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Design and Evaluation of a Wearable EEG-PPG Device for Sleep Monitoring
No full textThis thesis presents the design, implementation, and evaluation of a novel wearable device for simultaneous electroencephalography (EEG) and photoplethysmography (PPG) monitoring during sleep. The research aims to facilitate more accessible and long-term sleep analysis, endeavoring to assist people in identifying potential sleep-related issues, improving their sleep habits, and ultimately promoting a healthier lifestyle. Our work addresses the growing need for portable, non-invasive sleep monitoring solutions that can provide comprehensive physiological data outside of clinical settings. Specifically, the research details the hardware design process, including circuit development for EEG and PPG signal acquisition, power management, and data processing capabilities. The device incorporates a Right Leg Drive (RLD) circuit for common-mode rejection in EEG recordings and an optimized PPG-based heart rate monitoring system. Empirical testing demonstrated the device's ability to capture high-quality EEG and PPG signals in real-world conditions. The EEG component successfully differentiated various brain wave frequencies, while the PPG measurements provided reliable heart rate data. Limitations such as eye movement artifact and the need for clinical validation were also addressed. Future work will focus on reducing the size of the board and developing a more user-friendly electrode attachment solution
Hierarchical and Explainable Feature Selection Framework for Dimensionality Reduction in Sleep Staging
No full textSleep is crucial for human health, and EEG signals play a significant role in sleep research. Due to the high-dimensional nature of EEG signal data sequences, data visualization and clustering of different sleep stages have been challenging. To address these issues, this thesis proposes a two-stage, hierarchical and explainable feature selection framework by incorporating a feature selection algorithm to improve the performance of dimensionality reduction. Inspired by topological data analysis (TDA), which can analyze the structure of high-dimensional data, we extracted topological features from the EEG signals to compensate for the structural information loss that happens in traditional spectro-temporal data analysis. Supported by the topological visualization of the data from different sleep stages and the classification results, the proposed features were proven to be effective supplements to traditional features. Finally, we compared the performances of three dimensionality reduction algorithms: Principal Component Analysis (PCA), t-Distributed Stochastic Neighbor
Embedding (t-SNE), and Uniform Manifold Approximation and Projection (UMAP). Among them, t-SNE achieved the highest accuracy of 79.8%, but considering the overall performance
in terms of computational resources and metrics, UMAP is the optimal choice
Principal Turnover: A Rural School Perspective and Suggestions for Retention
No full textPrincipal turnover is a significant challenge in education, particularly in rural school districts, and can affect student achievement and school culture. Turnover disrupts or stalls school initiatives and drains the administrative resources of schools, particularly rural schools with limited budgets. This dissertation examined the causes, effects, and potential solutions to principal turnover by examining data from seven semi-structured interviews with rural Pennsylvania school district superintendents. Findings reveal that increasing job responsibilities, limited compensation, and opportunities to leave their positions for jobs closer to home drive turnover. The problem is compounded by a shrinking candidate pool. Interview data and research literature also indicated that strategies to address these challenges include offering competitive compensation, enhancing principal support and school culture, and creating “grow-your-own” pipelines to develop local leadership talent
Rational Identification of Novel Senolytic Therapies Revealed by a Genome-Wide CRISPR Screen
No full textBy the year 2050, the largest demographic in the world will be individuals over 60 years of age2-4. Accompanying this demographic shift, there is an increased focus on aging and healthy longevity. With aging known as a risk factor in a variety of diseases, the biology of aging has become pertinent to the scientific understanding of these diseases. The goal of many researchers in this area is to be able to treat the underlying pathological mechanisms. One of the fundamental processes contributing to pathological aging is senescence, the irreversible growth arrest of cells in reaction to a stressor. The hallmarks of aging have listed senescence as one keys to understand aging biology since 20136,7. Senescent cells are being linked to a variety of diseases from atherosclerosis to osteoarthritis9-14. While the process of senescence safeguards against the transformation of damaged cells into cancerous cells, the persistence of these senescent cells has proved to be deleterious15,16. These senescent cells are notoriously difficult to kill once they persist in tissues unless they are cleared by a competent immune system9,13,14. These cells contribute to inflammatory paracrine signaling through secreted factors9,17.
