Matching Items (4)
Description
When surgical resection becomes necessary to alleviate a patient's epileptiform activity, that patient is monitored by video synchronized with electrocorticography (ECoG) to determine the type and location of seizure focus. This provides a unique opportunity for researchers to gather neurophysiological data with high temporal and spatial resolution; these data are assessed prior to surgical resection to ensure the preservation of the patient's quality of life, e.g. avoid the removal of brain tissue required for speech processing. Currently considered the "gold standard" for the mapping of cortex, electrical cortical stimulation (ECS) involves the systematic activation of pairs of electrodes to localize functionally specific brain regions. This method has distinct limitations, which often includes pain experienced by the patient. Even in the best cases, the technique suffers from subjective assessments on the parts of both patients and physicians, and high inter- and intra-observer variability. Recent advances have been made as researchers have reported the localization of language areas through several signal processing methodologies, all necessitating patient participation in a controlled experiment. The development of a quantification tool to localize speech areas in which a patient is engaged in an unconstrained interpersonal conversation would eliminate the dependence of biased patient and reviewer input, as well as unnecessary discomfort to the patient. Post-hoc ECoG data were gathered from five patients with intractable epilepsy while each was engaged in a conversation with family members or clinicians. After the data were separated into different speech conditions, the power of each was compared to baseline to determine statistically significant activated electrodes. The results of several analytical methods are presented here. The algorithms did not yield language-specific areas exclusively, as broad activation of statistically significant electrodes was apparent across cortical areas. For one patient, 15 adjacent contacts along superior temporal gyrus (STG) and posterior part of the temporal lobe were determined language-significant through a controlled experiment. The task involved a patient lying in bed listening to repeated words, and yielded statistically significant activations that aligned with those of clinical evaluation. The results of this study do not support the hypothesis that unconstrained conversation may be used to localize areas required for receptive and productive speech, yet suggests a simple listening task may be an adequate alternative to direct cortical stimulation.
ContributorsLingo VanGilder, Jennapher (Author) / Helms Tillery, Stephen I (Thesis advisor) / Wahnoun, Remy (Thesis advisor) / Buneo, Christopher (Committee member) / Arizona State University (Publisher)
Created2013
Description
Psychogenic non-epileptic seizures (PNES), is a conversion disorder thought to be linked to unresolved emotional distress. While some studies suggest that PNES patients do not attribute their somatic symptoms to severe psychological experiences (Stone, Binzer, & Sharpe, 2004; LaFrance & Barry, 2005), it is unclear what PNES patients do think causes their seizures, and the psychological consequences of those attributions. The aim of the present study was to investigate PNES patients' attributions for their seizures, and to determine how these attributions relate to stress and emotion regulation. It was hypothesized that participants who attribute their seizures to something (i.e., have an explanation for their seizures) will have lower perceived stress and less difficulty with emotion regulation than those who are unsure of the cause of their seizures. Twenty-four PNES participants completed a questionnaire assessing seizure diagnosis, characteristics of seizure impact, perceived stress, psychological symptoms, emotion regulation, attributions for seizures, and coping resources. Contrary to the hypothesis, having an explanation for seizures, rather than being “unsure” of seizure cause, was related to greater perceived stress. While it would seem that attributing unpredictable seizure events to a cause would lower perceived stress and emotion regulation difficulty, this study indicates that an attribution to an unknown cause may be more beneficial for the individual.
