Thesis (Ph. D.)--University of California, San Diego, 1997. / Vita. Includes bibliographical references (leaves 174-188).

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A wide range of conditions are characterised by focal neurological symptoms, yet the pathophysiolgy often remains poorly understood. This thesis has focussed on applying functional neuroimaging in clinical groups. Migraines with aura are amongst the most common conditions posing a significant burden to sufferers. Elevated connectivity was detected in the visual cortex of migraine with aura patients, potentially complementing one of the leading proposed mechanisms for attacks. Minor strokes patients are also affected by focal symptoms after events which in some cases can be prolonged. Altered connectivity was observed in a number of regions reflecting previous findings for acute stroke. A group of transient ischaemic attack patients were also analysed, revealing subtle differences necessitating further study. Lastly disorders of consciousness pose acute challenges for treatment and ongoing care. Task based imaging was applied to form a more accurate picture of residual cognition. Additionally the correlation between measures derived from resting state data and cerebral glucose consumption was explored.

Spontaneously active frontal cortex and spinal cord networks grown on microelectrode arrays were used to study effects of D-methylphenidate. These central nervous system tissues have relatively low concentrations of dopaminergic and noradrenergic neurons compared to the richly populated loci, yet exhibit similar neurophysiological responses to methylphenidate. The spontaneous spike activity of both tissues was inhibited in a concentration-dependent manner by serial additions of 1-500 µM methylphenidate. Methylphenidate is non-toxic as spike inhibition was recovered following washes. The average concentrations for 50% spike rate inhibition (IC50 ± SD) were 118 ± 52 (n= 6) and 57 ± 43 (n = 11) for frontal cortex and spinal cord networks, respectively. A 3 hour exposure of a network to 1 mM methylphenidate was nontoxic. The effective concentrations described in this study are within the therapeutic dosage range. Therefore, the platform may be used for further investigations of drug mechanisms.

Understanding the mapping between stimulus, behavior, and neural responses is vital for understanding sensory, motor, and general neural processing. We can examine this relationship through the complementary methods of encoding (predicting neural responses given the stimulus) and decoding (reconstructing the stimulus given the neural responses). The work presented in this thesis proposes, evaluates, and analyzes several nonlinear approaches for encoding and decoding that leverage recent advances in machine learning to achieve better accuracy. We first present and analyze a recurrent neural network encoding model to predict retinal ganglion cell responses to natural scenes, followed by a decoding approach that uses neural networks for approximate Bayesian decoding of natural images from these retinal cells. Finally, we present a probabilistic framework to distill behavioral videos into useful low-dimensional variables and to decode this behavior from neural activity.

Gene expression regulation is a set of critical biological processes that give rise to the diversity of cell types across tissues and development stages. Noncoding regions of the genome (intergenic + intronic, >98% of genome) play an important role in these processes, with noncoding genetic variation quantitatively affecting transcriptional activity, splicing of pre-mRNA, and localization, stability, and translational control of mRNA transcripts. Previous genetic studies of human disease have implicated numerous common noncoding loci with small but significant effect in common conditions. Recently, we and others have reported evidence supporting a role of rare noncoding variants with larger effect in early onset conditions such as birth defects and neurodevelopmental disorders. These early onset conditions are quite common in aggregate, affecting over 3% of young children. A better understanding of the functional impact of rare regulatory noncoding variants will enable novel genetic discovery, give insights of disease mechanisms, and ultimately improve diagnosis, treatment, and clinical care. In this thesis dissertation, I describe three related projects. First, we used a combinatorial multi-testing framework to find excess burden of noncoding de novo mutations in congenital heart disease (impacting both transcriptional and post-transcriptional regulatory stages). This finding was central to the rest of my work, motivating the development of new computational approaches to predict genetic effect of noncoding variants through the lens of post-transcriptional regulation. Second, we used convolutional neural networks to model and understand sequence specific RBP binding processes. Finally, we designed a graphical neural network model capable of integrating cause and consequence to predict genetic effect of rare noncoding variants. In summary, we developed new machine learning methods to analyze multimodal human genome sequencing data, uncover deeper insights into post-transcriptional gene regulatory processes, and advance genomic medicine.

MScEng / Thesis (MScEng (Mechanical and Mechatronic Engineering))--University of Stellenbosch, 2009. / Clinical gait analysis has been proven to greatly improve treatment planning and monitoring of patients suffering from neuromuscular disorders. Despite this fact, it was found that gait analysis is still largely underutilised in general patient-care due to limitations of gait measurement equipment. Inertial motion capture (IMC) is able to overcome many of these limitations, but this technology is relatively untested and is therefore viewed as adolescent. This study addresses this problem by evaluating the validity and repeatability of gait parameters measured with a commercially available, full-body IMC system by comparing the results to those obtained with alternative methods of motion capture. The IMC system’s results were compared to a trusted optical motion capture (OMC) system’s results to evaluate validity. The results show that the measurements for the hip and knee obtained with IMC compares well with those obtained using OMC – with coefficient-of-correlation (R) values as high as 0.99. Some discrepancies were identified in the ankle-joint validity results. These were attributed to differences between the two systems with regard to the definition of ankle joint and to non-ideal IMC system foot-sensor design. The repeatability, using the IMC system, was quantified using the coefficient of variance (CV), the coefficient of multiple determination (CMD) and the coefficient of multiple correlation (CMC). Results show that IMC-recorded gait patterns have high repeatability for within-day tests (CMD: 0.786-0.984; CMC: 0.881-0.992) and between-day tests (CMD: 0.771-0.991; CMC: 0.872-0.995). These results compare well with those from similar studies done using OMC and electromagnetic motion capture (EMC), especially when comparing between-day results. Finally, to evaluate the measurements from the IMC system in a clinically useful application, a neural network was employed to distinguish between gait strides of stroke patients and those of able-bodied controls. The network proved to be very successful with a repeatable accuracy of 99.4% (1/166 misclassified). The study concluded that the full-body IMC system produces sufficiently valid and repeatable gait data to be used in clinical gait analysis, but that further refinement of the ankle-joint definition and improvements to the foot sensor are required.

