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 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. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2020. / FAU Electronic Theses and Dissertations Collection

The microtuble-associated protein tau is known to regulate neuronal micro- tubule dynamics and is involved in several neurodegenerative diseases collec- tively called tauopathies. Besides the formation of tau-containing aggregates this group of diseases is characterized by changes on different anatomical lev- els in the nervous system. Morphological changes in the dendritic arbor of neu- rons or subcellular compartments can be investigated with microscopy-based and image informatical methods. Furthermore, the functional processes that constitute these changes can be predicted with bioinformatical methods and based on these predictions investigated with biological experiments. Two different bioinformatical disciplines contribute to the study of neurobio- logical processes. Due to advances in microscopy and imaging coupled to the tremendous advances in computer technology, image informatics techniques and workflows are necessary to analyze the acquired data with greater pre- cision. The classical bioinformatics on the other hand covers the analysis of molecular evolution, phylogeny and the prediction of protein function. This work aims to assist neurobiologists with computational methods in ongo- ing reasearch questions. The development of computer-assisted or fully auto- mated workflows for image analysis has been achieved on different levels. A machine learning algorithm has been trained to determine the density of neu- rons in tissues. Workflows for analysis of morphological changes of dendritic arbors, like process thickness or branching pattern, have been implemented. Existing workflows for dendritic spine analysis have been optimized and the volume and movement behavior of subcellular compartments like ribonucle- oparticles have been analyzed. Image analysis workflows have been adapted for the analysis of molecular distributions after photoactivation. Additionally, techniques from data mining workflows have been adapted to extract and filter trajectories from single molecule tracking approaches to assist the inferrence of biophysical parameters. Sequence data from public available databases have been collected to recon- struct tau and other related sequences in a broad range of species to infer phy- logenetic trees and to perform hidden-Markov-model analysis. Using this ap- proach it has been possible to illuminate the relations in the MAPT/2/4 family and predict putative functional sequence motifs for further bioinformatical or biological investigations.

Thesis submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Community Psychology at the University of Zululand, South Africa, 2012. / The aim of this study was to explore factors which could influence the development of mass hysteria in the high schools within the UThukela District in Kwa Zulu Natal. Being exploratory in nature, the study generated or relied on hypotheses on the possible etiological factors that could lead to the development of mass hysteria. Quantitative research, in the form of subjective psychological well – being questionnaires (AFM, SWL & Fortitude scales) were used to collect data in order to determine whether or not mass hysteria was related or influenced by them. A total number of seven hundred and nineteen (719) participants – all high school teenagers of all races - answered questionnaires in the English language. Their age range was between 16 and 19 years. The smaller qualitative research section consisted of ten (10) randomly selected teenagers from the school community. The emphasis on qualitative research was placed on asking participants about their own experiences and/or meaning of mass hysteria and actions they took to heal or recover. The main findings were that there are statistically significant differences in the way different religious groups; gender and race contribute to the incidence of mass hysteria. The results of the subjective scales demonstrated a high level of psychological well – being of a large number of participants. In the literature review it was apparent that mass hysteria is a universal phenomenon, probably arising psycho dynamically from the mind/body interface without organic etiological factors. It is a symbolic relation between the pathological phenomenon and the precipitating psychical childhood traumas. Observations from mass hysteria victims are in keeping with various theories (for discussion), therefore the confirmatory hypotheses testing is not to be seen as an efficient means of unearthing a web of belief system in various communities. There are potential relationships among various theoretical dimensions of mass hysteria. Symptoms presented by victims of (mass) hysteria are almost similar, but are expressed differently by race, gender and religion. This research has tried to give some tentative answers to the question of mass hysteria. / University of Zululand

