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- Genre: Masters Thesis
Description
Functional magnetic resonance imaging (fMRI) has been widely used to measure the retinotopic organization of early visual cortex in the human brain. Previous studies have identified multiple visual field maps (VFMs) based on statistical analysis of fMRI signals, but the resulting geometry has not been fully characterized with mathematical models. This thesis explores using concepts from computational conformal geometry to create a custom software framework for examining and generating quantitative mathematical models for characterizing the geometry of early visual areas in the human brain. The software framework includes a graphical user interface built on top of a selected core conformal flattening algorithm and various software tools compiled specifically for processing and examining retinotopic data. Three conformal flattening algorithms were implemented and evaluated for speed and how well they preserve the conformal metric. All three algorithms performed well in preserving the conformal metric but the speed and stability of the algorithms varied. The software framework performed correctly on actual retinotopic data collected using the standard travelling-wave experiment. Preliminary analysis of the Beltrami coefficient for the early data set shows that selected regions of V1 that contain reasonably smooth eccentricity and polar angle gradients do show significant local conformality, warranting further investigation of this approach for analysis of early and higher visual cortex.
ContributorsTa, Duyan (Author) / Wang, Yalin (Thesis advisor) / Maciejewski, Ross (Committee member) / Wonka, Peter (Committee member) / Arizona State University (Publisher)
Created2013
Description
In blindness research, the corpus callosum (CC) is the most frequently studied sub-cortical structure, due to its important involvement in visual processing. While most callosal analyses from brain structural magnetic resonance images (MRI) are limited to the 2D mid-sagittal slice, we propose a novel framework to capture a complete set of 3D morphological differences in the corpus callosum between two groups of subjects. The CCs are segmented from whole brain T1-weighted MRI and modeled as 3D tetrahedral meshes. The callosal surface is divided into superior and inferior patches on which we compute a volumetric harmonic field by solving the Laplace's equation with Dirichlet boundary conditions. We adopt a refined tetrahedral mesh to compute the Laplacian operator, so our computation can achieve sub-voxel accuracy. Thickness is estimated by tracing the streamlines in the harmonic field. We combine areal changes found using surface tensor-based morphometry and thickness information into a vector at each vertex to be used as a metric for the statistical analysis. Group differences are assessed on this combined measure through Hotelling's T2 test. The method is applied to statistically compare three groups consisting of: congenitally blind (CB), late blind (LB; onset > 8 years old) and sighted (SC) subjects. Our results reveal significant differences in several regions of the CC between both blind groups and the sighted groups; and to a lesser extent between the LB and CB groups. These results demonstrate the crucial role of visual deprivation during the developmental period in reshaping the structural architecture of the CC.
ContributorsXu, Liang (Author) / Wang, Yalin (Thesis advisor) / Maciejewski, Ross (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2013
Description
ABSTRACT 1. Aposematic signals advertise prey distastefulness or metabolic unprofitability to potential predators and have evolved independently in many prey groups over the course of evolutionary history as a means of protection from predation. Most aposematic signals investigated to date exhibit highly chromatic patterning; however, relatives in these toxic groups with patterns of very low chroma have been largely overlooked. 2. We propose that bright displays with low chroma arose in toxic prey species because they were more effective at deterring predation than were their chromatic counterparts, especially when viewed in relatively low light environments such as forest understories. 3. We analyzed the reflectance and radiance of color patches on the wings of 90 tropical butterfly species that belong to groups with documented toxicity that vary in their habitat preferences to test this prediction: Warning signal chroma and perceived chromaticity are expected to be higher and brightness lower in species that fly in open environments when compared to those that fly in forested environments. 4. Analyses of the reflectance and radiance of warning color patches and predator visual modeling support this prediction. Moreover, phylogenetic tests, which correct for statistical non-independence due to phylogenetic relatedness of test species, also support the hypothesis of an evolutionary correlation between perceived chromaticity of aposematic signals and the flight habits of the butterflies that exhibit these signals.
