Theses and Dissertations from UMD
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New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM
More information is available at Theses and Dissertations at University of Maryland Libraries.
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Item EEG EFFECTS OF EVENT MODELS IN STORY COMPREHENSION(2023) Rickles, Ben Bogart; Bolger, Donald J; Neuroscience and Cognitive Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Cognitive models can offer deep insights into how stories are comprehended. Models which follow event segmentation theory (EST) focus on the processing of brief episodes or events within a narrative and the boundaries between events. To test the brain mechanisms proposed by EST to occur at the event boundaries we looked at electroencephalographs (EEG) recorded from 49 participants as they were tasked with both listening to and recalling 9 blocks of ~ 6 minute-long audio clips in one of three conditions: single ordered stories, unrelated events from unrelated stories, or single stories in scrambled order. All stimuli were designed to contain event boundaries spaced at semi-regular intervals. Accuracy during an inference recognition task administered after each block was highest in the single ordered stories condition. Analysis 1 examined the effects of event boundary vs. local semantic context on evoked negativities (N400) related to lexical processing of each word. Effects of condition suggest that narrative structure affected lexical processing, more so than event-level structure and sentence-level semantic context. Analysis 2 Examined changes in alpha (8.5-12.5 Hz) and theta (4-8 Hz) band power of the EEG induced by the onset of the event boundary. Boundary-induced changes in both frequencies were recorded, in all conditions. The largest increases were recorded during the ordered stories over large portions of the scalp. How these findings relate to cognitive mechanisms suggested by event segmentation theory is discussed.Item THE ACOUSTIC QUALITIES THAT INFLUENCE AUDITORY OBJECT AND EVENT RECOGNITION(2019) Ogg, Mattson Wallace; Slevc, L. Robert; Neuroscience and Cognitive Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Throughout the course of a given day, human listeners encounter an immense variety of sounds in their environment. These are quickly transformed into mental representations of objects and events in the world, which guide more complex cognitive processes and behaviors. Through five experiments in this dissertation, I investigated the rapid formation of auditory object and event representations (i.e., shortly after sound onset) with a particular focus on understanding what acoustic information the auditory system uses to support this recognition process. The first three experiments analyzed behavioral (dissimilarity ratings in Experiment 1; duration-gated identification in Experiment 2) and neural (MEG decoding in Experiment 3) responses to a diverse array of natural sound recordings as a function of the acoustic qualities of the stimuli and their temporal development alongside participants’ concurrently developing responses. The findings from these studies highlight the importance of acoustic qualities related to noisiness, spectral envelope, spectrotemporal change over time, and change in fundamental frequency over time for sound recognition. Two additional studies further tested these results via syntheszied stimuli that explicitly manipulated these acoustic cues, interspersed among a new set of natural sounds. Findings from these acoustic manipulations as well as replications of my previous findings (with new stimuli and tasks) again revealed the importance of aperiodicity, spectral envelope, spectral variability and fundamental frequency in sound-category representations. Moreover, analyses of the synthesized stimuli suggested that aperiodicity is a particularly robust cue for some categories and that speech is difficult to characterize acoustically, at least based on this set of acoustic dimensions and synthesis approach. While the study of the perception of these acoustic cues has a long history, a fuller understanding of how these qualities contribute to natural auditory object recognition in humans has been difficult to glean. This is in part because behaviorally important categories of sound (studied together in this work) have previously been studied in isolation. By bringing these literatures together over these five experiments, this dissertation begins to outline a feature space that encapsulates many different behaviorally relevant sounds with dimensions related to aperiodicity, spectral envelope, spectral variability and fundamental frequency.Item Medial Frontal Theta Negativities (MFTN) as Predictors of Anxiety Sensitivity Treatment Response(2019) Ellis, Jessica Steward; Bernat, Edward M; Neuroscience and Cognitive Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Anxiety