Understanding the operating principles of the brain functions is the key to building novel computing architectures for mimicking human intelligence. Neural activities at different scales lead to different levels of brain functions. For example, cellular functions, such as sensory transduction, occur in the molecular reactions, and cognitive functions, such as recognition, emerge in neural systems across multiple brain regions. To bridge the gap between neuroscience and artificial computation, we need systematic development of mechanistic models for neural computation across multiple scales. Existing models of neural computation are often independently developed for a specific scale and hence not compatible with others. In this thesis, we investigate the neural computations in the fruit fly brain and devise mechanistic models at different scales in a systematic manner so that models at one scale constitute functional building blocks for the next scale. Our study spans from the molecular and circuit computations in the olfactory system to the system-level computation of the central complex in the fruit fly. First, we study how the two key aspects of odorant, identity and concentration, are encoded by the odorant transduction process at the molecular scale. We mathematically quantify the odorant space and propose a biophysical model of the olfactory sensory neuron (OSN). To validate our modeling approaches, we examine the OSN model with a multitude of odorant waveforms and demonstrate that the model output reproduces the temporal responses of OSNs obtained from in vivo electrophysiology recordings. In addition, we evaluate the model at the OSN population level and quantify the combinatorial complexity of the transformation taking place between the odorant space and the OSNs. The resulting concentration-dependent combinatorial code determines the complexity of the input space driving olfactory processing in the downstream neuropil, the antennal lobe. Second, we investigate the neural information processing in the antennal lobe across the molecule scale and the circuit scale. The antennal lobe encodes the output of the OSN population from a concentration-dependent code into a concentration-independent combinatorial code. To study the transformation of the combinatorial code, we construct a computational model of the antennal lobe that consists of two sub circuits, a predictive coding circuit and an on-off circuit, realized by two distinct local neuron networks, respectively. By examining the entire circuit model with both monomolecular odorant and odorant mixtures, we demonstrate that the predictive coding circuit encodes the odorant identity into concentration invariant code and the on-off circuit encodes the onset and the offset of a unique odorant identity. Third, we investigate the odorant representation inherent in the Kenyon cell activities in the mushroom body. The Kenyon cells encodes the output of the antennal lobe into a high-dimensional, sparse neural code that is immediately used for learning and memory formation. We model the Kenyon cell circuitry as a real-time feedback normalization circuit converting odorant information into a time-dependent hash codes. The resultant real-time hash code represents odorants, pure or mixture alike, in a way conducive to classifications, and suggests an intrinsic partition of the odorant space with similar hash codes. Forth, we study at the system scale the neural coding of the central complex. The central complex is a set of neuropils in the center of the fly brain that integrates multiple sensory information and play an important role in locomotor control. We create an application that enables simultaneous graphical querying and construction of executable model of the central complex neural circuitry. By reconfiguring the circuitry and generating different executable models, we compare the model response of the wild type and mutant fly strains. Finally, we show that the multi-scale study of the fruit fly brain is made possible by the Fruit Fly Brain Observatory (FFBO), an open-source platform to support open, collaborative fruit fly neuroscience research. The software architecture of the FFBO and its key application are highlighted along with several examples.

Walden University College of Social and Behavioral Sciences This is to certify that the doctoral dissertation by Octavious Bishop has been found to be complete and satisfactory in all respects, and that any and all revisions required by the review committee have been made. Review Committee Dr. Thomas Edman, Committee Chairperson, Psychology Faculty Dr. Ricardo Thomas, Committee Member, Psychology Faculty Dr. Joanna Bissell-Havran, University Reviewer, Psychology Faculty Chief Academic Officer Eric Riedel, Ph.D. Quantifying the Spectrum of Depression by Octavious Bishop MA, University of Texas at Austin, 2008 BS, University of Texas at Austin, 2001 Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy Psychology Walden University May 2018 Depression is a medically serious and widespread mood disorder that is difficult to diagnose in an objective manner. Dopamine irregularities have been strongly implicated in depression studies, and drug therapy based on dopamine is in wide use. However, the same neurological abnormalities associated with depression also affect other neural systems, including the vestibular system, in which involuntary muscle movements involved with the contralateral acoustic reflex are located. Using nigrostriatal pathways that transmit dopamine as a framework, this study investigated the biological and physiological links between depression and acoustic reflexes, and their potential usefulness for objectively assessing depression. Records of 52 randomly-selected patients who presented symptoms of depression were assessed to determine the relationship between depression and the contralateral acoustic reflex. The patients were both male and female, ranging in age from 23 to 84. Acoustic reflex threshold testing was assessed through ranges of frequencies using a tympanogram. The resulting individual average scores for the right ear and the left ear were then statistically tested against the medically accepted normal score using one-sample t tests. Evidence indicated that acoustic reflex abnormality may be concomitant with depression. These findings offer promising possibilities to researchers looking to develop a functional quantifiable assessment of patients who present with symptoms of depression. Addressing the wide variance of symptoms in patients may help mental health professionals determine which antidepressants to prescribe or if a patient is ready for a therapeutic process.