ContributorsDouglas, Jonathan Marion (Author) / Rutowski, Ronald L (Thesis advisor) / Gadau, Juergen (Committee member) / McGraw, Kevin J. (Committee member) / Arizona State University (Publisher)
Created2013
Description
Over 2 billion people are using online social network services, such as Facebook, Twitter, Google+, LinkedIn, and Pinterest. Users update their status, post their photos, share their information, and chat with others in these social network sites every day; however, not everyone shares the same amount of information. This thesis explores methods of linking publicly available data sources as a means of extrapolating missing information of Facebook. An application named "Visual Friends Income Map" has been created on Facebook to collect social network data and explore geodemographic properties to link publicly available data, such as the US census data. Multiple predictors are implemented to link data sets and extrapolate missing information from Facebook with accurate predictions. The location based predictor matches Facebook users' locations with census data at the city level for income and demographic predictions. Age and relationship based predictors are created to improve the accuracy of the proposed location based predictor utilizing social network link information. In the case where a user does not share any location information on their Facebook profile, a kernel density estimation location predictor is created. This predictor utilizes publicly available telephone record information of all people with the same surname of this user in the US to create a likelihood distribution of the user's location. This is combined with the user's IP level information in order to narrow the probability estimation down to a local regional constraint.
ContributorsMao, Jingxian (Author) / Maciejewski, Ross (Thesis advisor) / Farin, Gerald (Committee member) / Wang, Yalin (Committee member) / Arizona State University (Publisher)
Created2012
Description
The purpose of this pilot randomized control trial was to test the initial efficacy of a 10 week social cognitive theory (SCT)-based intervention to reduce workplace sitting time (ST). Participants were currently employed adults with predominantly sedentary occupations (n=24) working in the Greater Phoenix area in 2012-2013. Participants wore an activPAL (AP) inclinometer to assess postural allocation (i.e., sitting vs. standing) and Actigraph accelerometer (AG) to assess sedentary time for one week prior to beginning and immediately following the completion of the 10 week intervention. Self-reported measures of sedentary time were obtained via two validated questionnaires for overall (International Physical Activity Questionnaire [IPAQ]) and domain specific sedentary behaviors (Sedentary Behavior Questionnaire [SBQ]). SCT constructs were also measured pre and post via adapted physical activity questionnaires. Participants were randomly assigned to receive either (a) 10 weekly social cognitive-based e-newsletters focused on reducing workplace ST; or (b) similarly formatted 10 weekly e-newsletters focusing on health education. Baseline adjusted Analysis of Covariance statistical analyses were used to examine differences between groups in time spent sitting (AP) and sedentary (AG) during self-reported work hours from pre- to post- intervention. Both groups decreased ST and AG sedentary time; however, no significant differences were observed. SCT constructs also did not change significantly between pretest and post test in either group. These results indicate that individualized educational approaches to decreasing workplace sitting time may not be sufficient for observing long term change in behaviors. Future research should utilize a larger sample, measure main outcomes more frequently, and incorporate more environmental factors throughout the intervention.
