOLD) contrast. Diffusion tensor magnetic resonance imaging (DTI) measures anisotropic (directional) diffusion of protons along myelinated fibers and thereby provides detailed information on the white matter architecture. Specific white matter tracts can be reconstructed using diffusion tensor tractography (DTT). During the last two decades both novel MR-modalities have revolutionised the imaging research on human brain function and structural connectivity under physiological and pathological conditions.
The greatest merit of in vivo magnetic resonance spectroscopy (MRS) methodology used in brain research is its ability to noninvasively determine cerebral metabolites, metabolic rates and their dynamic changes caused by physiological or pathological perturbations. The utility of in vivo MRS is further enhanced with high/ultrahigh magnetic field strength instruments because of significant gains in detection sensitivity and improvements in spectral resolution. Recent progress of in vivo 31P and 17O MRS methodologies at high field has further demonstrated great potential and promise for in vivo measurements of crucial metabolic rates with regard to two essential chemical processes: cerebral oxygen utilization and oxidative phosphorylation of ADP. These metabolic rates are tightly linked to each other and are ultimately regulated by ATP consumption. This chapter provides a brief review of the new developments in in vivo 31P and 17O MRS techniques and their applications to the study of cerebral oxidative metabolism in supporting brain activity and function.
This chapter provides an overview of the application of functional magnetic resonance imaging (FMRI) to addiction research. FMRI offers addiction researchers the opportunity to objectively assess neural signatures of subjective states, such as craving, withdrawal, effort, and associated emotional states. The chapter reviews the conceptual basis and empirical findings from applications of FMRI in addiction research. Conceptual basis for applying FMRI methodologies to understand drug addiction is twofold. First, it permits neurocognitive characterization of processes that are known to be implicated in addictive behavior. Second, innovations in FMRI permit characterization of novel and unobservable brain characteristics that are relevant to addiction. Then, toward informing future FMRI research, the chapter provides a critical overview of FMRI methodology, from study and paradigm design to data analysis. Finally, as the FMRI methods reflect a work-in-progress, it concludes by discussing challenges and future directions.
Injectable extended-release naltrexone (XRNTX) presents an effective therapeutic strategy for opioid addiction, however its utility could be hampered by poor adherence. To gain a better insight into this phenomenon, we utilized blood oxygenation level-dependent functional magnetic resonance imaging (fMRI) in conjunction with a validated cue-induced craving procedure to examine neural correlates of XRNTX adherence. We operationalized treatment adherence as the number of monthly XRNTX injections (range: 0-3) administered to a group of fully detoxified heroin-dependent subjects (n=32). Additional outcomes included urine toxicology screening and self-reported tobacco use. The presented heroin-related visual cues reliably elicited heroin craving in all tested subjects. Nine, five, three and 15 of the participants, respectively, received zero, one, two and three XRNTX injections, predicted by the individual baseline fMRI signal change in response to the cues in the medial prefrontal cortex, a brain region involved in inhibitory self-control and emotional appraisal. The incidence of opioid-positive urines during the XRNTX therapy was low and remained about half the pre-treatment rate after the XRNTX ended. During the treatment, cigarette smoking behaviors followed patterns of opioid use, while cocaine consumption was increased with reductions in opioid use. The present data support the hypothesis that medial prefrontal cortex functions are involved in adherence to opioid antagonist therapy. A potential role of concurrent non-opioid addictive substances consumption during the XRNTX pharmacotherapy warrants further investigation. Our findings set the stage for further bio-behavioral investigations of the mechanisms of relapse prevention in opioid dependence.
A new method for studying membrane transport is presented. High resolution n.m.r. is used to measure the distribution of small molecules between the intracellular and extracellular compartments. The method uses spin-echo techniques and relies on a difference in the magnetic susceptibility of the media inside and outside of cells. It also provides simultaneous information on the metabolic status of the cell. The method is illustrated by a study of alanine and lactate transport in the human erythrocyte.
