923 resultados para BRAIN IMAGING


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The neurotransmitter serotonin (5-HT) modulates many functions important for life, e.g., appetite and body temperature, and controls development of the neural system. Disturbed 5-HT function has been implicated in mood, anxiety and eating disorders. The serotonin transporter (SERT) controls the amount of effective 5-HT by removing it from the extracellular space. Radionuclide imaging methods single photon emission tomography (SPET) and positron emission tomography (PET) enable studies on the brain SERTs. This thesis concentrated on both methodological and clinical aspects of the brain SERT imaging using SPET. The first study compared the repeatability of automated and manual methods for definition of volumes of interest (VOIs) in SERT images. The second study investigated within-subject seasonal variation of SERT binding in healthy young adults in two brain regions, the midbrain and thalamus. The third study investigated the association of the midbrain and thalamic SERT binding with Bulimia Nervosa (BN) in female twins. The fourth study investigated the association of the midbrain and hypothalamic/thalamic SERT binding and body mass index (BMI) in monozygotic (MZ) twin pairs. Two radioligands for SERT imaging were used: [123I]ADAM (studies I-III) and [123I]nor-beta-CIT (study IV). Study subjects included young adult MZ and dizygotic (DZ) twins screened from the FinnTwin16 twin cohort (studies I-IV) and healthy young adult men recruited for study II. The first study validated the use of an automated brain template in the analyses of [123I]ADAM images and proved automated VOI definition more reproducible than manual VOI definition. The second study found no systematic within-subject variation in SERT binding between scans done in summer and winter in either of the investigated brain regions. The third study found similar SERT binding between BN women (including purging and non-purging probands), their unaffected female co-twins and other healthy women in both brain regions; in post hoc analyses, a subgroup of purging BN women had significantly higher SERT binding in the midbrain as compared to all healthy women. In the fourth study, MZ twin pairs were divided into twins with higher BMI and co-twins with lower BMI; twins with higher BMI were found to have higher SERT binding in the hypothalamus/thalamus than their leaner co-twins. Our results allow the following conclusions: 1) No systematic seasonal variation exists in the midbrain and thalamus between SERT binding in summer and winter. 2) In a population-based sample, BN does not associate with altered SERT status, but alterations are possible in purging BN women. 3) The higher SERT binding in MZ twins with higher BMIs as compared to their leaner co-twins suggests non-genetic association between acquired obesity and the brain 5-HT system, which may have implications on feeding behavior and satiety.

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PURPOSE To study the utility of fractional calculus in modeling gradient-recalled echo MRI signal decay in the normal human brain. METHODS We solved analytically the extended time-fractional Bloch equations resulting in five model parameters, namely, the amplitude, relaxation rate, order of the time-fractional derivative, frequency shift, and constant offset. Voxel-level temporal fitting of the MRI signal was performed using the classical monoexponential model, a previously developed anomalous relaxation model, and using our extended time-fractional relaxation model. Nine brain regions segmented from multiple echo gradient-recalled echo 7 Tesla MRI data acquired from five participants were then used to investigate the characteristics of the extended time-fractional model parameters. RESULTS We found that the extended time-fractional model is able to fit the experimental data with smaller mean squared error than the classical monoexponential relaxation model and the anomalous relaxation model, which do not account for frequency shift. CONCLUSIONS We were able to fit multiple echo time MRI data with high accuracy using the developed model. Parameters of the model likely capture information on microstructural and susceptibility-induced changes in the human brain.

