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THE CORPUS CALLOSUM OF INDIVIDUALS WITH MICROCEPHALY AN MRI STUDY
Title
THE CORPUS CALLOSUM OF INDIVIDUALS WITH MICROCEPHALY AN MRI STUDY.
Creator
Fishbein, Alyson, Ellis, Meredith, Florida Atlantic University, Dorothy F. Schmidt College of Arts and Letters, Department of Anthropology
Abstract/Description
Microcephaly is neurological condition within which the brain fails to develop to a normal size resulting in the appearance of a smaller head. Microcephaly often accompanies various neurodevelopmental disorders. The corpus callosum is the largest white matter structure in the brain, comprised primarily of heavily myelinated axons. The corpus callosum connects the left and right hemisphere and allows for communication to occur between hemispheres. Using MRI measurements from a sample of 18...
Show moreMicrocephaly is neurological condition within which the brain fails to develop to a normal size resulting in the appearance of a smaller head. Microcephaly often accompanies various neurodevelopmental disorders. The corpus callosum is the largest white matter structure in the brain, comprised primarily of heavily myelinated axons. The corpus callosum connects the left and right hemisphere and allows for communication to occur between hemispheres. Using MRI measurements from a sample of 18 microcephalic patients, I analyzed whether the corpus callosum was impacted as a result of microcephaly. When compared to normocephalic controls, the corpus callosum was generally smaller in relation to overall cerebral hemispheric volume, suggesting that white matter brain tissues may be affected by microcephaly. A deeper understanding of the brain through research on the underlying mechanisms responsible for brain evolution and development is critical to our ability to detect, treat and prevent neurodevelopmental, neurodegenerative and psychiatric disorders.
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Date Issued
2019
PURL
http://purl.flvc.org/fau/fd/FA00013307
Subject Headings
Corpus callosum, Microcephaly, Magnetic resonance imaging
Format
Document (PDF)
White matter networks indicative of Alzheimer's disease from diffusion MRI
Title
White matter networks indicative of Alzheimer's disease from diffusion MRI.
Creator
Hahn, William E., Fuchs, Armin, Graduate College
Date Issued
2013-04-12
PURL
http://purl.flvc.org/fcla/dt/3361307
Subject Headings
Alzheimer's disease, Diffusion tensor imaging, Diffusion magnetic resonance imaging
Format
Document (PDF)
Diffusion tensor imaging in mild traumatic brain injuries
Title
Diffusion tensor imaging in mild traumatic brain injuries.
Creator
Hotiu, Angelica, Charles E. Schmidt College of Science, Department of Physics
Abstract/Description
Mild traumatic brain injuries (MTBI) are the leading type of head injuries with appreciable risque of sequelae leading to functional and psychological deficits. Although mild traumatic brain injuries are frequently underdiagnosed by conventional imaging modalities, rapidly evolving techniques such as diffusion tensor imaging (DTI) reveal subtle changes in white matter integrity as a result of head trauma and play an important role in refining diagnosis, therapeutic interventions and...
