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Description
The recent spotlight on concussion has illuminated deficits in the current standard of care with regard to addressing acute and persistent cognitive signs and symptoms of mild brain injury. This stems, in part, from the diffuse nature of the injury, which tends not to produce focal cognitive or behavioral deficits

The recent spotlight on concussion has illuminated deficits in the current standard of care with regard to addressing acute and persistent cognitive signs and symptoms of mild brain injury. This stems, in part, from the diffuse nature of the injury, which tends not to produce focal cognitive or behavioral deficits that are easily identified or tracked. Indeed it has been shown that patients with enduring symptoms have difficulty describing their problems; therefore, there is an urgent need for a sensitive measure of brain activity that corresponds with higher order cognitive processing. The development of a neurophysiological metric that maps to clinical resolution would inform decisions about diagnosis and prognosis, including the need for clinical intervention to address cognitive deficits. The literature suggests the need for assessment of concussion under cognitively demanding tasks. Here, a joint behavioral- high-density electroencephalography (EEG) paradigm was employed. This allows for the examination of cortical activity patterns during speech comprehension at various levels of degradation in a sentence verification task, imposing the need for higher-order cognitive processes. Eight participants with concussion listened to true-false sentences produced with either moderately to highly intelligible noise-vocoders. Behavioral data were simultaneously collected. The analysis of cortical activation patterns included 1) the examination of event-related potentials, including latency and source localization, and 2) measures of frequency spectra and associated power. Individual performance patterns were assessed during acute injury and a return visit several months following injury. Results demonstrate a combination of task-related electrophysiology measures correspond to changes in task performance during the course of recovery. Further, a discriminant function analysis suggests EEG measures are more sensitive than behavioral measures in distinguishing between individuals with concussion and healthy controls at both injury and recovery, suggesting the robustness of neurophysiological measures during a cognitively demanding task to both injury and persisting pathophysiology.
ContributorsUtianski, Rene (Author) / Liss, Julie M (Thesis advisor) / Berisha, Visar (Committee member) / Caviness, John N (Committee member) / Dorman, Michael (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Distorted vowel production is a hallmark characteristic of dysarthric speech, irrespective of the underlying neurological condition or dysarthria diagnosis. A variety of acoustic metrics have been used to study the nature of vowel production deficits in dysarthria; however, not all demonstrate sensitivity to the exhibited deficits. Less attention has been

Distorted vowel production is a hallmark characteristic of dysarthric speech, irrespective of the underlying neurological condition or dysarthria diagnosis. A variety of acoustic metrics have been used to study the nature of vowel production deficits in dysarthria; however, not all demonstrate sensitivity to the exhibited deficits. Less attention has been paid to quantifying the vowel production deficits associated with the specific dysarthrias. Attempts to characterize the relationship between naturally degraded vowel production in dysarthria with overall intelligibility have met with mixed results, leading some to question the nature of this relationship. It has been suggested that aberrant vowel acoustics may be an index of overall severity of the impairment and not an "integral component" of the intelligibility deficit. A limitation of previous work detailing perceptual consequences of disordered vowel acoustics is that overall intelligibility, not vowel identification accuracy, has been the perceptual measure of interest. A series of three experiments were conducted to address the problems outlined herein. The goals of the first experiment were to identify subsets of vowel metrics that reliably distinguish speakers with dysarthria from non-disordered speakers and differentiate the dysarthria subtypes. Vowel metrics that capture vowel centralization and reduced spectral distinctiveness among vowels differentiated dysarthric from non-disordered speakers. Vowel metrics generally failed to differentiate speakers according to their dysarthria diagnosis. The second and third experiments were conducted to evaluate the relationship between degraded vowel acoustics and the resulting percept. In the second experiment, correlation and regression analyses revealed vowel metrics that capture vowel centralization and distinctiveness and movement of the second formant frequency were most predictive of vowel identification accuracy and overall intelligibility. The third experiment was conducted to evaluate the extent to which the nature of the acoustic degradation predicts the resulting percept. Results suggest distinctive vowel tokens are better identified and, likewise, better-identified tokens are more distinctive. Further, an above-chance level agreement between nature of vowel misclassification and misidentification errors was demonstrated for all vowels, suggesting degraded vowel acoustics are not merely an index of severity in dysarthria, but rather are an integral component of the resultant intelligibility disorder.
ContributorsLansford, Kaitlin L (Author) / Liss, Julie M (Thesis advisor) / Dorman, Michael F. (Committee member) / Azuma, Tamiko (Committee member) / Lotto, Andrew J (Committee member) / Arizona State University (Publisher)
Created2012
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Description
In this study, the Bark transform and Lobanov method were used to normalize vowel formants in speech produced by persons with dysarthria. The computer classification accuracy of these normalized data were then compared to the results of human perceptual classification accuracy of the actual vowels. These results were then analyzed

In this study, the Bark transform and Lobanov method were used to normalize vowel formants in speech produced by persons with dysarthria. The computer classification accuracy of these normalized data were then compared to the results of human perceptual classification accuracy of the actual vowels. These results were then analyzed to determine if these techniques correlated with the human data.
ContributorsJones, Hanna Vanessa (Author) / Liss, Julie (Thesis director) / Dorman, Michael (Committee member) / Borrie, Stephanie (Committee member) / Barrett, The Honors College (Contributor) / Department of Speech and Hearing Science (Contributor) / Department of English (Contributor) / Speech and Hearing Science (Contributor)
Created2013-05