Knowledge of regional cerebral hemodynamics has widespread application for both physiological research and clinical assessment because of the well-established interrelation between physiological function, energy metabolism, and localized blood supply. A magnetic resonance technique was developed for quantitative imaging of cerebral hemodynamics, allowing for measurement of regional cerebral blood volume during resting and activated cognitive states. This technique was used to generate the first functional magnetic resonance maps of human task activation, by using a visual stimulus paradigm. During photic stimulation, localized increases in blood volume (32 +/- 10 percent, n = 7 subjects) were detected in the primary visual cortex. Center-of-mass coordinates and linear extents of brain activation within the plane of the calcarine fissure are reported.
Magnetoencephalography (MEG) monitors magnetic field amplitudes, which are time averages of evoked neuronal responses. This method can detect magnetic fields emanating from the brain and localize the neuronal source. The location of somatosensory neuronal sources for voluntary right thumb and right index finger flexions were determined in four normal volunteers by using a seven-sensor neuromagnetometer inside a magnetically shielded room. These neuronal sources were then identified on the individual's respective CT or MR scans, and correlation was accomplished by geometric calculations, direct cranial measurement, and surface marker identification. Specific functional magnetic fields were located over the appropriate sensory motor cortex; however, there was considerable variation in the exact site. Magnetoencephalography combined with CT and MR may improve localization of normal and abnormal neurologic function.
At high and medium magnetic field, the transverse NMR relaxation rate (T2−1) of water protons in blood is determined predominantly by the oxygenation state of haemoglobin. T2−1 dependes quadratically on the field strength and on the proportion of haemoglobin that is deoxygenated. Deoxygenation increases the volume magnetic susceptibility within the erythrocytes and thus creates local field gradients around these cells. From volume susceptibility measurements and the dependence of T2−1 on the pulse rate in the Carr-Purcell-Meiboom-Gill experiment, we show that the increase in T2−1 with increasing blood deoxygenation arises from diffusion of water through these field gradients.
When deoxygenated, blood behaves as an effective susceptibility contrast agent. Changes in brain oxygenation can be monitored using gradient-echo echo-planar imaging. With this technique, difference images also demonstrate that blood oxygenation is increased during periods of recovery from respiratory challenge.
Inherent differences in tissue magnetic susceptibility produce inhomogeneities in the static magnetic field which give rise to an additional dephasing of the transverse magnetization in gradient-echo images. The enhanced dephasing of the signal results in an increase of the apparent relaxation rate 1/T2* and a corresponding decrease in signal intensity. These effects have been used to explain the regional loss of marrow signal intensity in the appendicular skeleton, where in the presence of trabecular bone in the proximal tibia there is an enhanced loss of signal compared to the tibial shaft where there is no trabeculation. It has been postulated that differences in tissue magnetic susceptibility arising due to the marrow--trabeculae interface give rise to magnetic field inhomogeneities and a reduced T2*. In this study computer simulations are used to determine whether susceptibility differences comparable to that between trabecular bone and tissue relate to the reduction of tissue T2* and whether the reduction in T2* is also related to the concentration and magnitude of susceptibility differences. In addition the effects of the spatial distribution of these particulate discontinuities in susceptibility on the measured relaxation time T2* are also estimated. This model demonstrates that 1/T2* increases as the number density and magnitude of such susceptibility differences increase. In a pixel of linear dimension L consisting of material simulating tissue water, the presence of circular point susceptibility differences of dimension 0.001 L with magnetic susceptibility equivalent to trabecular bone, 1/T2*, increases at a rate of 1.60 x 10(-2) s-1/N for N ranging from 25-2500. Differences in magnetic susceptibility that are less than that between soft tissue and trabecular bone are also modeled and the simulations demonstrate that differences in magnetic susceptibility, much lower than that between trabecular bone and tissue equivalent interfaces, also produce a relaxation rate enhancement in gradient-echo images.