Show moreMild traumatic brain injuries (MTBI) are the leading type of head injuries with appreciable risque of sequelae leading to functional and psychological deficits. Although mild traumatic brain injuries are frequently underdiagnosed by conventional imaging modalities, rapidly evolving techniques such as diffusion tensor imaging (DTI) reveal subtle changes in white matter integrity as a result of head trauma and play an important role in refining diagnosis, therapeutic interventions and management of MTBI. In this dissertation we use diffusion tensor imaging to detect the microstructural changes induced by axonal injuries and to monitor their evolution during the recovery process. DTI data were previously acquired from 11 subjects, football players of age 19-23 years (median age 20 years). Three players had suffered a mild traumatic brain injury during the season and underwent scanning within 24 hours after the injury with follow-ups after one and two weeks. A set of diffusion indices, such as fractional anisotropy, axial, radial and mean diffusivity were derived from the diffusion tensor. Changes in diffusion indices in concussed subjects were analyzed based on two different approaches: whole brain analysis, using tract-based spatial statistics (TBSS) and region of interest analysis (ROI). In both approaches we use a voxelwise analysis to examine group differences in diffusion indices between five controls and three concussed subjects for all DTI scans. Additional statistical analysis was performed between control groups consisting of five and three non-injured players. Both analyses demonstrated that the MTBI group reveals increase in fractional anisotropy and decreases in transversal and mean diffusivity in cortical and subcortical areas within 24 hours after the injury., No changes were detected in TBSS analysis for the follow-up data sets. Furthermore, our ROI approach revealed multiples regions with significantly different voxels, non-uniformly distributed throughout the brain, for all diffusion indices in all three scans. Three of the diffusion indices fractional anisotropy, mean and transversal diffusivity showed higher vulnerability to head trauma in subcortical and cortical areas than in regions in the lower brain. Recovery of white matter pathways occured at different locations in the brain at one and two weeks after head trauma. Strong recovery was observed in mean and transversal diffusivity in subcortical areas that correspond to the corticospinal tract. No recovery was found for fractional anisotropy and axial diffusivity in the same region. Also, decreases in fractional anisotropy and increases in transversal and axial diffusivity were observed in the spleninum of the corpus callosum. As voxelwise analysis performed on DTI data revealed white matter regions, which exhibit changes in diffusion parameters in the concussed group for all three scans, we conclude that diffusion tensor imaging is a powerful technique for early detection of axonal injuries and may serve as an important tool for monitoring microstructural changes during the recovery process.
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Date Issued
2010
PURL
http://purl.flvc.org/FAU/2100579
Subject Headings
Brain, Magnetic resonance imaging, Brain, Concussion, Diagnosis, Neuropsychology, Diffusion tensor imaging
Format
Document (PDF)
A COMPARISON OF TASK RELEVANT NODE IDENTIFICATION TECHNIQUES AND THEIR IMPACT ON NETWORK INFERENCES: GROUP-AGGREGATED, SUBJECT-SPECIFIC, AND VOXEL WISE APPROACHES
Title
A COMPARISON OF TASK RELEVANT NODE IDENTIFICATION TECHNIQUES AND THEIR IMPACT ON NETWORK INFERENCES: GROUP-AGGREGATED, SUBJECT-SPECIFIC, AND VOXEL WISE APPROACHES.
Creator
Falco, Dimitri, Bressler, Steven L., Florida Atlantic University, Center for Complex Systems and Brain Sciences, Charles E. Schmidt College of Science
Abstract/Description
The dissertation discusses various node identification techniques as well as their downstream effects on network characteristics using task-activated fMRI data from two working memory paradigms: a verbal n-back task and a visual n-back task. The three node identification techniques examined within this work include: a group-aggregated approach, a subject-specific approach, and a voxel wise approach. The first chapters highlight crucial differences between group-aggregated and subject-specific...
Show moreThe dissertation discusses various node identification techniques as well as their downstream effects on network characteristics using task-activated fMRI data from two working memory paradigms: a verbal n-back task and a visual n-back task. The three node identification techniques examined within this work include: a group-aggregated approach, a subject-specific approach, and a voxel wise approach. The first chapters highlight crucial differences between group-aggregated and subject-specific methods of isolating nodes prior to undirected functional connectivity analysis. Results show that the two techniques yield significantly different network interactions and local network characteristics, despite having their network nodes restricted to the same anatomical regions. Prior to the introduction of the third technique, a chapter is dedicated to explaining the differences between a priori approaches (like the previously introduced group-aggregated and subject-specific techniques) and no a priori approaches (like the voxel wise approach). The chapter also discusses two ways to aggregate signal for node representation within a network: using the signal from a single voxel or aggregating signal across a group of neighboring voxels. Subsequently, a chapter is dedicated to introducing a novel processing pipeline which uses a data driven voxel wise approach to identify network nodes. The novel pipeline defines nodes using spatial temporal features generated by a deep learning algorithm and is validated by an analysis showing that the isolated nodes are condition and subject specific. The dissertation concludes by summarizing the main takeaways from each of the three analyses as well as highlighting the advantages and disadvantages of each of the three node identification techniques.