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Carotid atherosclerotic disease is a major cause of stroke, but it may remain clinically asymptomatic. The factors that turn the asymptomatic plaque into a symptomatic one are not fully understood, neither are the subtle effects that a high-grade carotid stenosis may have on the brain. The purpose of this study was to evaluate brain microcirculation, diffusion, and cognitive performance in patients with a high-grade stenosis in carotid artery, clinically either symptomatic or asymptomatic, undergoing carotid endarterectomy (CEA). We wanted to find out whether the stenoses are associated with diffusion or perfusion abnormalities of the brain or variation in the cognitive functioning of the patients, and to what extent the potential findings are affected by CEA, and compare the clinically symptomatic and asymptomatic subjects as well as strictly healthy controls. Coagulation and fibrinolytic parameters were compared with the rate microembolic signals (MES) in transcranial Doppler (TCD) and the macroscopic appearance of stenosing plaques in surgery. Patients (n=92) underwent CEA within the study. Blood samples pertaining to coagulation and fibrinolysis were collected before CEA, and the subjects underwent repeated TCD monitoring for MES. A subpopulation (n= 46) underwent MR imaging and repeated neuropsychological examination (preoperative, as well 4 and 100 days after CEA). In MRI, the average apparent diffusion coefficients were higher in the ipsilateral white matter (WM), and altough the interhemispheric difference was abolished by CEA, the levels remained higher than in controls. Symptomatic stenoses were associated with more sluggish perfusion especially in WM, and lower pulsatility of flow in TCD. All patients had poorer cognitive performance than healthy controls. Cognitive functions improved as expected by learning effect despite transient postoperative worsening in a few subjects. Improvement was greater in patients with deepest hypoperfusion, primarily in executive functions. Symptomatic stenoses were associated with higher hematocrit and tissue plasminogen activator antigen levels, as well as higher rate of MES and ulcerated plaques, and better postoperative improvement of vasoreactivity and pulsatility. In light of the findings, carotid stenosis is associated with differences in brain diffusion, perfusion, and cognition. The effect on diffusion in the ipsilateral WM, partially reversible by CEA, may be associated with WM degeneration. Asymptomatic and symptomatic subpopulations differ from each other in terms of hemodynamic adaptation and in their vascular physiological response to removal of stenosis. Although CEA may be associated with a transient cognitive decline, a true improvement of cognitive performance by CEA is possible in patients with the most pronounced perfusion deficits. Mediators of fibrinolysis and unfavourable hemorheology may contribute to the development of a symptomatic disease in patients with a high-grade stenosis.

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Anatomical brain networks change throughout life and with diseases. Genetic analysis of these networks may help identify processes giving rise to heritable brain disorders, but we do not yet know which network measures are promising for genetic analyses. Many factors affect the downstream results, such as the tractography algorithm used to define structural connectivity. We tested nine different tractography algorithms and four normalization methods to compute brain networks for 853 young healthy adults (twins and their siblings). We fitted genetic structural equation models to all nine network measures, after a normalization step to increase network consistency across tractography algorithms. Probabilistic tractography algorithms with global optimization (such as Probtrackx and Hough) yielded higher heritability statistics than 'greedy' algorithms (such as FACT) which process small neighborhoods at each step. Some global network measures (probtrackx-derived GLOB and ST) showed significant genetic effects, making them attractive targets for genome-wide association studies.

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Genetic and environmental factors affect white matter connectivity in the normal brain, and they also influence diseases in which brain connectivity is altered. Little is known about genetic influences on brain connectivity, despite wide variations in the brain's neural pathways. Here we applied the 'DICCCOL' framework to analyze structural connectivity, in 261 twin pairs (522 participants, mean age: 21.8 y ± 2.7SD). We encoded connectivity patterns by projecting the white matter (WM) bundles of all 'DICCCOLs' as a tracemap (TM). Next we fitted an A/C/E structural equation model to estimate additive genetic (A), common environmental (C), and unique environmental/error (E) components of the observed variations in brain connectivity. We found 44 'heritable DICCCOLs' whose connectivity was genetically influenced (α2>1%); half of them showed significant heritability (α2>20%). Our analysis of genetic influences on WM structural connectivity suggests high heritability for some WM projection patterns, yielding new targets for genome-wide association studies.

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Cardiovascular diseases (CVD) are, in developed countries, the leading cause of mortality. The majority of premature deaths and disability caused by CVD are due to atherosclerosis, a degenerating inflammatory disease affecting arterial walls. Early identification of lesions and initiation of treatment is crucial because the first manifestations quite often are major disabling cardiovascular events. Methods of finding individuals at high risk for these events are under development. Because magnetic resonance imaging (MRI) is an excellent non-invasive tool to study the structure and function of vascular system, we sought to discover whether existing MRI methods are able to show any difference in aortic and intracranial atherosclerotic lesions between patients at high risk for atherosclerosis and healthy controls. Our younger group (age 6-48) comprised 39 symptomless familial hypercholesterolemia (FH) patients and 25 healthy controls. Our older group (age 48-64) comprised 19 FH patients and 18 type 2 diabetes mellitus (DM) patients with coronary heart disease (CHD) and 29 healthy controls. Intracranial and aortic MRI was compared with carotid and femoral ultrasound (US). In neither age-group did MRI reveal any difference in the number of ischemic brain lesions or white matter hyperintensities (WMHIs) - possible signs of intracranial atherosclerosis - between patients and controls. Furthermore, MRI showed no difference in the structure or function of the aorta between FH patients and controls in either group. DM patients had lower compliance of the aorta than did controls, while no difference appeared between DM and FH patients. However, ultrasound showed greater plaque burden and increased thickness of carotid arterial walls in FH and DM patients in both age-groups, suggesting a more advanced atherosclerosis. The mortality of FH patients has decreased substantially after the late 1980´s when statin treatment became available. With statins, the progression of atherosclerotic lesions slows. We think that this, in concert with improvements in treatment of other risk factors, is one reason for the lack of differences between FH patients and controls in MRI measurements of the aorta and brain despite the more advanced disease of the carotid arteries assessed with US. Furthermore, whereas atherosclerotic lesions between different vascular territories correlate, differences might still exist in the extent and location of these lesions among different diseases. Small (<5 mm in diameter) WMHIs are more likely a phenomenon related to aging, but the larger ones may be the ones related to CVD and may be intermediate surrogates of stroke. The image quality in aortic imaging, although constantly improving, is not yet optimal and thus is a source of bias.

