244 resultados para Neuroimage


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We propose a novel formulation to solve the problem of intra-voxel reconstruction of the fibre orientation distribution function (FOD) in each voxel of the white matter of the brain from diffusion MRI data. The majority of the state-of-the-art methods in the field perform the reconstruction on a voxel-by-voxel level, promoting sparsity of the orientation distribution. Recent methods have proposed a global denoising of the diffusion data using spatial information prior to reconstruction, while others promote spatial regularisation through an additional empirical prior on the diffusion image at each q-space point. Our approach reconciles voxelwise sparsity and spatial regularisation and defines a spatially structured FOD sparsity prior, where the structure originates from the spatial coherence of the fibre orientation between neighbour voxels. The method is shown, through both simulated and real data, to enable accurate FOD reconstruction from a much lower number of q-space samples than the state of the art, typically 15 samples, even for quite adverse noise conditions.

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OBJECTIVES: The aim of this study was to investigate pathological mechanisms underlying brain tissue alterations in mild cognitive impairment (MCI) using multi-contrast 3 T magnetic resonance imaging (MRI). METHODS: Forty-two MCI patients and 77 healthy controls (HC) underwent T1/T2* relaxometry as well as Magnetization Transfer (MT) MRI. Between-groups comparisons in MRI metrics were performed using permutation-based tests. Using MRI data, a generalized linear model (GLM) was computed to predict clinical performance and a support-vector machine (SVM) classification was used to classify MCI and HC subjects. RESULTS: Multi-parametric MRI data showed microstructural brain alterations in MCI patients vs HC that might be interpreted as: (i) a broad loss of myelin/cellular proteins and tissue microstructure in the hippocampus (p ≤ 0.01) and global white matter (p < 0.05); and (ii) iron accumulation in the pallidus nucleus (p ≤ 0.05). MRI metrics accurately predicted memory and executive performances in patients (p ≤ 0.005). SVM classification reached an accuracy of 75% to separate MCI and HC, and performed best using both volumes and T1/T2*/MT metrics. CONCLUSION: Multi-contrast MRI appears to be a promising approach to infer pathophysiological mechanisms leading to brain tissue alterations in MCI. Likewise, parametric MRI data provide powerful correlates of cognitive deficits and improve automatic disease classification based on morphometric features.

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Recognition of environmental sounds is believed to proceed through discrimination steps from broad to more narrow categories. Very little is known about the neural processes that underlie fine-grained discrimination within narrow categories or about their plasticity in relation to newly acquired expertise. We investigated how the cortical representation of birdsongs is modulated by brief training to recognize individual species. During a 60-minute session, participants learned to recognize a set of birdsongs; they improved significantly their performance for trained (T) but not control species (C), which were counterbalanced across participants. Auditory evoked potentials (AEPs) were recorded during pre- and post-training sessions. Pre vs. post changes in AEPs were significantly different between T and C i) at 206-232ms post stimulus onset within a cluster on the anterior part of the left superior temporal gyrus; ii) at 246-291ms in the left middle frontal gyrus; and iii) 512-545ms in the left middle temporal gyrus as well as bilaterally in the cingulate cortex. All effects were driven by weaker activity for T than C species. Thus, expertise in discriminating T species modulated early stages of semantic processing, during and immediately after the time window that sustains the discrimination between human vs. animal vocalizations. Moreover, the training-induced plasticity is reflected by the sharpening of a left lateralized semantic network, including the anterior part of the temporal convexity and the frontal cortex. Training to identify birdsongs influenced, however, also the processing of C species, but at a much later stage. Correct discrimination of untrained sounds seems to require an additional step which results from lower-level features analysis such as apperception. We therefore suggest that the access to objects within an auditory semantic category is different and depends on subject's level of expertise. More specifically, correct intra-categorical auditory discrimination for untrained items follows the temporal hierarchy and transpires in a late stage of semantic processing. On the other hand, correct categorization of individually trained stimuli occurs earlier, during a period contemporaneous with human vs. animal vocalization discrimination, and involves a parallel semantic pathway requiring expertise.

