139 resultados para BOLD FMRI SIGNAL

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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Functional magnetic resonance imaging (fMRI) is presently either performed using blood oxygenation level-dependent (BOLD) contrast or using cerebral blood flow (CBF), measured with arterial spin labeling (ASL) technique. The present fMRI study aimed to provide practical hints to favour one method over the other. It involved three different acquisition methods during visual checkerboard stimulation on nine healthy subjects: 1) CBF contrast obtained from ASL, 2) BOLD contrast extracted from ASL and 3) BOLD contrast from Echo planar imaging. Previous findings were replicated; i) no differences between the three measurements were found in the location of the activated region; ii) differences were found in the temporal characteristics of the signals and iii) BOLD has significantly higher sensitivity than ASL perfusion. ASL fMRI was favoured when the investigation demands for perfusion and task related signal changes. BOLD fMRI is more suitable in conjunction with fast event related design.

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We combined repetitive transcranial magnetic stimulation (rTMS) and functional magnetic resonance imaging (fMRI) to investigate the functional relevance of parietal cortex activation during the performance of visuospatial tasks. fMRI provides information about local transient changes in neuronal activation during behavioural or cognitive tasks. Information on the functional relevance of this activation was obtained by using rTMS to induce temporary regional deactivations. We thereby turned the physiological parameter of brain activity into an independent variable controlled and manipulated by the experimenter and investigated its effect on the performance of the cognitive tasks within a controlled experimental design. We investigated cognitive tasks that were performed on the same visual material but differed in the demand on visuospatial functions. For the visuospatial tasks we found a selective enhancement of fMRI signal in the superior parietal lobule (SPL) and a selective impairment of performance after rTMS to this region in comparison to a control group. We could thus show that the parietal cortex is functionally important for the execution of spatial judgements on visually presented material and that TMS as an experimental tool has the potential to interfere with higher cognitive functions such as visuospatial information processing.

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Neural correlates of electroencephalographic (EEG) alpha rhythm are poorly understood. Here, we related EEG alpha rhythm in awake humans to blood-oxygen-level-dependent (BOLD) signal change determined by functional magnetic resonance imaging (fMRI). Topographical EEG was recorded simultaneously with fMRI during an open versus closed eyes and an auditory stimulation versus silence condition. EEG was separated into spatial components of maximal temporal independence using independent component analysis. Alpha component amplitudes and stimulus conditions served as general linear model regressors of the fMRI signal time course. In both paradigms, EEG alpha component amplitudes were associated with BOLD signal decreases in occipital areas, but not in thalamus, when a standard BOLD response curve (maximum effect at approximately 6 s) was assumed. The part of the alpha regressor independent of the protocol condition, however, revealed significant positive thalamic and mesencephalic correlations with a mean time delay of approximately 2.5 s between EEG and BOLD signals. The inverse relationship between EEG alpha amplitude and BOLD signals in primary and secondary visual areas suggests that widespread thalamocortical synchronization is associated with decreased brain metabolism. While the temporal relationship of this association is consistent with metabolic changes occurring simultaneously with changes in the alpha rhythm, sites in the medial thalamus and in the anterior midbrain were found to correlate with short time lag. Assuming a canonical hemodynamic response function, this finding is indicative of activity preceding the actual EEG change by some seconds.

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The Default Mode Network (DMN) is a higher order functional neural network that displays activation during passive rest and deactivation during many types of cognitive tasks. Accordingly, the DMN is viewed to represent the neural correlate of internally-generated self-referential cognition. This hypothesis implies that the DMN requires the involvement of cognitive processes, like declarative memory. The present study thus examines the spatial and functional convergence of the DMN and the semantic memory system. Using an active block-design functional Magnetic Resonance Imaging (fMRI) paradigm and Independent Component Analysis (ICA), we trace the DMN and fMRI signal changes evoked by semantic, phonological and perceptual decision tasks upon visually-presented words. Our findings show less deactivation during semantic compared to the two non-semantic tasks for the entire DMN unit and within left-hemispheric DMN regions, i.e., the dorsal medial prefrontal cortex, the anterior cingulate cortex, the retrosplenial cortex, the angular gyrus, the middle temporal gyrus and the anterior temporal region, as well as the right cerebellum. These results demonstrate that well-known semantic regions are spatially and functionally involved in the DMN. The present study further supports the hypothesis of the DMN as an internal mentation system that involves declarative memory functions.