With our understanding of senescence deepening, many have sought to develop drug candidates that can kill these persistent senescent cells. Some of the first senolytic drugs developed are now being tested in clinical trials to determine their efficacy in a variety of diseases9. These first generations of drugs sought to tip the balance of anti-apoptotic mechanisms in senescent cells towards a more pro-apoptotic mechanism9,17,19. These drugs have proven to have a narrow therapeutic index making their efficacy in the clinic difficult to assess without unwanted side effects30,60. To develop better senolytics, or drugs to target senescent cells, there is a need to develop rational approaches to better understanding senescent cell biology and to exploit any underlying vulnerabilities. In this study, we perform a novel whole genome CRISPR screen to select for targets that lead to the death of senescent cells without affecting the growth of healthy replicating cells. From this screen, we go on to validate PARP16 as a selectively lethal target in a variety of senescent cell types and following a variety of senescent cell triggers. Finally, we show that two small molecule inhibitors of PARP16 are able to specifically kill senescent cells. Using this platform, we show that systematic unbiased assessment of all genes in the genome allows the rational design of selective senolytic drugs
Task-Irrelevant Perceptual Learning
No full textThe brain is tasked with extracting behaviorally meaningful information from perceptual environments containing a wide array of sensory inputs across different modalities, many of which are irrelevant to an attended task. Studies have shown that perceptual learning can occur for task-irrelevant features given appropriate associations between the features and reinforcing events, and that this learning does not require attention towards or perceptual salience of the task-irrelevant feature. Most studies of task-irrelevant perceptual learning have been conducted in unisensory contexts where both the task and irrelevant features occur within the same sensory modality. It is unclear how modality contributes to this learning and the extent to which congruence in the sensory channels between the trained task and irrelevant stimuli interact with learning. To address these questions, this study used a custom and closely analogous auditory adaptation of a frequently used visual training approach. Participants were exposed to visual or auditory task-irrelevant motion stimuli while completing a visual or auditory number identification task. One direction was consistently and temporally paired with the task targets while the other direction was paired with some distractors. Tests of sensitivity administered before and after training revealed that directional learning occurred equally for all training conditions, whether unisensory (i.e., entirely visual or auditory) or cross-modal (i.e., visual task with acoustic task-irrelevant stimuli or vice versa). These findings suggest that the temporal relationship between stimuli and reinforcing events, rather than the sensory modalities of the stimuli and trained task, drive task-irrelevant perceptual learning. This nonspecificity to modality can be exploited to develop interventions where training with stronger sensory systems can engender concomitant enhancements in sensitivity for weaker ones
The Spatiotemporal Organization of Motor Cortex Activity Supporting Manual Dexterity
No full textMotor cortex (M1) is a crucial brain area for controlling voluntary movements, such as reaching and grasping for a cup of coffee. M1 is organized in a somatotopic manner, such that M1 output driving movement to different parts of the body is organized along the cortical surface. In primates, the arm and hand are represented in M1 as separate but overlapping territories. Unit activity recorded from the M1 forelimb representation comodulates with parameters related to reaching and/or grasping. The overall aim of this dissertation is to understand the spatiotemporal dynamics of M1 activity that produces reach-to-grasp movements. To address this goal, intracortical microstimulation (ICMS) is delivered along the precentral gyrus of two macaque monkeys to define the M1 motor map. Subsequently, cortical activity is recorded from the M1 forelimb representation using intrinsic signal optical imaging (ISOI) while macaques execute an instructed reach-to-grasp task. Results from imaging experiments produce spatial maps that define cortical territories with increased activity during reach-to-grasp movements. Next, unit activity was recorded from the M1 forelimb representation with a laminar multielectrode while macaques completed the same reach-to-grasp task. Recording site locations differed between sessions to comprehensively sample unit responses throughout the M1 forelimb representation. Imaging experiments reveal that activity supporting reach-to-grasp movements was concentrated in patches that comprise less than half of the M1 forelimb representation. Electrophysiology recordings reveal that activity related to reaching is spatially organized within M1 distinctly from activity related to grasping. The results support the idea that spatial organizing principles are inherent in M1 activity that supports reach-to-grasp movements
Network Analysis of Multimodal MRI to Identify Regional Associations with Neurodevelopmental Outcomes in Children with Congenital Heart Disease
No full textThis research addresses the critical relationship between Congenital Heart Disease (CHD) and neurodevelopment, recognizing the heightened risk of neurocognitive deficits and psychiatric disorders among CHD patients. To uncover the intricate connection between CHD and these conditions, this study harnesses the potential of brain network models derived from brain MRI data. By applying Functional Connectivity Networks (FCNs) and Morphometric Similarity Networks (MSNs), this research aims to investigate the differences between the brains of individuals with CHD and those without, with the potential to identify relationships with clinical outcomes.