The use of magnetic resonance (MR) imaging is investigated for noninvasively estimating the oxygen saturation of human blood (%HbO2) in vivo by means of relaxation characteristics identified in earlier MR spectrometry studies. To this end, a sequence is presented for determining the T2 of vascular blood in regions in which motions of the body and of the blood itself present a major challenge. With use of this sequence on a commercial 1.5-T whole-body imager, the relationship between the T2 and %HbO2 of blood is calibrated in vitro for the conditions expected in vivo. T2 varies predictably from about 30 to 250 msec as %HbO2 varies from 30% to 96%. T2 values measured in situ for vascular blood in the mediastinum of several healthy subjects qualitatively reflected the behavior observed in vitro. Estimates of %HbO2 for these vessels obtained with the in vitro calibration appear reasonable, particularly for venous blood, although difficulties arise in selecting the appropriate calibration factors. These encouraging initial results support a more systematic study of potential sources of error and an examination of the accuracy of in vivo measurements by comparison with direct measurements of %HbO2 in vessels.
The stable xenon CT method of measuring cerebral blood flow has been investigated in research studies for over 10 years. Recently, it has been gaining clinical acceptance, primarily owing to a combination of several unique advantages it holds over other cerebral blood flow measurement techniques. The accuracy of this technique in quantifying low cerebral blood flow gives it a unique application in cases of brain death and acute stroke and it can be repeated after an interval of 20 min. making it possible to evaluate autoregulation and cerebrovascular reserve. Furthermore, cerebral blood flow information is directly coupled to CT anatomy. Although it is more difficult to administer than a standard CT scan, careful monitoring can ensure patient safety during the examination. In this article we review the physiologic and technical bases for the clinical application of xenon CT-derived quantitative cerebral blood flow information and discuss the advantages and disadvantages of the technique. We also describe its current clinical applications, including its usefulness in the evaluation of acute stroke, occlusive vascular disease, carotid occlusion testing, vasospasm, arteriovenous malformations, and head trauma management.
The design of magnetic particles as a magnetic resonance contrast agent will rely on the prediction of their ability to induce transverse relaxation among the surrounding protons. There exists several divergent predictions of the contribution of these agents to 1/T2. This article points out a problem, commonly overlooked, in the development of expressions for the relaxation enhancement which has led some workers to the derivation of results inappropriate for large magnetic particles. The size of the magnetic inhomogeneity created by the particle precludes the averaging of the interaction over a single proton unless it experiences an average field in the time tau between pulses. Computer simulations following the trajectories of diffusing water molecules in inhomogeneous fields are shown to be the correct approach to dealing with large inhomogeneities.
At high magnetic fields (7 and 8.4 T), water proton magnetic resonance images of brains of live mice and rats under pentobarbital anesthetization have been measured by a gradient echo pulse sequence with a spatial resolution of 65 x 65-microns pixel size and 700-microns slice thickness. The contrast in these images depicts anatomical details of the brain by numerous dark lines of various sizes. These lines are absent in the image taken by the usual spin echo sequence. They represent the blood vessels in the image slice and appear when the deoxyhemoglobin content in the red cells increases. This contrast is most pronounced in an anoxy brain but not present in a brain with diamagnetic oxy or carbon monoxide hemoglobin. The local field induced by the magnetic susceptibility change in the blood due to the paramagnetic deoxyhemoglobin causes the intra voxel dephasing of the water signals of the blood and the surrounding tissue. This oxygenation-dependent contrast is appreciable in high field images with high spatial resolution.
Unusually high image contrast in vivo magnetic resonance imaging of the brain becomes observable at high magnetic fields when the blood oxygenation level is lowered. The cause of the contrast has been attributed to a magnetic susceptibility effect induced by paramagnetic deoxyhemoglobin in red cells. When the cylinder axis of a blood vessel is not parallel to the main magnetic field, the susceptibility difference produces varying local fields around the blood vessel. In gradient-echo images, not in spin-echo images, these local fields cause intravoxel dephasing of the water signal of the surrounding tissue. This description of the contrast enhancement has been confirmed by a series of in vitro blood sample experiments and image simulations. A predicted contrast change has been demonstrated in brain images of a mouse placed at two different orientations in the magnet. From the simulated images, the dependence of the contrast on the field strength has been estimated.