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Although fetal anatomy can be adequately viewed in new multi-slice MR images, many critical limitations remain for quantitative data analysis. To this end, several research groups have recently developed advanced image processing methods, often denoted by super-resolution (SR) techniques, to reconstruct from a set of clinical low-resolution (LR) images, a high-resolution (HR) motion-free volume. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has been quite attracted by Total Variation energies because of their ability in edge preserving but only standard explicit steepest gradient techniques have been applied for optimization. In a preliminary work, it has been shown that novel fast convex optimization techniques could be successfully applied to design an efficient Total Variation optimization algorithm for the super-resolution problem. In this work, two major contributions are presented. Firstly, we will briefly review the Bayesian and Variational dual formulations of current state-of-the-art methods dedicated to fetal MRI reconstruction. Secondly, we present an extensive quantitative evaluation of our SR algorithm previously introduced on both simulated fetal and real clinical data (with both normal and pathological subjects). Specifically, we study the robustness of regularization terms in front of residual registration errors and we also present a novel strategy for automatically select the weight of the regularization as regards the data fidelity term. Our results show that our TV implementation is highly robust in front of motion artifacts and that it offers the best trade-off between speed and accuracy for fetal MRI recovery as in comparison with state-of-the art methods.

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Imaging in neuroscience, clinical research and pharmaceutical trials often employs the 3D magnetisation-prepared rapid gradient-echo (MPRAGE) sequence to obtain structural T1-weighted images with high spatial resolution of the human brain. Typical research and clinical routine MPRAGE protocols with ~1mm isotropic resolution require data acquisition time in the range of 5-10min and often use only moderate two-fold acceleration factor for parallel imaging. Recent advances in MRI hardware and acquisition methodology promise improved leverage of the MR signal and more benign artefact properties in particular when employing increased acceleration factors in clinical routine and research. In this study, we examined four variants of a four-fold-accelerated MPRAGE protocol (2D-GRAPPA, CAIPIRINHA, CAIPIRINHA elliptical, and segmented MPRAGE) and compared clinical readings, basic image quality metrics (SNR, CNR), and automated brain tissue segmentation for morphological assessments of brain structures. The results were benchmarked against a widely-used two-fold-accelerated 3T ADNI MPRAGE protocol that served as reference in this study. 22 healthy subjects (age=20-44yrs.) were imaged with all MPRAGE variants in a single session. An experienced reader rated all images of clinically useful image quality. CAIPIRINHA MPRAGE scans were perceived on average to be of identical value for reading as the reference ADNI-2 protocol. SNR and CNR measurements exhibited the theoretically expected performance at the four-fold acceleration. The results of this study demonstrate that the four-fold accelerated protocols introduce systematic biases in the segmentation results of some brain structures compared to the reference ADNI-2 protocol. Furthermore, results suggest that the increased noise levels in the accelerated protocols play an important role in introducing these biases, at least under the present study conditions.

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The enhanced functional sensitivity offered by ultra-high field imaging may significantly benefit simultaneous EEG-fMRI studies, but the concurrent increases in artifact contamination can strongly compromise EEG data quality. In the present study, we focus on EEG artifacts created by head motion in the static B0 field. A novel approach for motion artifact detection is proposed, based on a simple modification of a commercial EEG cap, in which four electrodes are non-permanently adapted to record only magnetic induction effects. Simultaneous EEG-fMRI data were acquired with this setup, at 7T, from healthy volunteers undergoing a reversing-checkerboard visual stimulation paradigm. Data analysis assisted by the motion sensors revealed that, after gradient artifact correction, EEG signal variance was largely dominated by pulse artifacts (81-93%), but contributions from spontaneous motion (4-13%) were still comparable to or even larger than those of actual neuronal activity (3-9%). Multiple approaches were tested to determine the most effective procedure for denoising EEG data incorporating motion sensor information. Optimal results were obtained by applying an initial pulse artifact correction step (AAS-based), followed by motion artifact correction (based on the motion sensors) and ICA denoising. On average, motion artifact correction (after AAS) yielded a 61% reduction in signal power and a 62% increase in VEP trial-by-trial consistency. Combined with ICA, these improvements rose to a 74% power reduction and an 86% increase in trial consistency. Overall, the improvements achieved were well appreciable at single-subject and single-trial levels, and set an encouraging quality mark for simultaneous EEG-fMRI at ultra-high field.