Additionally, this work introduces an innovative automated tool for MSN development, addressing the significant challenges posed by the labor-intensive nature of MSN construction and the need for substantial domain expertise to get started. By overcoming the limitations of lab-specific customizations and the lack of standardized code-sharing practices, this tool streamlines the complex process of MSN creation. It reduces the barrier to entry for researchers while enabling the exploration of previously unexamined network parameters and configurations, fostering broader accessibility and collaboration in the field.
The methods and insights developed in this work provide a robust framework for investigating structural and functional brain differences in CHD patients. The findings offer valuable insights into the neurological development of individuals with CHD and support the generation of new hypotheses. Furthermore, the tools and findings from this research aim to serve the neuroimaging community by standardizing and expediting the generation of brain network models, enhancing replicability, and improving our understanding of their capabilities and limitations
Community partner compensation: strategies for humanizing payment processes
No full textEquitable compensation for people’s time and contributions is one way to demonstrate respect, dignity, and trustworthiness in the context of engaged scholarship. Institutional processes including contracts and payment processes can be challenging for individuals to navigate.
This workshop will share workflows for contracts, invoicing, and payment processes that involve increased transparency and accountability. The workflows consider approaching these institutional processes with several key questions: What are ways for those of us within academic institutions to reduce administrative burden for community partners? And how can we work collaboratively across our internal systems to expedite contracting and payment processes? Together, we can humanize our institutional processes on the pathway to strengthening our community partnerships
Cultivating successful academic-community partnerships: The role of CBO research capacity assessment in CBPR.
No full textAcademic institutions widely recognize community-based organizations (CBOs), as leaders, experts, and gatekeepers for minoritized communities. In fact, much of the existing literature about these communities would not be possible without CBOs. Despite the vital role CBOs play in the research process, CBOs have struggled to “maintain equitable partnerships with academic researchers,” as CBOs are oftentimes viewed by academics as lacking sufficient research capacity. This elitist perspective reinforces the inequitable power dynamics often cited in Community-based Participatory Research (CBPR). While perspectives vary on “who” gets to define and measure research capacity, efforts to develop a uniform framework are underway. The Community REsearch Activity Assessment Tool (CREAT), is one of the few frameworks available. In this session, participants will learn more about the framework, and how it can be used when working with CBOs not only to examine their research capacity, but to strengthen partnership efforts and produce better outcomes
Strengthening Families Protective Factors Framework
No full textThis presentation will provide an overview of the Strengthening Families Protective Factors Framework developed by the Center for the Study of Social Policy. The framework identifies five key protective factors—parental resilience, social connections, knowledge of parenting and child development, concrete support in times of need, and social-emotional competence of children—that promote positive family well-being and mitigate risk. Attendees will learn how these factors serve as a foundation for building capacity among family-facing direct service professionals. By focusing on strengths rather than deficits, this approach empowers professionals to support families in fostering healthy development, strengthening relationships, and improving outcomes