Dynamic Complexity and Causality Analysis of Scalp EEG for Detection of Cognitive Deficits

This dissertation explores the potential of scalp electroencephalography (EEG) for the detection and evaluation of neurological deficits due to moderate/severe traumatic brain injury (TBI), mild cognitive impairment (MCI), and early Alzheimer’s disease (AD). Neurological disorders often cannot be accurately diagnosed without the use of advanced imaging modalities such as computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). Non-quantitative task-based examinations are also used. None of these techniques, however, are typically performed in the primary care setting. Furthermore, the time and expense involved often deters physicians from performing them, leading to potential worse prognoses for patients. If feasible, screening for cognitive deficits using scalp EEG would provide a fast, inexpensive, and less invasive alternative for evaluation of TBI post injury and detection of MCI and early AD. In this work various measures of EEG complexity and causality are explored as means of detecting cognitive deficits. Complexity measures include eventrelated Tsallis entropy, multiscale entropy, inter-regional transfer entropy delays, and regional variation in common spectral features, and graphical analysis of EEG inter-channel coherence. Causality analysis based on nonlinear state space reconstruction is explored in case studies of intensive care unit (ICU) signal reconstruction and detection of cognitive deficits via EEG reconstruction models. Significant contributions in this work include: (1) innovative entropy-based methods for analyzing event-related EEG data; (2) recommendations regarding differences in MCI/AD of common spectral and complexity features for different scalp regions and protocol conditions; (3) development of novel artificial neural network techniques for multivariate signal reconstruction; and (4) novel EEG biomarkers for detection of dementia

English for Operating a Small Business

This materials development project is a course program designed for owners, operators, and managers of small businesses, who are non-native English speakers. Emphasis will be on business terms and the language used in operating a family owned or a small business. Topics covered include typical conversations with accountants, lawyers, insurance agents, bankers, suppliers, creditors, customers, and employees

Paper Session II-A - The Testability of Software for the Space Station Freedom Program

The Space Station Freedom Data Management System consists of state-of-the-art hardware and software technology that exceeds the capabilities of earlier test tools and methods used to verify and certify man-rated space systems. New technologies and techniques are being developed to meet these challenges

Discrimination of Mild Cognitive Impairment and Alzheimer\u27s Disease Using Transfer Entropy Measures of Scalp EEG

Mild cognitive impairment (MCI) is a neurological condition related to early stages of dementia including Alzheimer\u27s disease (AD). This study investigates the potential of measures of transfer entropy in scalp EEG for effectively discriminating between normal aging, MCI, and AD participants. Resting EEG records from 48 age-matched participants (mean age 75.7 years)-15 normal controls, 16 MCI, and 17 early AD-are examined. The mean temporal delays corresponding to peaks in inter-regional transfer entropy are computed and used as features to discriminate between the three groups of participants. Three-way classification schemes based on binary support vector machine models demonstrate overall discrimination accuracies of 91.7- 93.8%, depending on the protocol condition. These results demonstrate the potential for EEG transfer entropy measures as biomarkers in identifying early MCI and AD. Moreover, the analyses based on short data segments (two minutes) render the method practical for a primary care setting

The chicken type III GnRH receptor homologue is predominantly expressed in the pituitary, and exhibits similar ligand selectivity to the type I receptor

Two GnRH isoforms (cGnRH-I and GnRH-II) and two GnRH receptor subtypes (cGnRH-R-I and cGnRH-R-III) occur in chickens. Differential roles for these molecules in regulating gonadotrophin secretion or other functions are unclear. To investigate this we cloned cGnRH-R-III from a broiler chicken and compared its structure, expression and pharmacological properties with cGnRH-R-I. The broiler cGnRH-R-III cDNA was 100% identical to the sequence reported in the red jungle fowl and white leghorn breed. Pituitary cGnRH-R-III mRNA was ∼1400-fold more abundant than cGnRH-R-I mRNA. Northern analysis indicated a single cGnRH-R-III transcript. A pronounced sex and age difference existed, with higher pituitary transcript levels in sexually mature females versus juvenile females. In contrast, higher expression levels occurred in juvenile males versus sexually mature males. Functional studies in COS-7 cells indicated that cGnRH-R-III has a higher binding affinity for GnRH-II than cGnRH-I (Kd: 0·57 vs 19·8 nM) with more potent stimulation of inositol phosphate production (ED50: 0·8 vs 4·38 nM). Similar results were found for cGnRH-R-I, (Kd: 0·51 vs 10·8 nM) and (ED50: 0·7 vs 2·8 nM). The initial rate of internalisation was faster for cGnRH-R-III than cGnRH-R-I (26 vs 15·8%/min). Effects of GnRH antagonists were compared at the two receptors. Antagonist #27 distinguished between cGnRH-R-I and cGnRH-R-III (IC50: 2·3 vs 351 nM). These results suggest that cGnRH-R-III is probably the major mediator of pituitary gonadotroph function, that antagonist #27 may allow delineation of receptor subtype function in vitro and in vivo and that tissue-specific recruitment of cGnRH-R isoforms has occurred during evolution