ContributorsGordon, Amanda (Author) / Buman, Matthew (Thesis advisor) / Der Ananian, Cheryl (Committee member) / Swan, Pamela (Committee member) / Arizona State University (Publisher)
Created2013
Description
INTRODUCTION: Exercise performed at moderate to vigorous intensities has been shown to generate a post exercise hypotensive response. Whether this response is observed with very low exercise intensities is unclear. PURPOSE: To compare post physical activity ambulatory blood pressure (ABP) response to a single worksite walking day and a normal sedentary work day in pre-hypertensive adults. METHODS: Participants were 7 pre-hypertensive (127 + 8 mmHg / 83 + 8 mmHg) adults (3 male, 4 female, age = 42 + 12 yr) who participated in a randomized, cross-over study that included a control and a walking treatment. Only those who indicated regularly sitting at least 8 hours/day and no structured physical activity were enrolled. Treatment days were randomly assigned and were performed one week apart. Walking treatment consisted of periodically increasing walk time up to 2.5 hours over the course of an 8 hour work day on a walking workstation (Steelcase Company, Grand Rapids, MI). Walk speed was set at 1 mph. Participants wore an ambulatory blood pressure cuff (Oscar 2, SunTech Medical, Morrisville, NC) for 24-hours on both treatment days. Participants maintained normal daily activities on the control day. ABP data collected from 9:00 am until 10:00 pm of the same day were included in statistical analyses. Linear mixed models were used to detect differences in systolic (SBP) and diastolic blood pressure (DBP) by treatment condition over the whole day and post workday for the time periods between 4 -10 pm when participants were no longer at work. RESULTS:BP was significantly lower in response to the walking treatment compared to the control day (Mean SBP 126 +7 mmHg vs.124 +7 mmHg, p=.043; DBP 80 + 3 mmHg vs. 77 + 3 mmHg, p = 0.001 respectively). Post workday (4:00 to 10:00 pm) SBP decreased 3 mmHg (p=.017) and DBP decreased 4 mmHg (p<.001) following walking. CONCLUSION: Even low intensity exercise such as walking on a walking workstation is effective for significantly reducing acute BP when compared to a normal work day.
ContributorsZeigler, Zachary (Author) / Swan, Pamela (Thesis advisor) / Buman, Matthew (Committee member) / Gaesser, Glenn (Committee member) / Arizona State University (Publisher)
Created2013
Description
Vertebrate genomes demonstrate a remarkable range of sizes from 0.3 to 133 gigabase pairs. The proliferation of repeat elements are a major genomic expansion. In particular, long interspersed nuclear elements (LINES) are autonomous retrotransposons that have the ability to "cut and paste" themselves into a host genome through a mechanism called target-primed reverse transcription. LINES have been called "junk DNA," "viral DNA," and "selfish" DNA, and were once thought to be parasitic elements. However, LINES, which diversified before the emergence of many early vertebrates, has strongly shaped the evolution of eukaryotic genomes. This thesis will evaluate LINE abundance, diversity and activity in four anole lizards. An intrageneric analysis will be conducted using comparative phylogenetics and bioinformatics. Comparisons within the Anolis genus, which derives from a single lineage of an adaptive radiation, will be conducted to explore the relationship between LINE retrotransposon activity and causal changes in genomic size and composition.
ContributorsMay, Catherine (Author) / Kusumi, Kenro (Thesis advisor) / Gadau, Juergen (Committee member) / Rawls, Jeffery A (Committee member) / Arizona State University (Publisher)
Created2013
Description
This document presents a new implementation of the Smoothed Particles Hydrodynamics algorithm using DirectX 11 and DirectCompute. The main goal of this document is to present to the reader an alternative solution to the largely studied and researched problem of fluid simulation. Most other solutions have been implemented using the NVIDIA CUDA framework; however, the proposed solution in this document uses the Microsoft general-purpose computing on graphics processing units API. The implementation allows for the simulation of a large number of particles in a real-time scenario. The solution presented here uses the Smoothed Particles Hydrodynamics algorithm to calculate the forces within the fluid; this algorithm provides a Lagrangian approach for discretizes the Navier-Stockes equations into a set of particles. Our solution uses the DirectCompute compute shaders to evaluate each particle using the multithreading and multi-core capabilities of the GPU increasing the overall performance. The solution then describes a method for extracting the fluid surface using the Marching Cubes method and the programmable interfaces exposed by the DirectX pipeline. Particularly, this document presents a method for using the Geometry Shader Stage to generate the triangle mesh as defined by the Marching Cubes method. The implementation results show the ability to simulate over 64K particles at a rate of 900 and 400 frames per second, not including the surface reconstruction steps and including the Marching Cubes steps respectively.
