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Now showing 1 - 10 of 12

Representing the Effect of Multiple Alternatives and Information Strength on Confidence in Perceptual Decision Tasks

(Georgia Institute of Technology, 2020-12) Crabtree, Brooklyn

Confidence in perceptual decisions is a baseline for quantitatively measuring metacognitive processes in psychology. Most researchers limit the stimulus to two choices, assuming that the mental process summarizes the likely accuracy of all choices to determine confidence in the decision. The purpose of this study was to determine whether multiple alternative choices, with varying levels of information strength for each choice, follow the same mental statistics as similar two-alternative forced choice (2AFC) tasks. If the differences between information strengths for each of the multiple choices had a direct effect on confidence, then presenting higher and lower differences of information strength between the correct choice and the incorrect choice would result in corresponding higher and lower confidence ratings. Participants were shown multicolor clouds of dots made up of three colors, with one dot color (dominant) being more abundant than the others. Participants decided which color was the dominant color for each cloud, then indicated their confidence in that decision. The overall information strength, dominant-secondary strength difference, and dominant-tertiary strength difference all had significant main effects on both confidence and accuracy. The overall strength had the largest effect size for confidence, with more information strength resulting in higher confidence ratings. The dominant-secondary strength difference had the largest effect size for accuracy, with a larger difference between dominant and secondary color strengths resulting in higher accuracy rates. Further investigation on how the brain defines relevant stimuli in an environment and processing of multiple choices must be conducted before developing computational models for confidence.
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.
Influence of Social Intention on Switch Cost in Task-Switching Paradigms

(Georgia Institute of Technology, 2020-12) Barrett, Jacquelyn Marie

Humans have built a society based upon elaborate social interactions. We have processes that enable us to interact with each other and switch between tasks. Humans often multitask especially in a social context, such as talking while working on a project, listening to someone while driving, or switching between conversations with different people. One of these processes that aids in this interaction is the intentional stance. The intentional stance is the tendency humans have to view other’s actions as driven by their own mental states, beliefs, and intentions. In this experiment, it is examined whether or not social cognition, such as inferring the beliefs or intentions of others, behaves like other cognitively dominant tasks. Cognitively dominant tasks are automatic processes that are elicited with minimal to no effort, such as reading. A task switching paradigm was used among two groups, social and non-social, where tasks in the social group invoke the intentional stance and tasks in the non-social group do not. Switch cost, the increase in reaction time when switching between tasks, may increase when switching from a hard task to an easier task. This is due to the amount of inhibition initially placed on the easier stimuli in order to attend to the cued, more difficult stimulus until the more readily available stimulus has become relevant again Based on previous research, it is believed that switching from a non-social to a social task will result in a greater switch cost due to the amount of effort needed to overcome inhibition initially placed on the more readily available stimuli, or the social stimuli. These findings would support the hypothesis that social cognitive process behave similarly to other cognitively dominant processes.
Brain mechanisms for the cognitive effects of dual task interference

(Georgia Institute of Technology, 2020-08) Heo, Yeseul

Our ability to multitask has been found to have critical limitations primarily due to the restricted available attentional resources. Although many studies have explored the phenomena of processing bottleneck using serial reaction time experimental designs, there has been a significant limitation in the current literature due to the complex nature of multiple task representations. In other words, it is difficult to relate the discrepancy in performances during one-task and two-task solely to the differences in the task representation mechanisms because of the convoluted interaction between the single task and dual task experiments. To minimize such discrepancy, Schumacher et al. (2018) introduced a novel dual-task procedure that uses constant stimuli for one-task and two-task conditions. This study expanded the work by Schumacher et al. by replicating the experimental design to observe similar performance trends that show greater effects of dual-task interference in the two-task condition compared to that in the one-task condition. This finding set the stage for functional data collection that will occur following the current study using neuroimaging techniques to identify the neural correlates responsible for the facilitation of multitasking.
The Effects of Boundary Manipulations on Navigational Abilities

(Georgia Institute of Technology, 2020-08) Han, Andrew Taekyu

The purpose of this study is to see how manipulating boundaries impact one’s spatial memory in unfamiliar spaces. To test this, after we measured our participants’ Sense of Direction (SOD) and memory capacities, they were equally divided up into three separate training conditions: an abstract environment, a translucent environment, and a control environment. Afterwards, they were evaluated using wayfinding and pointing tasks. Our results indicated that the abstract training significantly impacted those with varying SOD’s. Those with low SOD’s in the control condition outperformed their abstract counterparts in wayfinding, and those with high SOD’s in the opaque abstract condition outperformed their control counterparts in the pointing tasks. This could be due to their reliance on different navigation strategies. In this case piloting versus path integration, respectively. Regardless, this study emphasizes the need to further investigate other methods of boundary manipulation that will potentially affect people’s spatial abilities.
Basal Forebrain Degeneration and Cortisol as Biomarkers Mediating Alzheimer’s Disease Pathology: A Machine Learning Approach