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One of the most consistent findings in the neuroscience of autism is hypoactivation of the fusiform gyrus (FG) during face processing. In this study the authors examined whether successful facial affect recognition training is associated with an increased activation of the FG in autism. The effect of a computer-based program to teach facial affect identification was examined in 10 individuals with high-functioning autism. Blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) changes in the FG and other regions of interest, as well as behavioral facial affect recognition measures, were assessed pre- and posttraining. No significant activation changes in the FG were observed. Trained participants showed behavioral improvements, which were accompanied by higher BOLD fMRI signals in the superior parietal lobule and maintained activation in the right medial occipital gyrus.

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SUMMARY: Multimodal imaging was performed in Rasmussen Encephalitis (RE) during episodes of complex-partial and focal motor status epilepticus including independent component analysis of BOLD-fMRI, arterial spin labeling perfusion imaging and diffusion tensor imaging. The active epileptic network and topographically independent brain areas showed regional hyperperfusion and progressive atrophy. The results suggest that hyperperfusion outside of the epileptic network represent active inflammation in RE and the imaging protocol presented here, allows assessing thereby the disease activity non-invasively.

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In humans, theta band (5-7 Hz) power typically increases when performing cognitively demanding working memory (WM) tasks, and simultaneous EEG-fMRI recordings have revealed an inverse relationship between theta power and the BOLD (blood oxygen level dependent) signal in the default mode network during WM. However, synchronization also plays a fundamental role in cognitive processing, and the level of theta and higher frequency band synchronization is modulated during WM. Yet, little is known about the link between BOLD, EEG power, and EEG synchronization during WM, and how these measures develop with human brain maturation or relate to behavioral changes. We examined EEG-BOLD signal correlations from 18 young adults and 15 school-aged children for age-dependent effects during a load-modulated Sternberg WM task. Frontal load (in-)dependent EEG theta power was significantly enhanced in children compared to adults, while adults showed stronger fMRI load effects. Children demonstrated a stronger negative correlation between global theta power and the BOLD signal in the default mode network relative to adults. Therefore, we conclude that theta power mediates the suppression of a task-irrelevant network. We further conclude that children suppress this network even more than adults, probably from an increased level of task-preparedness to compensate for not fully mature cognitive functions, reflected in lower response accuracy and increased reaction time. In contrast to power, correlations between instantaneous theta global field synchronization and the BOLD signal were exclusively positive in both age groups but only significant in adults in the frontal-parietal and posterior cingulate cortices. Furthermore, theta synchronization was weaker in children and was--in contrast to EEG power--positively correlated with response accuracy in both age groups. In summary we conclude that theta EEG-BOLD signal correlations differ between spectral power and synchronization and that these opposite correlations with different distributions undergo similar and significant neuronal developments with brain maturation.

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Auditory neuroscience has not tapped fMRI's full potential because of acoustic scanner noise emitted by the gradient switches of conventional echoplanar fMRI sequences. The scanner noise is pulsed, and auditory cortex is particularly sensitive to pulsed sounds. Current fMRI approaches to avoid stimulus-noise interactions are temporally inefficient. Since the sustained BOLD response to pulsed sounds decreases with repetition rate and becomes minimal with unpulsed sounds, we developed an fMRI sequence emitting continuous rather than pulsed gradient sound by implementing a novel quasi-continuous gradient switch pattern. Compared to conventional fMRI, continuous-sound fMRI reduced auditory cortex BOLD baseline and increased BOLD amplitude with graded sound stimuli, short sound events, and sounds as complex as orchestra music with preserved temporal resolution. Response in subcortical auditory nuclei was enhanced, but not the response to light in visual cortex. Finally, tonotopic mapping using continuous-sound fMRI demonstrates that enhanced functional signal-to-noise in BOLD response translates into improved spatial separability of specific sound representations.