ContributorsBarker, Mallory (Author) / Roberts, Nicole A. (Thesis advisor) / Miller, Paul A. (Committee member) / Burleson, Mary H (Committee member) / Arizona State University (Publisher)
Created2012
Description
Abstract
Diagnosing psychogenic non-epileptic seizures (PNES) requires admission to an epilepsy monitoring unit, which is a lengthy and expensive process. Despite the cost of and time commitment to this inpatient evaluation, a definitive diagnosis at the end isn’t always guaranteed. Therefore, predictor variables such as demographic information and psychological testing scores can help improve the accuracy of diagnosing PNES or epilepsy at the end of a patient’s EMU admission. Locke et al. have demonstrated that the SOM scale and SOM-C subscale on the Personality Assessment Inventory (PAI) are the best indicators for predicting PNES diagnosis, with an optimal cut score of T≥70 on both of these scales. The aim of the current study was to determine whether evaluating male and female performance separately on these relevant PAI scales improves the accuracy of diagnosing PNES. The results support the hypothesis, such that male optimal cut scores on the SOM and SOM C scales are T=80 and T=75, respectively, and female optimal cut scores on the SOM and SOM C scales are T=71 and T=72, respectively. Utilizing the results of this study can help clinicians diagnose patients with PNES or epilepsy at the end of EMU evaluation with more certainty.
Diagnosing psychogenic non-epileptic seizures (PNES) requires admission to an epilepsy monitoring unit, which is a lengthy and expensive process. Despite the cost of and time commitment to this inpatient evaluation, a definitive diagnosis at the end isn’t always guaranteed. Therefore, predictor variables such as demographic information and psychological testing scores can help improve the accuracy of diagnosing PNES or epilepsy at the end of a patient’s EMU admission. Locke et al. have demonstrated that the SOM scale and SOM-C subscale on the Personality Assessment Inventory (PAI) are the best indicators for predicting PNES diagnosis, with an optimal cut score of T≥70 on both of these scales. The aim of the current study was to determine whether evaluating male and female performance separately on these relevant PAI scales improves the accuracy of diagnosing PNES. The results support the hypothesis, such that male optimal cut scores on the SOM and SOM C scales are T=80 and T=75, respectively, and female optimal cut scores on the SOM and SOM C scales are T=71 and T=72, respectively. Utilizing the results of this study can help clinicians diagnose patients with PNES or epilepsy at the end of EMU evaluation with more certainty.
ContributorsCorallo, Kelsey Lynn (Author) / Lanyon, Richard (Thesis director) / Knight, George (Committee member) / Karoly, Paul (Committee member) / Barrett, The Honors College (Contributor) / School of Social Transformation (Contributor) / Department of Psychology (Contributor)
Created2015-05
Description
Epilepsy is a complex neurological disease that affects one in twenty-six people. Despite this prevalence, it is very difficult to diagnose. EpiFinder, Inc. has created an app to better diagnose epilepsy through the use of an epilepsy focused ontology and a heuristic algorithm. Throughout this project, efforts were made to improve the user interface and robustness of the EpiFinder app in order to ease usability and increase diagnostic accuracy. A general workflow of the app was created to aid new users with navigation of the app’s screens. Additionally, numerous diagnostic guidelines provided by the International League Against Epilepsy as well as de-identified case studies were annotated using the Knowtator plug-in in Protégé 3.3.1, where new terms not currently represented in the seizure and epilepsy syndrome ontology (ESSO) were identified for future integration into the ontology. This will help to increase the confidence level of the differential diagnosis reached. A basic evaluation of the user interface was done to provide feedback for the developers for future iterations of the app. Significant efforts were also made for better incorporation of the app into a physician’s typical workflow. For instance, an ontology of a basic review of systems of a medical history was built in Protégé 4.2 for later integration with the ESSO, which will help to increase efficiency and familiarity of the app for physician users. Finally, feedback regarding utility of the app was gathered from an epilepsy support group. These points will be taken into consideration for development of patient-based features in future versions of the EpiFinder app. It is the hope that these various improvements of the app will contribute to a more efficient, more accurate diagnosis of epilepsy patients, resulting in more appropriate treatments and an overall increased quality of life.
ContributorsCsernak, Lidia Maria (Author) / Crook, Sharon (Thesis director) / Greger, Bradley (Committee member) / Yao, Robert (Committee member) / School of Life Sciences (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12