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The human connectome represents a network map of the brain's wiring diagram and the pattern into which its connections are organized is thought to play an important role in cognitive function. The generative rules that shape the topology of the human connectome remain incompletely understood. Earlier work in model organisms has suggested that wiring rules based on geometric relationships (distance) can account for many but likely not all topological features. Here we systematically explore a family of generative models of the human connectome that yield synthetic networks designed according to different wiring rules combining geometric and a broad range of topological factors. We find that a combination of geometric constraints with a homophilic attachment mechanism can create synthetic networks that closely match many topological characteristics of individual human connectomes, including features that were not included in the optimization of the generative model itself. We use these models to investigate a lifespan dataset and show that, with age, the model parameters undergo progressive changes, suggesting a rebalancing of the generative factors underlying the connectome across the lifespan.

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A cortical visuomotor network, comprising the medial intraparietal sulcus (mIPS) and the dorsal premotor area (PMd), encodes the sensorimotor transformations required for the on-line control of reaching movements. How information is transmitted between these two regions and which pathways are involved, are less clear. Here, we use a multimodal approach combining repetitive transcranial magnetic stimulation (rTMS) and diffusion tensor imaging (DTI) to investigate whether structural connectivity in the 'reaching' circuit is associated to variations in the ability to control and update a movement. We induced a transient disruption of the neural processes underlying on-line motor adjustments by applying 1Hz rTMS over the mIPS. After the stimulation protocol, participants globally showed a reduction of the number of corrective trajectories during a reaching task that included unexpected visual perturbations. A voxel-based analysis revealed that participants exhibiting higher fractional anisotropy (FA) in the second branch of the superior longitudinal fasciculus (SLF II) suffered less rTMS-induced behavioral impact. These results indicate that the microstructural features of the white matter bundles within the parieto-frontal 'reaching' circuit play a prominent role when action reprogramming is interfered. Moreover, our study suggests that the structural alignment and cohesion of the white matter tracts might be used as a predictor to characterize the extent of motor impairments.

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Chromosome 22q11.2 deletion syndrome (22q11DS) is a genetic disease known to lead to cerebral structural alterations, which we study using the framework of the macroscopic white-matter connectome. We create weighted connectomes of 44 patients with 22q11DS and 44 healthy controls using diffusion tensor magnetic resonance imaging, and perform a weighted graph theoretical analysis. After confirming global network integration deficits in 22q11DS (previously identified using binary connectomes), we identify the spatial distribution of regions responsible for global deficits. Next, we further characterize the dysconnectivity of the deficient regions in terms of sub-network properties, and investigate their relevance with respect to clinical profiles. We define the subset of regions with decreased nodal integration (evaluated using the closeness centrality measure) as the affected core (A-core) of the 22q11DS structural connectome. A-core regions are broadly bilaterally symmetric and consist of numerous network hubs - chiefly parietal and frontal cortical, as well as subcortical regions. Using a simulated lesion approach, we demonstrate that these core regions and their connections are particularly important to efficient network communication. Moreover, these regions are generally densely connected, but less so in 22q11DS. These specific disturbances are associated to a rerouting of shortest network paths that circumvent the A-core in 22q11DS, "de-centralizing" the network. Finally, the efficiency and mean connectivity strength of an orbito-frontal/cingulate circuit, included in the affected regions, correlate negatively with the extent of negative symptoms in 22q11DS patients, revealing the clinical relevance of present findings. The identified A-core overlaps numerous regions previously identified as affected in 22q11DS as well as in schizophrenia, which approximately 30-40% of 22q11DS patients develop.

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NlmCategory="UNASSIGNED">Objects' borders are readily perceived despite absent contrast gradients, e.g. due to poor lighting or occlusion. In humans, a visual evoked potential (VEP) correlate of illusory contour (IC) sensitivity, the "IC effect", has been identified with an onset at ~90ms and generators within bilateral lateral occipital cortices (LOC). The IC effect is observed across a wide range of stimulus parameters, though until now it always involved high-contrast achromatic stimuli. Whether IC perception and its brain mechanisms differ as a function of the type of stimulus cue remains unknown. Resolving such will provide insights on whether there is a unique or multiple solutions to how the brain binds together spatially fractionated information into a cohesive perception. Here, participants discriminated IC from no-contour (NC) control stimuli that were either comprised of low-contrast achromatic stimuli or instead isoluminant chromatic contrast stimuli (presumably biasing processing to the magnocellular and parvocellular pathways, respectively) on separate blocks of trials. Behavioural analyses revealed that ICs were readily perceived independently of the stimulus cue-i.e. when defined by either chromatic or luminance contrast. VEPs were analysed within an electrical neuroimaging framework and revealed a generally similar timing of IC effects across both stimulus contrasts (i.e. at ~90ms). Additionally, an overall phase shift of the VEP on the order of ~30ms was consistently observed in response to chromatic vs. luminance contrast independently of the presence/absence of ICs. Critically, topographic differences in the IC effect were observed over the ~110-160ms period; different configurations of intracranial sources contributed to IC sensitivity as a function of stimulus contrast. Distributed source estimations localized these differences to LOC as well as V1/V2. The present data expand current models by demonstrating the existence of multiple, cue-dependent circuits in the brain for generating perceptions of illusory contours.

