This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students. 

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With no known cure, Alzheimer's disease (AD) is the most common dementia, affecting more than 5.5 million Americans. Research has shown that women who undergo surgical menopause (i.e. removal of the ovaries) before the onset of natural menopause are at a greater risk for AD. It is hypothesized that this

With no known cure, Alzheimer's disease (AD) is the most common dementia, affecting more than 5.5 million Americans. Research has shown that women who undergo surgical menopause (i.e. removal of the ovaries) before the onset of natural menopause are at a greater risk for AD. It is hypothesized that this greater relative risk of developing AD is linked to ovarian hormone deprivation associated with surgical menopause. The purpose of these studies was to evaluate the behavioral changes that occur after a short-term (ST) and a long-term (LT) ovarian hormone deprivation in a mouse model of AD. Wildtype (Wt) or APP/PS1 (Tg) mutation mice underwent either a sham surgery or an ovariectomy (Ovx) surgery at three months of age. Study 1 consisted of a short-term cohort that was behaviorally tested one month following surgery on a battery of spatial memory tasks including, the Morris water maze, delayed matched-to-sample water maze, and visible platform task. Study 2 consisted of a long-term cohort that was behaviorally tested on the same cognitive battery three months following surgery. Results of Study 1 revealed that genotype interacted with surgical menopause status, such that after a short-term ovarian hormone deprivation, Ovx induced a genotype effect while Sham surgery did not. Results of Study 2 showed a similar pattern of effects, with a comparable interaction between genotypes and surgical menopause status. These findings indicate that the cognitive impact of ovarian hormone deprivation depends on AD-related genotype. Neuropathology evaluations in these mice will be done in the near future and will allow us to test relations between surgical menopause status, cognition, and AD-like neuropathology.
ContributorsPalmer, Justin M. (Author) / Bimonte-Nelson, Heather (Thesis director) / Oddo, Salvatore (Committee member) / Davis, Mary (Committee member) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
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Description
Hand-coding systems of measuring facial expressions were developed to study and analyze human emotions, but they are time-intensive and thus seldom used. As technology has advanced, new computer software programs, such as Affectiva, were developed to code facial expressions automatically using artificial intelligence and machine learning. Since this technology is

Hand-coding systems of measuring facial expressions were developed to study and analyze human emotions, but they are time-intensive and thus seldom used. As technology has advanced, new computer software programs, such as Affectiva, were developed to code facial expressions automatically using artificial intelligence and machine learning. Since this technology is still new, Affectiva and its validity remain understudied, and no psychological research has been conducted to compare Affectiva computer coding and hand coding of children’s emotions. The purpose of this study was to compare hand and computer coding of children’s expressions of emotion during a videotaped parent-child interaction. The study answered the following questions: 1) Do hand and computer coding agree?; and 2) Are hand and computer coding in higher agreement for some emotions than others? The sample included 25 pairs of twins from the Arizona Twin Project. Facial expressions were coded from videotape by a trained and reliable human coder and using the software Affectiva. The results showed that hand and computer coded emotion were in agreement for positive, but not negative emotions. Changing the context of the interaction to elicit more negative emotion, and using the same indicators of each emotion in computer and hand coding are suggested to improve the comparison of computer and hand coding.
ContributorsKwok, Connie (Author) / Lemery-Chalfant, Kathryn (Thesis director) / Davis, Mary (Committee member) / Miadich, Samantha (Committee member) / Department of Psychology (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05