is one of the most prevalent mental health problems around the world. Despite a number of widely available interventions, it can take weeks or months to see effects, and nearly half of individuals may not respond. In an effort to better understand response rates, a large body of evidence indicates the most consistent predictor of treatment outcomes is activity in the anterior cingulate cortex (ACC). Although activity in ACC can be measured by medial frontal theta event related potentials (ERPs) at a finer temporal resolution, these neurophysiological components have not been evaluated as predictors of treatment response. There is also a lack of research on the functional networks associated with ACC treatment prediction, despite implications for prefrontal engagement of cognitive control processes. The present study aimed to examine these gaps in the literature by using task-based electroencephalography (EEG) and medial frontal theta negativities (MFTN) as predictors of anxiety sensitivity treatment response. Using amplitude as well as functional connectivity measures (i.e., inter-channel phase synchrony), baseline MFTN (i.e., Theta-FN, Theta-N2) were assessed as predictors of treatment response at mid-treatment, 1-week post treatment, and 6 months post treatment. Subjects underwent a baseline EEG before completing three sessions of a computerized cognitive behavioral intervention. Contrary to the hypothesis, findings revealed MFTN amplitude did not predict treatment response. However, medial to lateral prefrontal theta phase synchrony demonstrated significant prediction effects, such that lower phase synchrony was associated with greater symptom improvement at mid-treatment, 1-week post treatment, and 6 months post treatment. This effect was specific to certain task conditions (i.e., gain feedback and go stimuli), as well as to the combined anxiety and depression treatment group. Results demonstrated accuracy and consistency of treatment prediction, as well as incremental validity after controlling for self-report measures. Finally, results provide additional support for a convergent medial frontal theta process, and suggest that low engagement of regulatory and proactive control mechanisms may be predictive of better response to cognitive behavioral interventions. This work represents a novel finding that may contribute to the improvement in treatment efficacy by serving as a target for future interventions and individualized treatment selection.Item Analysis of Gamma-Band Auditory Responses in Schizophrenia(2015) Walsh, Benjamin Bryan; Simon, Jonathan Z; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Schizophrenia is a debilitating mental illness that affects 1% of the general population. One characteristic symptom is auditory hallucinations, which is experienced by almost all patients sometime in their lifetime. To investigate differences in auditory response in general, 50 schizophrenic patients and 50 age and sex-matched healthy controls were presented with auditory click trains at 40 Hz. Responses are recorded using electroencephalography (EEG). Magnitude and phase of responses at 40 Hz are computed using Gabor filters. Supporting previous literature, a significant difference in inter-trial phase coherence (ITC) and overall power is found between patients and controls, in particular near stimulus onset. Additionally, this study also investigated inter-subject phase coherence (ISC). This study finds that ISC is in fact higher for patients, in particular near stimulus onset. One possible explanation is that while healthy controls develop a preferred phase for perception, schizophrenic patients exhibit phase that is primarily stimulus-driven.Item Decoding Repetitive Finger Movements with Brain Signals Acquired Via Noninvasive Electroencephalography(2011) Paek, Andrew Young; Contreras-Vidal, Jose L; Bioengineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)We investigated how well finger movements can be decoded from electroencephalography (EEG) signals. 18 hand joint angles were measured simultaneously with 64-channel EEG while subjects performed a repetitive finger tapping task. A linear decoder with memory was used to predict continuous index finger angular velocities from EEG signals. A genetic algorithm was used to select EEG channels across temporal lags between the EEG and kinematics recordings, which optimized decoding accuracies. To evaluate the accuracy of the decoder, the Pearson's correlation coefficient (r) between the observed and predicted trajectories was calculated in a 10-fold cross-validation scheme. Our results (median r = .403, maximum r = .704), compare favorably with previous studies that used electrocorticography (ECoG) to decode finger movements. The decoder used in this study can be used for future brain machine interfaces, where individuals can control peripheral devices through EEG signals.