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Focal epilepsy is increasingly recognized as the result of an altered brain network, both on the structural and functional levels and the characterization of these widespread brain alterations is crucial for our understanding of the clinical manifestation of seizure and cognitive deficits as well as for the management of candidates to epilepsy surgery. Tractography based on Diffusion Tensor Imaging allows non-invasive mapping of white matter tracts in vivo. Recently, diffusion spectrum imaging (DSI), based on an increased number of diffusion directions and intensities, has improved the sensitivity of tractography, notably with respect to the problem of fiber crossing and recent developments allow acquisition times compatible with clinical application. We used DSI and parcellation of the gray matter in regions of interest to build whole-brain connectivity matrices describing the mutual connections between cortical and subcortical regions in patients with focal epilepsy and healthy controls. In addition, the high angular and radial resolution of DSI allowed us to evaluate also some of the biophysical compartment models, to better understand the cause of the changes in diffusion anisotropy. Global connectivity, hub architecture and regional connectivity patterns were altered in TLE patients and showed different characteristics in RTLE vs LTLE with stronger abnormalities in RTLE. The microstructural analysis suggested that disturbed axonal density contributed more than fiber orientation to the connectivity changes affecting the temporal lobes whereas fiber orientation changes were more involved in extratemporal lobe changes. Our study provides further structural evidence that RTLE and LTLE are not symmetrical entities and DSI-based imaging could help investigate the microstructural correlate of these imaging abnormalities.

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Inactivating mutations of TP53, a tumor suppressor gene, are associated with abnormal cell proliferation. Although p53 expression is common in many human malignancies, p53 protein has seldom been evaluated in pituitary tumors. When detected, the percentage of p53-positive cells is low, and, in general, it is exclusive for invasive lesions. The aim of the present study was to use immunohistochemistry to determine the presence of p53 protein in pituitary adenomas from tumor samples of 163 surgeries performed in 148 patients (40% male, 60% female). In 35% of the cases the adenoma was nonfunctional, while in the others it was associated with PRL, GH and/or ACTH endocrine hypersecretion syndrome. Macroadenomas were observed in 83.2% of the cases with available neuroimage evaluation, of which 28% invaded the cavernous, sphenoid and/or ethmoidal sinus, bone, third ventricle or subfrontal lobe. p53 protein was detected in 2/148 patients (1.3%). Immunohistochemistry was positive for PRL and GH in these cases. Due to the high percentage of invasive pituitary adenomas found in our study, the low frequency of p53 detection suggests that it is inadequate as a routine marker for aggressiveness and as a predictive factor of tumor behavior.

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El neurofeedback es una técnica no invasiva en la que se pretende corregir, mediante condicionamiento operante, ondas cerebrales que se encuentren alteradas en el electroencefalograma. Desde 1967, se han conducido numerosas investigaciones relacionadas con los efectos de la técnica en el tratamiento de alteraciones psicológicas. Sin embargo, a la fecha no existen revisiones sistemáticas que reúnan los temas que serán aquí tratados. El aporte de este trabajo es la revisión de 56 artículos, publicados entre los años 1995 y 2013 y la evaluación metodológica de 29 estudios incluidos en la revisión. La búsqueda fue acotada a la efectividad del neurofeedback en el tratamiento de depresión, ansiedad, trastorno obsesivo compulsivo (TOC), ira y fibromialgia. Los hallazgos demuestran que el neurofeedback ha tenido resultados positivos en el tratamiento de estos trastornos, sin embargo, es una técnica que aún está en desarrollo, con unas bases teóricas no muy bien establecidas y cuyos resultados necesitan de diseños metodológicamente más sólidos que ratifiquen su validez.