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Undergraduate Research Opportunities Program

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Start date: 2020 × End date: 2023 × search.filters.applied.f.advisor: Schumacher, Eric H. ×

Publication Search Results

Now showing 1 - 4 of 4
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    Improving Online Instructional Design using Memory, Attention, and Engagement
    (Georgia Institute of Technology, 2022-05) Chanda, Ritika
    Neuroscience research supports a relationship between the psychological constructions of attention and engagement. The level of selective attention and engagement present during the learning process correlates with increased memory and recall. With the recent rise in online learning, new questions regarding the improvement of educational design, teaching techniques, and learning have created a new avenue of investigation within the field of Neuroeducation. The objective of this study is to identify whether attentional brain networks related to Gagné’s Nine Events of Instruction and engagement can predict learning in an online setting by using fMRI and behavioral techniques. Overall, we found fMRI evidence of engagement, verified engagement’s role in memory and retrieval, and identified three Gagné events (Events 5, 6 and 7) that increase learning among students. This investigation allows for further advancements in online educational design as it will provide instructors with guidance on how to properly build their curriculum and modify the content structure of online classes to highlight techniques that promote successful learning.
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    Sleep and Quasi-Periodic Patterns During Rest
    (Georgia Institute of Technology, 2022-05) Karkare, Maya C.
    In this preliminary study, researchers attempted to determine the relationship between sleep and quasi-periodic pattern strength. Three participants wore actigraphy watches for three nights prior to a resting-state functional MRI (rs-fMRI) scan. Actigraphy data was analyzed using the Cole Kripke analysis method. Functional connectivity was analyzed for quasi-periodic patterns (QPPs) between the default mode network (DMN) and the task-positive network (TPN). Due to errors involving preprocessing of rs-fMRI data, proper QPP analyses were unable to be conducted as the QPP template was abnormal. Further analysis of the data collected in the future will yield more conclusive results.
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    The Impact of Sleep on Quasi-Periodic Patterns During Working Memory Tasks
    (Georgia Institute of Technology, 2022-05) Huell, Derek Terrell
    Quasi-periodic patterns (QPPs) are a form of low-frequency neural activity that include the interactions of both default mode and task positive networks. As this brain activity occurs constantly in our brains, they are suspected to contribute to the brain's functional connectivity. This is critical to our understanding understanding of the coordination of activity between multiple brain regions over time to accomplish tasks. Thus, this cognitive neuroscience study will seek to illuminate the effects of underlying brain mechanisms on QPPs, representing functional connectivity. Previous literature has shown that the pattern of QPPs may vary between individuals and with levels of sleep, and this variability may impact the brain's functional connectivity. In this study, we will analyze neural activity while participants complete 0-back, 2-back, and flanker tasks and a resting state fMRI scan, and pair these results with a wearable accelerometer to evaluate how sleep levels affect QPPs.
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    Broad Effects of Arousal on Quasi-Periodic Patterns of Brain Activity
    (Georgia Institute of Technology, 2020-12) Humm, Erek Matthew
    Quasi Periodic Patterns (QPPs) are recurring patterns of brain activity found in brain imaging data that last approximately 20 seconds and occur at no regular interval. In this experiment, researchers aim to establish a link between the level of mental arousal and the strength and frequency of QPPs. It was thought that increased levels of arousal would result in an increase in the strength and frequency of QPPs. To test this, subjects from three different contrasting experimental groups conducted tasks while in a functional magnetic resonance imaging (fMRI) scanner: (1) young subjects vs. old subjects, (2) task-engaged vs. resting-state, and (3) sleep disorder vs. no disorder. QPPs were regressed from the fMRI scans using an extensive processing and analysis pipeline. It was generally found that increased arousal levels led to an increase in the incidence and strength of QPPs. Increased arousal is present in young subjects, task-engaged subjects, and subjects without sleeping disorders. These results open the door for future experiments to quantify the link between arousal and QPPs. Establishing a link between these two can be vital to future research involving therapeutic devices, diagnostic tools, and even human-computer interfaces.