(Georgia Institute of Technology, 2020-05) Nakirikanti, Anudeep Sai

The impact of Alzheimer’s Disease (AD) on today’s society and healthcare is unprecedented. As a larger portion of today’s population enters an age for which AD becomes a health concern, there is growing support among health practitioners to prevent the disease’s progression and development. Early identification of the disease may serve as a critical step towards combating the disease, allowing earlier interventions in the disease process to foster healthy aging. The focus of such interventions includes alleviating risk factors of AD, two of which include cortisol and degeneration in the basal forebrain. Importantly, increased levels of cortisol and reduced volume in the basal forebrain are attributed to higher risks of AD. In the present study, we make use of machine learning and the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database to characterize individuals with AD by using data from cortisol levels and basal forebrain degeneration. This allowed us to test whether cortisol and basal forebrain degeneration were predictively valuable for AD diagnosis. Our data partially supported our prediction—the machine learning classifier yielded significantly above chance classification accuracy for basal forebrain degeneration, but the classification accuracy for cortisol was not significantly above chance. Consequently, our results indicate that basal forebrain degeneration might serve as a diagnostically useful biomarker for AD, while cortisol’s role in AD characterization necessitates further investigation.
Stress effects on the ability to learn statistical regularities about our world

(Georgia Institute of Technology, 2020-05) Freeman, Sarah Austin

Stress, a common feature of everyday life, has been demonstrated in numerous studies to profoundly impact memory function, particularly functions dependent on the hippocampus. The impacts of acute stress on statistical learning are still unknown, as statistical learning has only recently been demonstrated to rely on hippocampal mechanisms. In order to examine the impact of acute stress on statistical learning, as well as investigate individual differences in statistical learning performance, I induced acute stress via shock on healthy young adults during either the encoding or retrieval phase of a previously established statistical learning tasks that is based on implicit learning of temporal community structures. Preliminary results suggest that stress applied during either encoding or retrieval can disrupt statistical learning, though further data collection is needed to generate a more robust model of these effects. A thorough definition of the interactions between stress and statistical learning of temporal relationships has implications for understanding maladaptive effects of stress mechanisms and potential interventions for improving learning and memory – and thus quality of life - for people who suffer from chronic stress disorders, such as generalized anxiety disorder and post-traumatic stress disorder.
Characteristic Neural Firing Profiles in Different Hippocampal Subfields for Successful and Unsuccessful Memory

(Georgia Institute of Technology, 2020-05) Ben-Yishai, Tal

Memory is our ability to encode, store, retrain, and subsequently recall information and past experiences. Different areas of the brain are responsible for different aspects of memory, including the hippocampus which enables us to form, organize, and store new memories. Numerous research studies show that the hippocampal subfields are affected by memory related diseases such as Alzheimer’s Disease and Schizophrenia in different ways. Understanding what the different hippocampal subfields do is important for basic science, but also for understanding neurodegenerative disorders which are associated with structural and functional abnormalities of hippocampal neurons. In order to examine the effects of memory success and failure of the firing patterns of the hippocampal neurons in the different subfields, I used a unique dataset, published by Faraut et al (2018), of a large sample of intracranial neural spiking data from humans.) and ran a hierarchical clustering algorithm on the neural firing patterns. Results suggest that the neurons in the different hippocampus subfields (CA1, CA2, CA3, and DG) have certain firing profiles which as a result causes them to group together according to these specific subfields. These firing patters were different in some degree depending on weather on successful and unsuccessful memory – and thus suggest each subfield processes memories in a different way.
Encoding Differences in Aging Adults can Explain Associative Memory Deficits

(Georgia Institute of Technology, 2020-05) McClelland, Lauren

The relationship between aging and associative memory decline has been well-established in literature, however there is no clear reasoning for this decline. Recent functional magnetic resonance imaging (fMRI) studies have shown that aging adults show decreased neural specificity across the cortex, now commonly termed dedifferentiation. The current research attempts to find a relationship between increased dedifferentiation with age and their resulting decreases in associative memory performance. By utilizing multi-voxel pattern analysis (MVPA) classifiers, the level of neural distinctiveness of the variably aged adults can be quantified and compared to associative memory performance. We found that neural distinctiveness was decreased with age as well as retrieval of increasing levels of specificity of associate items. This suggests that the associative memory decline in older adults can be explained by a decrease in neural specificity for the specifics of associate items during encoding.
Sleep-based Memory Consolidation and Aging

(Georgia Institute of Technology, 2020-05) Lee, Claire

It is a known phenomenon that older adults tend to get less sleep and lower sleep quality compared to their younger counterparts, getting worse with age. They also often have difficulty falling asleep, which can be described as long sleep latency, and difficulty staying asleep throughout the night, characterized as low sleep quality. The implications of decreased amount of sleep includes impaired memory, inability to concentrate, reduced physical strength, hallucinations, and mood swings, to name a few. Oddly enough, older adults are able to function relatively normally even after fewer hours of sleep. As such, the current study focuses on the interrelationship between age, sleep, and memory to explain how both decreased hours of sleep and lower sleep quality in older adults affect behavior and cognition.