T2 values were measured at 0.23 and 4.7 T for deoxygenated blood samples (43%-73% O2 saturation) with hematocrits of 18%-100%. An increase in the hematocrit produced a marked reduction in T2 at both field strengths. Cell lysis did not abolish the T2 effect at either field strength. The authors conclude that the increase in hemoglobin concentration caused by formation of a retracted clot is a cause of the hypointense appearance of acute hemorrhage compared with brain on T2-weighted clinical magnetic resonance images. This is particularly important on low-field-strength systems, which are not sensitive to the T2 shortening effects of paramagnetic intracellular deoxyhemoglobin.
Positron-emission tomography (PET) can localize functions of the human brain by imaging regional cerebral blood flow (CBF) during voluntary behaviour. Functional brain mapping with PET, however, has been hindered by PET's poor spatial resolution (typically greater than 1 cm). We have developed an image-analysis strategy that can map functional zones not resolved by conventional PET images. Brain areas selectively activated by a behavioural task can be isolated by subtracting a paired control-state image from the task-state image, thereby removing areas not recruited by the task. When imaged in isolation the centre of an activated area can be located very precisely. This allows subtle shifts in response locale due to changes in task to be detected readily despite poor spatial resolution. As an initial application of this strategy we mapped the retinal projection topography of human primary visual cortex. Functional zones separated by less than 3 mm (centre-to-centre) were differentiated using PET CBF images with a spatial resolution of 18 mm. This technique is not limited to a particular brain area or type of behaviour but does require that the increase in CBF produced by the task be both intense and focal.
The variation with field strength or interecho interval of the T1 and T2 relaxation times of oxyhemoglobin (HbO2), deoxyhemoglobin (Hb), and methemoglobin (MHb) in either intact or lysed red blood cells was studied with a variable field (0.19-1.4 T) nuclear magnetic resonance spectroscopy unit. The T2 relaxation time of intracellular HbO2 decreased slightly with increasing field strength and interecho interval. The T2 relaxation times of intracellular Hb and MHb decreased markedly with increasing field strength and interecho interval. This T2 proton relaxation enhancement increased as the square of the applied field strength and was 1.6 times stronger for intracellular MHb than for intracellular Hb. The T2 relaxation enhancement is secondary to the loss of transverse phase coherence of water protons that diffuse across cellular magnetic field gradients. These field gradients occur when an external field is applied to a region with gradients of magnetic susceptibility. The heterogeneity of magnetic susceptibility is caused by the heterogeneous distribution (only intracellular) of the paramagnetic molecules (Hb or MHb). The T2 relaxation times of red cell lysates (homogeneous magnetic susceptibility) were independent of field strength or interecho interval. There was a decrease in the T1 relaxation times when the red cells were lysed. This may be due to an increase in the slow motional components of water molecules, because of the decrease in the average distance between water and hemoglobin molecules in the lysate. The T1 relaxation times of all the MHb samples were shortened because of proton-electron dipolar-dipolar relaxation enhancement. All the T1 relaxation times increased with increasing field strength.
The magnetic resonance imaging appearance of blood, as with other body tissues, is affected strongly by magnetic relaxation rates of the water protons. For blood containing only oxyhemoglobin, as for most tissues, the relaxation times are determined by diamagnetic effects related primarily to protein content. However blood containing either deoxyhemoglobin or methemoglobin exhibits additional paramagnetic relaxation effects, which have important consequences for magnetic resonance imaging of hematomas. First, the field inhomogeneity created by the concentration of paramagnetism in the red blood cells lowers the effective T2. This effect depends on field strength, and so is more striking at high fields, and is greater if gradient echoes are used. In fact, the observation of a difference in T2 with the two different echo methods provides an unequivocal indication of field inhomogeneity such as is produced by erythrocytes. A second paramagnetic relaxation effect is the direct interaction of protons with the electron spin of methemoglobin, which markedly lowers both T1 and T2. This effect is important in the imaging of hematomas that are at least several days old, after significant conversion of hemoglobin to the met form has taken place.