The Many Facets of Genetic Literacy: Assessing the Scalability of Multiple Measures for Broad Use in Survey Research

Objectives To determine how three dimensions of genetic literacy (familiarity, skills, and factual knowledge) fit the hierarchy of knowledge outlined in E.M. Rogers’ Diffusion of Innovations to better conceptualize lay understandings of genomics. Methods A consumer panel representing the US adult population (N = 1016) completed an electronic survey in November 2013. Adjusting for education, we used correlations, principle components analysis, Mokken Scale tests, and linear regressions to assess how scores on the three genetic literacy sub-dimensions fit an ordered scale. Results The three scores significantly loaded onto one factor, even when adjusting for education. Analyses revealed moderate strength in scaling (0.416, p\u3c0.001) and a difficulty ordering that matched Rogers’ hierarchy (knowledge more difficult than skills, followed by familiarity). Skills scores partially mediated the association between familiarity and knowledge with a significant indirect effect (0.241, p\u3c0.001). Conclusion We established an ordering in genetic literacy sub-dimensions such that familiarity with terminology precedes skills using information, which in turn precedes factual knowledge. This ordering is important to contextualizing previous findings, guiding measurement in future research, and identifying gaps in the understanding of genomics relevant to the demands of differing applications

Effects of Surotomycin on Clostridium difficile Viability and Toxin Production In Vitro

The increasing incidence and severity of infection by Clostridium difficile have stimulated attempts to develop new antimicrobial therapies. We report here the relative abilities of two antibiotics (metronidazole and vancomycin) in current use for treating C. difficile infection and of a third antimicrobial, surotomycin, to kill C. difficile cells at various stages of development and to inhibit the production of the toxin proteins that are the major virulence factors. The results indicate that none of the drugs affects the viability of spores at 8× MIC or 80× MIC and that all of the drugs kill exponential-phase cells when provided at 8× MIC. In contrast, none of the drugs killed stationary-phase cells or inhibited toxin production when provided at 8× MIC and neither vancomycin nor metronidazole killed stationary-phase cells when provided at 80× MIC. Surotomycin, on the other hand, did kill stationary-phase cells when provided at 80× MIC but did so without inducing lysis

Sugihara Causality Analysis of Scalp EEG for Detection of Early Alzheimer\u27s Disease

Recently, Sugihara proposed an innovative causality concept, which, in contrast to statistical predictability in Granger sense, characterizes underlying deterministic causation of the system. This work exploits Sugihara causality analysis to develop novel EEG biomarkers for discriminating normal aging from mild cognitive impairment (MCI) and early Alzheimer\u27s disease (AD). The hypothesis of this work is that scalp EEG based causality measurements have different distributions for different cognitive groups and hence the causality measurements can be used to distinguish between NC, MCI, and AD participants. The current results are based on 30-channel resting EEG records from 48 age-matched participants (mean age 75.7 years) - 15 normal controls (NCs), 16 MCI, and 17 early-stage AD. First, a reconstruction model is developed for each EEG channel, which predicts the signal in the current channel using data of the other 29 channels. The reconstruction model of the target channel is trained using NC, MCI, or AD records to generate an NC-, MCI-, or AD-specific model, respectively. To avoid over fitting, the training is based on the leave-one-out principle. Sugihara causality between the channels is described by a quality score based on comparison between the reconstructed signal and the original signal. The quality scores are studied for their potential as biomarkers to distinguish between the different cognitive groups. First, the dimension of the quality scores is reduced to two principal components. Then, a three-way classification based on the principal components is conducted. Accuracies of 95.8%, 95.8%, and 97.9% are achieved for resting eyes open, counting eyes closed, and resting eyes closed protocols, respectively. This work presents a novel application of Sugihara causality analysis to capture characteristic changes in EEG activity due to cognitive deficits. The developed method has excellent potential as individualized biomarkers in the detection of pathophysiological changes in early-stage AD