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Phase locking or synchronization of brain areas is a key concept of information processing in the brain. Synchronous oscillations have been observed and investigated extensively in EEG during the past decades. EEG oscillations occur over a wide frequency range. In EEG, a prominent type of oscillations is alpha-band activity, present typically when a subject is awake, but at rest with closed eyes. The spectral power of alpha rhythms has recently been investigated in simultaneous EEG/fMRI recordings, establishing a wide-range cortico-thalamic network. However, spectral power and synchronization are different measures and little is known about the correlations between BOLD effects and EEG synchronization. Interestingly, the fMRI BOLD signal also displays synchronous oscillations across different brain regions. These oscillations delineate so-called resting state networks (RSNs) that resemble the correlation patterns of simultaneous EEG/fMRI recordings. However, the nature of these BOLD oscillations and their relations to EEG activity is still poorly understood. One hypothesis is that the subunits constituting a specific RSN may be coordinated by different EEG rhythms. In this study we report on evidence for this hypothesis. The BOLD correlates of global EEG synchronization (GFS) in the alpha frequency band are located in brain areas involved in specific RSNs, e.g. the 'default mode network'. Furthermore, our results confirm the hypothesis that specific RSNs are organized by long-range synchronization at least in the alpha frequency band. Finally, we could localize specific areas where the GFS BOLD correlates and the associated RSN overlap. Thus, we claim that not only the spectral dynamics of EEG are important, but also their spatio-temporal organization.

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In functional magnetic resonance imaging (fMRI) coherent oscillations of the blood oxygen level-dependent (BOLD) signal can be detected. These arise when brain regions respond to external stimuli or are activated by tasks. The same networks have been characterized during wakeful rest when functional connectivity of the human brain is organized in generic resting-state networks (RSN). Alterations of RSN emerge as neurobiological markers of pathological conditions such as altered mental state. In single-subject fMRI data the coherent components can be identified by blind source separation of the pre-processed BOLD data using spatial independent component analysis (ICA) and related approaches. The resulting maps may represent physiological RSNs or may be due to various artifacts. In this methodological study, we propose a conceptually simple and fully automatic time course based filtering procedure to detect obvious artifacts in the ICA output for resting-state fMRI. The filter is trained on six and tested on 29 healthy subjects, yielding mean filter accuracy, sensitivity and specificity of 0.80, 0.82, and 0.75 in out-of-sample tests. To estimate the impact of clearly artifactual single-subject components on group resting-state studies we analyze unfiltered and filtered output with a second level ICA procedure. Although the automated filter does not reach performance values of visual analysis by human raters, we propose that resting-state compatible analysis of ICA time courses could be very useful to complement the existing map or task/event oriented artifact classification algorithms.

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Among other auditory operations, the analysis of different sound levels received at both ears is fundamental for the localization of a sound source. These so-called interaural level differences, in animals, are coded by excitatory-inhibitory neurons yielding asymmetric hemispheric activity patterns with acoustic stimuli having maximal interaural level differences. In human auditory cortex, the temporal blood oxygen level-dependent (BOLD) response to auditory inputs, as measured by functional magnetic resonance imaging (fMRI), consists of at least two independent components: an initial transient and a subsequent sustained signal, which, on a different time scale, are consistent with electrophysiological human and animal response patterns. However, their specific functional role remains unclear. Animal studies suggest these temporal components being based on different neural networks and having specific roles in representing the external acoustic environment. Here we hypothesized that the transient and sustained response constituents are differentially involved in coding interaural level differences and therefore play different roles in spatial information processing. Healthy subjects underwent monaural and binaural acoustic stimulation and BOLD responses were measured using high signal-to-noise-ratio fMRI. In the anatomically segmented Heschl's gyrus the transient response was bilaterally balanced, independent of the side of stimulation, while in opposite the sustained response was contralateralized. This dissociation suggests a differential role at these two independent temporal response components, with an initial bilateral transient signal subserving rapid sound detection and a subsequent lateralized sustained signal subserving detailed sound characterization.

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Spatial independent component analysis (sICA) of functional magnetic resonance imaging (fMRI) time series can generate meaningful activation maps and associated descriptive signals, which are useful to evaluate datasets of the entire brain or selected portions of it. Besides computational implications, variations in the input dataset combined with the multivariate nature of ICA may lead to different spatial or temporal readouts of brain activation phenomena. By reducing and increasing a volume of interest (VOI), we applied sICA to different datasets from real activation experiments with multislice acquisition and single or multiple sensory-motor task-induced blood oxygenation level-dependent (BOLD) signal sources with different spatial and temporal structure. Using receiver operating characteristics (ROC) methodology for accuracy evaluation and multiple regression analysis as benchmark, we compared sICA decompositions of reduced and increased VOI fMRI time-series containing auditory, motor and hemifield visual activation occurring separately or simultaneously in time. Both approaches yielded valid results; however, the results of the increased VOI approach were spatially more accurate compared to the results of the decreased VOI approach. This is consistent with the capability of sICA to take advantage of extended samples of statistical observations and suggests that sICA is more powerful with extended rather than reduced VOI datasets to delineate brain activity.