This dissertation research explored the capabilities of neuronal networks grown on substrate integrated microelectrode arrays in vitro with emphasis on utilizing such preparations in three specific application domains: pharmacology and drug development, biosensors and neurotoxicology, and the study of burst and synaptic mechanisms. Chapter 1 details the testing of seven novel AChE inhibitors, demonstrating that neuronal networks rapidly detect small molecular differences in closely related compounds, and reveal information about their probable physiological effects that are not attainable through biochemical characterization alone. Chapter 2 shows how neuronal networks may be used to classify and characterize an unknown compound. The compound, trimethylol propane phosphate (TMPP) elicited changes in network activity that resembled those induced by bicuculline, a known epileptogenic. Further work determined that TMPP produces its effects on network activity through a competitive inhibition of the GABAA receptor. This demonstrates that neuronal networks can provide rapid, reliable warning of the presence of toxic substances, and from the manner in which the spontaneous activity changes provide information on the class of compound present and its potential physiological effects. Additional simple pharmacological tests can provide valuable information on primary mechanisms involved in the altered neuronal network responses. Chapter 3 explores the effects produced by a radical simplification of synaptic driving forces. With all synaptic interactions pharmacologically limited to those mediated through the NMDA synapse, spinal cord networks exhibited an extremely regular burst oscillation characterized by a period of 2.9 ± 0.3 s, with mean coefficients of variation of 3.7, 4.7, and 4.9 % for burst rate, burst duration, and inter-burst interval, respectively (16 separate cultures). The reliability of expression of this oscillation suggests that it may represent a fundamental mechanism of importance during periods of NMDA receptor dominated activity, such as embryonic and early postnatal development. NMDA synapse mediated activity produces a precise oscillatory state that allows the study of excitatory-coupled network dynamics, burst mechanisms, emergent network properties, and structure-function relationships.

Embryonic murine neuronal networks cultured on microelectrode arrays were used to quantify acute electrophysiological effects of fluoxetine and ethanol. Spontaneously active frontal cortex cultures showed highly repeatable, dose-dependent sensitivities to both compounds. Cultures began to respond to fluoxetine at 3 µM and were shut off at 10-16 µM. EC50s mean ± S.D. for spike and burst rates were 4.1 ± 1.5 µM and 4.5 ± 1.1 µM (n=14). The fluoxetine inhibition was reversible and without effect on action potential wave shapes. Ethanol showed initial inhibition at 20 mM, with spike and burst rate EC50s at 52.0 ± 17.4 mM and 56.0 ± 17.0 mM (n=15). Ethanol concentrations above 100 -140 mM led to cessation of activity. Although ethanol did not change the shape and amplitude of action potentials, unit specific effects were found. The combined application of ethanol and fluoxetine was additive. Ethanol did not potentiate the effect of fluoxetine.

Murine neuronal networks, derived from embryonic frontal cortex (FC) tissue grown on microelectrode arrays, were used to investigate zinc toxicity at concentrations ranging from 20 to 2000 mM total zinc acetate added to the culture medium. Continual multi-channel recording of spontaneous action potential generation allowed a quantitative analysis of the temporal evolution of network spike activity generation at specific zinc acetate concentrations. Cultures responded with immediate concentration-dependent excitation lasting from 5 to 50 min, consisting of increased spiking and enhanced, coordinated bursting. This was followed by irreversible activity decay. The time to 50% and 90% activity loss was concentration dependent, highly reproducible, and formed linear functions in log-log plots. Network activity loss generally preceded morphological changes. 20% cell swelling was correlated with 50% activity loss. Cultures pretreated with the GABAA receptor antagonists bicuculline (40 mM) and picrotoxin (1 mM) lacked the initial excitation phase. This suggests that zinc-induced excitation may be mediated by interfering with GABA inhibition. Partial network protection was achieved by stopping spontaneous activity with either tetrodotoxin (200 nM) or lidocaine (250 mM). However, recovery was not complete and slow deterioration of network activity continued over 6 hrs. Removal of zinc by early medium changes showed irreversible, catastrophic network failure to develop in a concentration-dependent time window between 50% and 90% activity loss. Investigation of entry routes suggested the L-type but not N-type calcium channels to be the main entry pathway for zinc. Data are presented implicating the chloride channel to be an additional entry route.