Until recently, society and science often ignored, erased, and avoided bisexual women and men and individuals with biracial and multiracial identities, and rarely considered these identities simultaneously. Prior research has shown that some lesbians and gay people of color exhibit resilience against sexual minority stress due in part to an inoculating effect of exposure to racism earlier in life. However, little is known about the lived experience of thriving, resilient bisexual multiracial individuals. In the tradition of positive psychology and context of intersectionality theory, this qualitative study explored how multiracial bisexual individuals develop and maintain flourishing well-€being despite sociocultural factors promoting chronic stressors. In-€depth, semistructured interviews were conducted with 6 multiracial bisexual participants. Interpretive phenomenological analysis revealed 6 key themes for developing and maintaining resilience: integration of intersecting social identities, social support, emotional openness, hope and optimism, meaningful life, and life/personal accomplishments. Deeper knowledge about resilience-€building in holders of multiple-€marginal identities may influence informed stakeholders (bisexual, biracial and multiracial individuals and their families, service providers, researchers, public institutions, and decision makers) to advance development of more effective counseling programs and influence more responsive and affirmative social policies. Subsequent social change involves the advance of sexual health, rights, and behaviors of bisexual, biracial and multiracial citizens.

The prevalence of obesity, which is considered as a disease, has been increasing uncontrollably over the last two decades. Obesity is a state of disregulated energy homeostasis characterized by hypothalamic resistance to adiposity signals (insulin and leptin). While many factors are involved in the development of obesity, excess dietary fat has been proposed as one of the main causal factors. This causes disrupted energy homeostasis by inducing both leptin and insulin resistance in the central nervous system. Although brain tissue was considered to be insulin independent for a long time, insulin is now recognized to have important functions in the brain in the regulation of feeding behavior, energy expenditure and peripheral metabolism to maintain energy homeostasis. Recently, our lab discovered that insulin has an anorectic effect when it is applied into the central nucleus of the amygdala (CeA), a response that is similar to its effect when it is intracerebroventricularly (icv) administered into the hypothalamus. Our lab also demonstrated that rats fed a high fat diet lost the anorectic response to CeA insulin and became insulin resistant. These data suggested that insulin signaling in the amygdala had an important role in controlling food intake and energy expenditure in similar ways to the hypothalamus. It also suggests that a high fat diet inhibits amygdala insulin signaling in the CeA. Both in vitro cell culture and in vivo animal studies have been used to investigate the effects of dietary fats on insulin signaling in neuronal cells and in the amygdala. Using both hypothalamic GT1-7 cells and primary amygdala cells in culture, the saturated fatty acid palmitic acid was shown to inhibit insulin signaling (Akt phosphorylation). This response appears to be related to the activation of PKC-θ since the inhibitory effect of palmitic acid on Akt phosphorylation was greater in GT1-7 cells transfected with PKC-θ compared to wild type cells and was abolished in GT1-7 cells transfected with PKC-θ siRNA. Further investigations in vivo confirmed that insulin stimulated Akt and mTOR signaling in the CeA of rats and that the insulin stimulation of Akt phosphorylation, but not mTOR phosphorylation, was inhibited in rats fed a high fat diet for 3 days or by infusing palmitic acid into the CeA for 3 days. These experiments also identified that fatty acid and insulin signaling in the CeA differentially affected Akt and mTOR signaling in the hypothalamus and suggest that these neural connections might be important components of the neural pathways through which insulin in the amygdala affects food intake and peripheral metabolism. This research has provided novel insight into the effects of dietary fats on insulin signaling in an area of the brain, the CeA, that is now recognized to have effects on energy balance and peripheral metabolism.