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Listening to music involves a widely distributed bilateral network of brain regions that controls many auditory perceptual, cognitive, emotional, and motor functions. Exposure to music can also temporarily improve mood, reduce stress, and enhance cognitive performance as well as promote neural plasticity. However, very little is currently known about the relationship between music perception and auditory and cognitive processes or about the potential therapeutic effects of listening to music after neural damage. This thesis explores the interplay of auditory, cognitive, and emotional factors related to music processing after a middle cerebral artery (MCA) stroke. In the acute recovery phase, 60 MCA stroke patients were randomly assigned to a music listening group, an audio book listening group, or a control group. All patients underwent neuropsychological assessments, magnetoencephalography (MEG) measurements, and magnetic resonance imaging (MRI) scans repeatedly during a six-month post-stroke period. The results revealed that amusia, a deficit of music perception, is a common and persistent deficit after a stroke, especially if the stroke affects the frontal and temporal brain areas in the right hemisphere. Amusia is clearly associated with deficits in both auditory encoding, as indicated by the magnetic mismatch negativity (MMNm) response, and domain-general cognitive processes, such as attention, working memory, and executive functions. Furthermore, both music and audio book listening increased the MMNm, whereas only music listening improved the recovery of verbal memory and focused attention as well as prevented a depressed and confused mood during the first post-stroke months. These findings indicate a close link between musical, auditory, and cognitive processes in the brain. Importantly, they also encourage the use of listening to music as a rehabilitative leisure activity after a stroke and suggest that the auditory environment can induce long-term plastic changes in the recovering brain.

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The diffusion equation-based modeling of near infrared light propagation in tissue is achieved by using finite-element mesh for imaging real-tissue types, such as breast and brain. The finite-element mesh size (number of nodes) dictates the parameter space in the optical tomographic imaging. Most commonly used finite-element meshing algorithms do not provide the flexibility of distinct nodal spacing in different regions of imaging domain to take the sensitivity of the problem into consideration. This study aims to present a computationally efficient mesh simplification method that can be used as a preprocessing step to iterative image reconstruction, where the finite-element mesh is simplified by using an edge collapsing algorithm to reduce the parameter space at regions where the sensitivity of the problem is relatively low. It is shown, using simulations and experimental phantom data for simple meshes/domains, that a significant reduction in parameter space could be achieved without compromising on the reconstructed image quality. The maximum errors observed by using the simplified meshes were less than 0.27% in the forward problem and 5% for inverse problem.

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It is increasingly being recognized that resting state brain connectivity derived from functional magnetic resonance imaging (fMRI) data is an important marker of brain function both in healthy and clinical populations. Though linear correlation has been extensively used to characterize brain connectivity, it is limited to detecting first order dependencies. In this study, we propose a framework where in phase synchronization (PS) between brain regions is characterized using a new metric ``correlation between probabilities of recurrence'' (CPR) and subsequent graph-theoretic analysis of the ensuing networks. We applied this method to resting state fMRI data obtained from human subjects with and without administration of propofol anesthetic. Our results showed decreased PS during anesthesia and a biologically more plausible community structure using CPR rather than linear correlation. We conclude that CPR provides an attractive nonparametric method for modeling interactions in brain networks as compared to standard correlation for obtaining physiologically meaningful insights about brain function.

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Overexpression of the mammalian homolog of the unc-18 gene (munc18-1) has been described in the brain of subjects with schizophrenia. Munc18-1 protein is involved in membrane fusion processes, exocytosis and neurotransmitter release. A transgenic mouse strain that overexpresses the protein isoform munc18-1a in the brain was characterized. This animal displays several schizophrenia-related behaviors, supersensitivity to hallucinogenic drugs and deficits in prepulse inhibition that reverse after antipsychotic treatment. Relevant brain areas (that is, cortex and striatum) exhibit reduced expression of dopamine D-1 receptors and dopamine transporters together with enhanced amphetamine-induced in vivo dopamine release. Magnetic resonance imaging demonstrates decreased gray matter volume in the transgenic animal. In conclusion, the mouse overexpressing brain munc18-1a represents a new valid animal model that resembles functional and structural abnormalities in patients with schizophrenia.