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Date Issued
2020
PURL
http://purl.flvc.org/fau/fd/FA00013553
Subject Headings
Functional magnetic resonance imaging, Brain mapping, Working memory, Neural networks (Neurobiology), Neuroimaging--methods
Format
Document (PDF)
Investigation of human visual spatial attention with fMRI and Granger Causality analysis
Title
Investigation of human visual spatial attention with fMRI and Granger Causality analysis.
Creator
Tang, Wei, Charles E. Schmidt College of Science, Center for Complex Systems and Brain Sciences
Abstract/Description
Contemporary understanding of human visual spatial attention rests on the hypothesis of a top-down control sending from cortical regions carrying higher-level functions to sensory regions. Evidence has been gathered through functional Magnetic Resonance Imaging (fMRI) experiments. The Frontal Eye Field (FEF) and IntraParietal Sulcus (IPS) are candidates proposed to form the frontoparietal attention network for top-down control. In this work we examined the influence patterns between...
Show moreContemporary understanding of human visual spatial attention rests on the hypothesis of a top-down control sending from cortical regions carrying higher-level functions to sensory regions. Evidence has been gathered through functional Magnetic Resonance Imaging (fMRI) experiments. The Frontal Eye Field (FEF) and IntraParietal Sulcus (IPS) are candidates proposed to form the frontoparietal attention network for top-down control. In this work we examined the influence patterns between frontoparietal network and Visual Occipital Cortex (VOC) using a statistical measure, Granger Causality (GC), with fMRI data acquired from subjects participated in a covert attention task. We found a directional asymmetry in GC between FEF/IPS and VOC, and further identified retinotopically specific control patterns in top-down GC. This work may lead to deeper understanding of goal-directed attention, as well as the application of GC to analyzing higher-level cognitive functions in healthy functioning human brain.
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Date Issued
2011
PURL
http://purl.flvc.org/FAU/3334101
Subject Headings
Attention, Physiological aspects, Cognitive neuroscience, Brain, Magnetic resonance imaging, Sensorimotor integration, Movement sequences, Human information processing, Cognitive psychology, Visual perception, Testing
Format
Document (PDF)
effect of age on processing family, famous and novel faces: An fMRI study
Title
The effect of age on processing family, famous and novel faces: An fMRI study.
Creator
Jones, Lana Casey, Florida Atlantic University, Tuller, Betty, Charles E. Schmidt College of Science, Department of Psychology
Abstract/Description
Facial recognition memory is a specialized system in the human brain, with an effect of familiarity playing a role in the brain activations involved. Previous studies examining the familiar face processing system have used college-aged subjects. However, memory disorders, like those associated with Alzheimer's disease, typically affect adults over sixty. In an attempt to reveal possible differences between young and older adults', two different age groups were subjected to fMRI analysis while...
Show moreFacial recognition memory is a specialized system in the human brain, with an effect of familiarity playing a role in the brain activations involved. Previous studies examining the familiar face processing system have used college-aged subjects. However, memory disorders, like those associated with Alzheimer's disease, typically affect adults over sixty. In an attempt to reveal possible differences between young and older adults', two different age groups were subjected to fMRI analysis while viewing face images with varying familiarity (family, famous and novel). The result showed a significant difference in activations for various cortical areas including the precuneus, cingulate cortex, and fusiform gyrus. Among the differences, an overall trend of greater activation in the left hemisphere for younger subjects compared to the older group was revealed. The results have implications for the study of memory disorders afflicting older adults, like Alzheimer's disease.
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Date Issued
2006
PURL
http://purl.flvc.org/fcla/dt/13358
Subject Headings
Brain--Magnetic resonance imaging, Evoked potentials (Electrophysiology), Memory, Cognition--Age factors, Aging--Psychological aspects, Memory disorders in old age
Format
Document (PDF)