Critical life history events such as breeding, migration and hibernation must take place in the correct environmental context to minimize deleterious consequences on survival and reproductive fitness. Neuroendocrine mechanisms synchronizing internal physiological states with extrinsic environmental cues are vital to timing life history events appropriately. Secretion of the pineal hormone melatonin is sensitive to light and temperature cues, which provides a physiological indicator of time of day and time of year for organisms. Melatonin influences seasonal reproduction in a variety of vertebrates, likely by altering the synthesis and/or release of reproductive neuropeptides in the brain. The neuropeptides arginine vasotocin and its mammalian homologue, arginine vasopressin, are well-known modulators of reproductive and sociosexual behavior across vertebrate taxa, and are likely targets of melatonin in the context of seasonal reproduction. There is extensive evidence that vasotocin/vasopressin innervation in the brain is subject to seasonal variation, and that this variation is frequently sexually dimorphic. However, evidence that melatonin directly modulates this important neuropeptide system is lacking. Melatonin receptor 1a (MT1 in mammals) may be responsible for mediating melatonin's influence on brain vasotocin, as it is known to regulate seasonal reproduction in a variety of vertebrates. In the present study, I asked whether melatonin influences brain vasotocin in male green treefrogs (Hyla cinerea), and compared the distribution of melatonin receptor 1a in the brain of green treefrogs between sexes and seasons. Adult male and female green treefrogs were collected from field sites in Louisiana during the summer breeding season. Summer animals were acclimated to lab conditions for 3 weeks, then euthanized and their brains collected. Winter animals were maintained in the lab for four months under incrementally changing photo-, thermo-, and hygroperiod regimes that mimicked the transition to winter in their natural habitat, followed by euthanasia and brain collection. A subset of winter males (Experiment 1) were implanted with melatonin-filled or blank silastic capsules for a period of one month prior to euthanasia and brain collection. Brains of these males were processed for vasotocin immunohistochemistry. I quantified AVT-ir cell number in Experiment 1 males in the nucleus accumbens (NAcc), amygdala and caudal striatum (AMG), preoptic area (POA), suprachaismatic nucleus (SCN), and ventral hypothalamus (VH). Melatonin did not influence brain vasotocin-ir cell number in any brain region. Brains from untreated summer and winter males and females were collected and processed for MT1 immunohistochemistry. MT1-ir cells were quantified in the NAcc, striatum (STR), AMG, POA, SCN, and VH. In all regions quantified, reproductively active males had significantly more MT1-ir cells than nonreproductive males. Within the summer breeding season, males had significantly more MT1-ir cells in the NAcc than did reproductively active females. In all other regions there was no significant difference in MT1-ir cell number between reproductively active males and females. Collectively, these data suggest that melatonin modulates vasotocin via MT1. These findings assist in elucidating the neuroendocrine mechanisms by which vertebrates integrate seasonal cues with physiology to correctly time critical life history events.