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Waking up from a dreamless sleep, I open my eyes, recognize my wife’s face and am filled with joy. In this thesis, I used functional Magnetic Resonance Imaging (fMRI) to gain insights into the mechanisms involved in this seemingly simple daily occurrence, which poses at least three great challenges to neuroscience: how does conscious experience arise from the activity of the brain? How does the brain process visual input to the point of recognizing individual faces? How does the brain store semantic knowledge about people that we know? To start tackling the first question, I studied the neural correlates of unconscious processing of invisible faces. I was unable to image significant activations related to the processing of completely invisible faces, despite existing reports in the literature. I thus moved on to the next question and studied how recognition of a familiar person was achieved in the brain; I focused on finding invariant representations of person identity – representations that would be activated any time we think of a familiar person, read their name, see their picture, hear them talk, etc. There again, I could not find significant evidence for such representations with fMRI, even in regions where they had previously been found with single unit recordings in human patients (the Jennifer Aniston neurons). Faced with these null outcomes, the scope of my investigations eventually turned back towards the technique that I had been using, fMRI, and the recently praised analytical tools that I had been trusting, Multivariate Pattern Analysis. After a mostly disappointing attempt at replicating a strong single unit finding of a categorical response to animals in the right human amygdala with fMRI, I put fMRI decoding to an ultimate test with a unique dataset acquired in the macaque monkey. There I showed a dissociation between the ability of fMRI to pick up face viewpoint information and its inability to pick up face identity information, which I mostly traced back to the poor clustering of identity selective units. Though fMRI decoding is a powerful new analytical tool, it does not rid fMRI of its inherent limitations as a hemodynamics-based measure.

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Microglia are largely known as the major orchestrators of the brain inflammatory response. As such, they have been traditionally studied in various contexts of disease, where their activation has been assumed to induce a wide range of detrimental effects. In the last few years, a series of discoveries have challenged the current view of microglia, showing their active and positive contribution to normal brain function. This Research Topic will review the novel physiological roles of microglia in the developing, mature and aging brain, under non-pathological conditions. In particular, this Research Topic will discuss the cellular and molecular mechanisms by which microglia contribute to the formation, pruning and plasticity of synapses; the maintenance of the blood brain barrier; the regulation of adult neurogenesis and hippocampal learning; and neuronal survival, among other important roles. Because these novel findings defy our understanding of microglial function in health as much as in disease, this Research Topic will also summarize the current view of microglial nomenclature, phenotypes, origin and differentiation, sex differences, and contribution to various brain pathologies. Additionally, novel imaging approaches and molecular tools to study microglia in their non-activated state will be discussed. In conclusion, this Research Topic seeks to emphasize how the current research in neuroscience is challenged by never-resting microglia.

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Elucidating the intricate relationship between brain structure and function, both in healthy and pathological conditions, is a key challenge for modern neuroscience. Recent progress in neuroimaging has helped advance our understanding of this important issue, with diffusion images providing information about structural connectivity (SC) and functional magnetic resonance imaging shedding light on resting state functional connectivity (rsFC). Here, we adopt a systems approach, relying on modular hierarchical clustering, to study together SC and rsFC datasets gathered independently from healthy human subjects. Our novel approach allows us to find a common skeleton shared by structure and function from which a new, optimal, brain partition can be extracted. We describe the emerging common structure-function modules (SFMs) in detail and compare them with commonly employed anatomical or functional parcellations. Our results underline the strong correspondence between brain structure and resting-state dynamics as well as the emerging coherent organization of the human brain.

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Over the last few decades, wine makers have been producing wines with a higher alcohol content, assuming that they are more appreciated by consumers. To test this hypothesis, we used functional magnetic imaging to compare reactions of human subjects to different types of wine, focusing on brain regions critical for flavor processing and food reward. Participants were presented with carefully matched pairs of high- and low- alcohol content red wines, without informing them of any of the wine attributes. Contrary to expectation, significantly greater activation was found for low- alcohol than for high- alcohol content wines in brain regions that are sensitive to taste intensity, including the insula as well as the cerebellum. Wines were closely matched for all physical attributes except for alcohol content, thus we interpret the preferential response to the low- alcohol content wines as arising from top-down modulation due to the low alcohol content wines inducing greater attentional exploration of aromas and flavours. The findings raise intriguing possibilities for objectively testing hypotheses regarding methods of producing a highly complex product such as wine.