Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 534 for “"Neuroimaging"”.
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Data-driven analysis for multimodal neuroimaging
Bildgebende Verfahren in den Neurowissenschaften haben unser Verständnis von Informationsverarbeitung im Hirn entscheidend geprägt. Die schnelle Verbreitung von nicht-invasiven bildgebenden Verfahren wie etwa der funktionellen Magnet-Resonanz Tomographie (fMRT) in den letzten beiden Dekaden erlaubt …
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Advancing photoacoustic neuroimaging through deep learning
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-12-01
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Hierarchical Bayesian Models for Multimodal Neuroimaging Data
… Due to the complex spatial structure of neuroimaging data as well as the small number of samples typically collected in neuroimaging experiments, statistical methods which try to integrate different types of neuroimaging data are paramount. Our research is focused on the development of …
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Computation cloud to enable high throughput neuroimaging
Neuroimaging studies require significant computational power in order to perform non-linear registrations, 3D volumetric segmentations, and statistical analysis across a large group of subjects. In addition to the need for this large computational infrastructure, the large number of open-source …
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Biophysical modeling of hemodynamic-based neuroimaging techniques
Two different hemodynamic-based neuroimaging techniques were studied in this work. Near-Infrared Spectroscopy (NIRS) is a promising technique to measure cerebral hemodynamics in a clinical setting due to its potential for continuous monitoring. However, the presence of strong systemic interference …
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Developing High-Density Diffuse Optical Tomography for Neuroimaging
… to pioneer the in vivo use of DOT for advanced neuroimaging by: 1) quantifying the advantages of DOT through both <italic>in silico</italic> simulation and <italic>in vivo</italic> performance metrics,: 2) restoring confidence in the technique with the first retinotopic mapping of the visual …
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Overcoming Vulnerabilities of Machine Learning in Neuroimaging Applications
Neuroimaging has been widely used to non-invasively probe the structural and functional changes in many neurological and psychiatric diseases. Techniques such as functional magnetic resonance imaging (fMRI) generate a wealth of dense and high-dimensional measurements of the brain. Through machine …
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Bayesian Tensor Modeling of High-Dimensional Neuroimaging Data
Neuroimaging has played a pivotal role in advancing the understanding of neurological and psychiatric conditions by providing comprehensive insights into structural and functional brain changes. Techniques such as magnetic resonance imaging (MRI), positron emission tomography (PET), and diffusion …
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IDENTIFICATION OF NEUROMARKERS USING STRUCTURAL AND FUNCTIONAL NEUROIMAGING
… research, the spatially and temporally complex neuroimaging data were used to identify neuromarkers that aids in quantifying a brain’s health. In the first part, a comparison of static and dynamic functional connectivities was made to study their efficacies in identifying intrinsic individual …
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Functional neuroimaging studies of peripheral inflammation-related depression
… a literature review of current brain functional neuroimaging studies on inflammation-linked depression. I noted through this endeavor that the body of knowledge addressing fMRI abnormalities in inflammation-linked depression is presently limited, and it is further complicated by considerable …
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STATISTICAL METHODS FOR ANALYSIS OF HIGH-DIMENSIONAL NEUROIMAGING DATA
The increasing accessibility of neuroimaging data promises new insights into the human brain. However, the complexity of neuroimaging data poses significant challenges. This dissertation develops statistical tools to capture neuroimaging patterns and address these challenges. First, we propose an …
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Neuroimaging Investigation of Binge Alcohol Drinking and Opioid Dependency.
Substance use disorder and mental illness are the leading cause of years of life lived with disability worldwide; depressive and anxiety disorders account for about half of total disability-adjusted life years and alcohol and illicit drug (including opioid) use disorder account for about ten …
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Development of Machine Learning-Based Techniques in Psychiatric Neuroimaging
The primary goal of this thesis is to investigate whether machine learning-<br/>based methods can be successfully applied to make clinically relevant predictions. These techniques are applied to a range of data such as demographic, socioeconomic and neuropsychiatric variables but primarily to …
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Computational methods for analyzing wide-field calcium neuroimaging data
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-05-01
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Neurovascular mechanisms of cognitive aging: A multimodal neuroimaging investigation
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-03-01 without embargo terms
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Neuroimaging Depression Risk in a Sample of Never-Depressed Children
… risk. Of the few studies that have used neuroimaging techniques to characterize risk-based differences in children’s neural structure, function, and functional connectivity, most have used samples that include participants with a personal history of depression or older samples (i.e., past …
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Learning the meaning of new words: Behavioural and neuroimaging evidence
This thesis aimed to shed light on the process of word learning and the consequences of storing, retrieving, and using new lexical representations. A number of behavioural experiments and one final fMRI study were conducted. Experiments 1-2 investigated effects of context variability (number of …
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Clinical, cognitive, and neuroimaging correlates of risk for postpartum psychosis
… study assessing<br/>cognitive, emotional and neuroimaging correlates of women at risk of postpartum<br/>psychosis. We hypothesised that women “at risk” will show decreased brain<br/>activation in the dorsolateral prefrontal cortex in a working memory task and<br/>increased brain activation in …
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