Rotating shift work, irregular sleep patterns and jetlag disrupt circadian rhythms, induce or aggravate disease, and produce deficits in cognitive function. Internal misalignment, a state in which abnormal phase relationships prevail between and within organs, is widely proposed to account for these adverse effects of circadian disruption. This hypothesis has been difficult to test because phase shifts of the entraining environmental cycle lead to transient desynchrony. Thus, it remains possible that phase shifts, regardless of internal desynchrony, account for adverse effects of circadian disruption. I have used the duper mutant hamster, whose locomotor activity rhythms re-entrain 5-fold faster than wild types after a phase shift of 8 hours, to test whether internal desynchrony can account for adverse effects of jet lag on adult neurogenesis. I subjected wild type and duper female hamsters to alternating 8h phase advances and delays of the LD cycle at 16-day intervals. I injected 5-Bromo-2’-deoxyuridine (BrdU, a thymidine analogue) after the 4th shift and collected brains after the 8th shift. As expected, mutants re-entrained activity rhythms more rapidly than did wild types. On the other hand, estrous cycles, as assessed by vaginal smears, were rarely disrupted by repeated phase shifts in either genotype. I next compared cell proliferation and neurogenesis in the subgranular zone of the hippocampus between Duper mutants and wild type siblings using the S-phase marker BrdU and the neuronal marker NeuN. I assessed the total number of BrdU cells in the subgranular zone of the hippocampus, as the proportion that expressed NeuN. Duper mutants had more BrdU-ir cells, and more BrdU+/NeuN+ cells than did wild types, whether or not they experienced phase shifts, revealing an unexpected increase in neurogenesis. Surprisingly, repeated phase shifts increased neurogenesis in WT but not duper hamsters. Despite the increase in neurogenesis, phase shifts reduced the number of adult-born non-neuronal (BrdU+/NeuN-) cells in WT hamsters but had no such effect on duper mutants. In addition, the duper mutation increases hippocampal neurogenesis regardless of circadian. Our results suggest that adult-born non-neuronal cells are most vulnerable to circadian disruption, and that internal desynchrony promotes their demise. disruption.

Major depressive disorder (MDD) is a leading cause of disability worldwide, with a lifetime prevalence rate of approximately 20%. Inadequate pharmacological treatment methods for MDD are a significant debilitating factor. Patient estimates suggest that the treatment resistance rate for pharmacological interventions is over 30%. Postmortem analyses of human tissue of individuals diagnosed with MDD have shown an increase in Poly (ADP-ribose) polymerase 1 (PARP-1) mRNA gene expression in prefrontal cortical white matter when compared to psychiatrically normal brain tissue. In order to further investigate this issue, the present study used the social defeat stress/chronic unpredictable stress (SDS + CUS) rodent model of depression to induce a state of chronic psychological distress. Rats were treated with either the PARP-inhibitor, 3-aminobenzamide (3-AB); a common selective serotonin reuptake inhibitor (SSRI) fluoxetine (FLX), or saline. During the stress manipulation we conducted the sucrose preference test, results revealed that saline-treated rats which had undergone SDS + CUS showed significant reductions in sucrose preference compared to all other groups. In addition, a social interaction test was conducted one day after the stress manipulation, and saline-treated stressed animals demonstrated less social interaction compared to all other groups, indicating the stress manipulation was effective. Neurobiological assays were conducted to examine PARP expression, microglial morphology, and proinflammatory cytokine expression. Though we expected to find a decrease, results from immunofluorescence studies of tissue sections revealed an elevation of PARP-1 protein expression in prefrontal cortical gray matter in the FLX/Stress group compared with SAL/Stress group. Microglial morphological changes indicated that the SAL/Stress group had significantly more prolate microglia when compared to all other treatment groups, suggesting early activation of microglia, an indicator of neuroinflammation. Increases in IL-1β and TNF-⍺ expression was observed in the hippocampus of the SAL/Stress group when compared to all other treatment groups. Interestingly, IL-6 expression was significantly elevated in the SAL/Stress group when compared to the FLX/Stress group and the CTRL/No stress group but did not significantly differ from the 3-AB/Stress group. This study revealed therapeutic potential of 3-AB for the treatment of stress-related disorders, as well as the neuroinflammatory mechanisms associated with chronic stress.