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The aim of the current study was to examine the effect of theta burst repetitive transcranial magnetic stimulation (rTMS) on the blood oxygenation level-dependent (BOLD) activation during repeated functional magnetic resonance imaging (fMRI) measurements. Theta burst rTMS was applied over the right frontal eye field in seven healthy subjects. Subsequently, repeated fMRI measurements were performed during a saccade-fixation task (block design) 5, 20, 35, and 60 min after stimulation. We found that theta burst rTMS induced a strong and long-lasting decrease of the BOLD signal response of the stimulated frontal eye field at 20 and 35 min. Furthermore, less pronounced alterations of the BOLD signal response with different dynamics were found for remote oculomotor areas such as the left frontal eye field, the pre-supplementary eye field, the supplementary eye field, and both parietal eye fields. Recovery of the BOLD signal changes in the anterior remote areas started earlier than in the posterior remote areas. These results show that a) the major inhibitory impact of theta burst rTMS occurs directly in the stimulated area itself, and that b) a lower effect on remote, oculomotor areas can be induced.

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Combined EEG/fMRI recordings offer a promising opportunity to detect brain areas with altered BOLD signal during interictal epileptic discharges (IEDs). These areas are likely to represent the irritative zone, which is itself a reflection of the epileptogenic zone. This paper reports on the imaging findings using independent component analysis (ICA) to continuously quantify epileptiform activity in simultaneously acquired EEG and fMRI. Using ICA derived factors coding for the epileptic activity takes into account that epileptic activity is continuously fluctuating with each spike differing in amplitude, duration and maybe topography, including subthreshold epileptic activity besides clear IEDs and may thus increase the sensitivity and statistical power of combined EEG/fMRI in epilepsy. Twenty patients with different types of focal and generalized epilepsy syndromes were investigated. ICA separated epileptiform activity from normal physiological brain activity and artifacts. In 16/20 patients, BOLD correlates of epileptic activity matched the EEG sources, the clinical semiology, and, if present, the structural lesions. In clinically equivocal cases, the BOLD correlates aided to attribute proper diagnosis of the underlying epilepsy syndrome. Furthermore, in one patient with temporal lobe epilepsy, BOLD correlates of rhythmic delta activity could be employed to delineate the affected hippocampus. Compared to BOLD correlates of manually identified IEDs, the sensitivity was improved from 50% (10/20) to 80%. The ICA EEG/fMRI approach is a safe, non-invasive and easily applicable technique, which can be used to identify regions with altered hemodynamic effects related to IEDs as well as intermittent rhythmic discharges in different types of epilepsy.

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Resting-state functional connectivity (FC) fMRI (rs-fcMRI) offers an appealing approach to mapping the brain's intrinsic functional organization. Blood oxygen level dependent (BOLD) and arterial spin labeling (ASL) are the two main rs-fcMRI approaches to assess alterations in brain networks associated with individual differences, behavior and psychopathology. While the BOLD signal is stronger with a higher temporal resolution, ASL provides quantitative, direct measures of the physiology and metabolism of specific networks. This study systematically investigated the similarity and reliability of resting brain networks (RBNs) in BOLD and ASL. A 2×2×2 factorial design was employed where each subject underwent repeated BOLD and ASL rs-fcMRI scans on two occasions on two MRI scanners respectively. Both independent and joint FC analyses revealed common RBNs in ASL and BOLD rs-fcMRI with a moderate to high level of spatial overlap, verified by Dice Similarity Coefficients. Test-retest analyses indicated more reliable spatial network patterns in BOLD (average modal Intraclass Correlation Coefficients: 0.905±0.033 between-sessions; 0.885±0.052 between-scanners) than ASL (0.545±0.048; 0.575±0.059). Nevertheless, ASL provided highly reproducible (0.955±0.021; 0.970±0.011) network-specific CBF measurements. Moreover, we observed positive correlations between regional CBF and FC in core areas of all RBNs indicating a relationship between network connectivity and its baseline metabolism. Taken together, the combination of ASL and BOLD rs-fcMRI provides a powerful tool for characterizing the spatiotemporal and quantitative properties of RBNs. These findings pave the way for future BOLD and ASL rs-fcMRI studies in clinical populations that are carried out across time and scanners.