ContributorsFigueroa, Gustavo (Author) / Farin, Gerald (Thesis advisor) / Maciejewski, Ross (Committee member) / Wang, Yalin (Committee member) / Arizona State University (Publisher)
Created2012
Description
Gene-centric theories of evolution by natural selection have been popularized and remain generally accepted in both scientific and public paradigms. While gene-centrism is certainly parsimonious, its explanations fall short of describing two patterns of evolutionary and social phenomena: the evolution of sex and the evolution of social altruism. I review and analyze current theories on the evolution of sex. I then introduce the conflict presented to gene-centric evolution by social phenomena such as altruism and caste sterility in eusocial insects. I review gene-centric models of inclusive fitness and kin selection proposed by Hamilton and Maynard Smith. Based their assumptions, that relatedness should be equal between sterile workers and reproductives, I present several empirical examples that conflict with their models. Following that, I introduce a unique system of genetic caste determination (GCD) observed in hybrid populations of two sister-species of seed harvester ants, Pogonomyrmex rugosus and Pogonomyrmex barbatus. I review the evidence for GCD in those species, followed by a critique of the current gene-centric models used to explain it. In chapter two I present my own theoretical model that is both simple and extricable in nature to explain the origin, evolution, and maintenance of GCD in Pogonomyrmex. Furthermore, I use that model to fill in the gaps left behind by the contributing authors of the other GCD models. As both populations in my study system formed from inter-specific hybridization, I review modern discussions of heterosis (also called hybrid vigor) and use those to help explain the ecological competitiveness of GCD. I empirically address the inbreeding depression the lineages of GCD must overcome in order to remain ecologically stable, demonstrating that as a result of their unique system of caste determination, GCD lineages have elevated recombination frequencies. I summarize and conclude with an argument for why GCD evolved under selective mechanisms which cannot be considered gene-centric, providing evidence that natural selection can effectively operate on non-heritable genotypes appearing in groups and other social contexts.
ContributorsJacobson, Neal (Author) / Gadau, Juergen (Thesis advisor) / Laubichler, Manfred (Committee member) / Pratt, Stephen (Committee member) / Arizona State University (Publisher)
Created2012
Description
Alzheimer's Disease (AD) is the most common form of dementia observed in elderly patients and has significant social-economic impact. There are many initiatives which aim to capture leading causes of AD. Several genetic, imaging, and biochemical markers are being explored to monitor progression of AD and explore treatment and detection options. The primary focus of this thesis is to identify key biomarkers to understand the pathogenesis and prognosis of Alzheimer's Disease. Feature selection is the process of finding a subset of relevant features to develop efficient and robust learning models. It is an active research topic in diverse areas such as computer vision, bioinformatics, information retrieval, chemical informatics, and computational finance. In this work, state of the art feature selection algorithms, such as Student's t-test, Relief-F, Information Gain, Gini Index, Chi-Square, Fisher Kernel Score, Kruskal-Wallis, Minimum Redundancy Maximum Relevance, and Sparse Logistic regression with Stability Selection have been extensively exploited to identify informative features for AD using data from Alzheimer's Disease Neuroimaging Initiative (ADNI). An integrative approach which uses blood plasma protein, Magnetic Resonance Imaging, and psychometric assessment scores biomarkers has been explored. This work also analyzes the techniques to handle unbalanced data and evaluate the efficacy of sampling techniques. Performance of feature selection algorithm is evaluated using the relevance of derived features and the predictive power of the algorithm using Random Forest and Support Vector Machine classifiers. Performance metrics such as Accuracy, Sensitivity and Specificity, and area under the Receiver Operating Characteristic curve (AUC) have been used for evaluation. The feature selection algorithms best suited to analyze AD proteomics data have been proposed. The key biomarkers distinguishing healthy and AD patients, Mild Cognitive Impairment (MCI) converters and non-converters, and healthy and MCI patients have been identified.
ContributorsDubey, Rashmi (Author) / Ye, Jieping (Thesis advisor) / Wang, Yalin (Committee member) / Wu, Tong (Committee member) / Arizona State University (Publisher)
Created2012