Epilepsy is a disease affecting millions of people worldwide. Despite over 50 years of research, the mechanisms that generate and sustain ictal discharges, a key neural hallmark of seizures, remain unknown. While once thought to be caused by hypersynchronous neuronal firing, we now recognize that the activity underlying ictal discharges is much more complex. With the development of microelectrode arrays (MEAs) suitable for use in humans, it is possible to observe neural activity at fine spatiotemporal scales in human patients with epilepsy. However, the diversity of seizure characteristics and limited patient population has led to a number of conflicting observations and theories. The purpose of this work is to elucidate mechanisms underlying ictal discharges in humans by applying statistical analyses and computational modeling to MEA recordings from human patients with epilepsy. We approach this aim in two projects. In the first project, we unify two seemingly conflicting theories surrounding cortical sources of ictal discharges. According to the ictal wavefront theory, ictal discharges are seeded at an expanding narrow front of high neuronal firing that delineates the boundary between regions of cortex with compromised functionality, and surrounding territory where the seizure is observable in electrical recordings, but cortical function remains intact. A second theory posits that discharges are predominantly seeded from a stationary localized cortical source. The two theories are based on observations from MEA recordings of seizures in two different small cohorts of patients. In this project, we analyze and model the discharge propagation patterns in a combined dataset from both cohorts. We show that discharges are seeded at the ictal wavefront in addition to other–possibly stationary–locations. In the second project, we characterize spatiotemporal patterns in the secondary transients of complex ictal discharges. Electrographic recordings of ictal discharges often have complex waveforms. Existing analyses focus on the spatiotemporal dynamics of the first, high-amplitude transient. In this project, we establish that ictal discharges often comprise multiple transients separated by ≈60 ms. Surprisingly, and contrary to our initial hypothesis, we find that individual transients within a complex discharge may propagate with different speeds, suggesting that different mechanisms are involved in the propagation of different transients.

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As the problem of resistance increases in the current health care system, new solutions to this problem are not emerging at a similar rate. The ability to discover novel antibiotics, and modify existing antibiotics, is competing with highly evolving resistance profiles. An alternate solution to this problem may be to search for inhibitors of these resistance mechanisms and pairing them with current antibiotics. Proof of this hypothesis lies in the great success of P-lactamase inhibitors already in the clinic. Inhibitors may be created using synthetic methods, however searching for inhibitors found in the natural environment may lead to a greater success. For example, bacteria in their natural setting must cope with constant exposure to antibiotics secreted by both themselves and by other species. As well, bacteria must be able to handle encounters with other species that are resistant to their own defense mechanisms. With this in consideration, it is possible that these bacteria have already established an ability to challenge resistance encountered in their own environment, such as through the secretion of compounds that inhibit these mechanisms. Screening of such inhibitors can be done against purified resistance elements or via cell-based screens with resistant bacteria. The focus of this research was to develop expression systems which contain inducible antibiotic resistance genes to be used for whole-cell screening for inhibitors of antibiotic resistance. The expression systems studied were pSWEET, for use in the Gram positive bacterium Bacillus subtilis, and pETcoco, for use in the Gram negative bacterium Escherichia coli. It was found that the pSWEET expression system integrated into the B. subtilis chromosome at unspecified locations and was not an ideal system for the proposed screen. pET coco holds promise as a suitable expression system but at this point in time it requires further examination to ensure plasmid stability and reproducibility of results. Therefore further examination of these two systems is needed if they are to be used in a screen for inhibitors, and a search for substitute systems must be undertaken. / Thesis / Master of Science (MSc)

Brainstem Auditory Evoked Potentials (BAEP) contain valuable information about the condition of the neural fibers associated with the auditory pathways. Extraction of this information is a difficult task due to contamination by on-going scalp EEG. This thesis reviews the current processing techniques and introduces adaptive noise cancellation (ANC) using systolic arrays as an alternative to existing technology. Q-R decomposition theory is reviewed and an explanation of the mechanics of systolic adaptive noise cancellation (SANC) is presented. A modified Given's rotation algorithm is derived resulting in a saving of up to 2/3 in memory requirements. Real data were collected in the laboratory. Real and simulated data were processed to determine the characteristics and effectiveness of adaptive noise cancellation strategies. Successful ANC of BAEP was performed on simulated data using a number or signal-to-noise ratios (S/N), data sequence lengths, reference signals and filter parameter values. We conclude that systolic arrays are a very powerful and appropriate technique for the extraction or BAEPs. Correlation studies indicated that the pre-stimulus EEG signal is inadequately correlated to the primary signal for successful ANC or BAEP in real data. A multi-channel collection scheme is outlined for future collection or Evoked Potential data. A summary or experimental results is presented to address the problem or data collection and signal processing optimization. / Thesis / Master of Engineering (MEngr)