by Law Hing Man, Hudson. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1990. / Bibliography: leaves 109-112. / Acknowledgements / Abstract / Chapter Chapter I. --- Introduction --- p.1 / Chapter 1.1 --- Overview of the thesis --- p.2 / Chapter 1.2 --- Organization of the thesis --- p.7 / Chapter Chapter II. --- Artificial Neural Networks --- p.9 / Chapter 2.1 --- Architectures of Artificial Neural Networks --- p.10 / Chapter 2.1.1 --- Neuron Models --- p.10 / Chapter 2.1.2 --- Network Models --- p.12 / Chapter 2.2 --- Learning algorithms --- p.13 / Chapter Chapter III. --- From Logic Neuron to Non-Overlapped Trees --- p.15 / Chapter 3.1 --- Deterministic Logic Neuron (DLN) --- p.15 / Chapter 3.2 --- Probabilistic Logic Neuron (PLN) --- p.20 / Chapter 3.2.1 --- Well-behaved learning of orthogonal patterns in PLN network --- p.23 / Chapter 3.2.2 --- Well-behaved learning algorithm for non-orthogonal patterns --- p.23 / Chapter 3.3 --- Non-Overlapped Trees --- p.28 / Chapter 3.3.1 --- Homogeneous learning algorithm --- p.30 / Chapter 3.3.2 --- An external comparator --- p.34 / Chapter 3.3.3 --- Problems solved by NOTPLN --- p.35 / Chapter Chapter IV. --- Properties of NOTPLN --- p.37 / Chapter 4.1 --- Noise Insensitivity --- p.37 / Chapter 4.1.1 --- Noise insensitivity with one bit noise --- p.38 / Chapter 4.1.2 --- Noise insensitivity under different noise distributions --- p.40 / Chapter 4.2 --- Functionality --- p.46 / Chapter 4.3 --- Capacity --- p.49 / Chapter 4.4 --- Distributed representation --- p.50 / Chapter 4.5 --- Generalization --- p.51 / Chapter 4.5.1 --- Text-to-Phoneme Problem --- p.52 / Chapter 4.5.2 --- Automobile Learning --- p.53 / Chapter Chapter V. --- Learning Algorithms --- p.54 / Chapter 5.1 --- Presentation methods --- p.54 / Chapter 5.2 --- Learning algorithms --- p.56 / Chapter 5.2.1 --- Heterogeneous algorithm --- p.57 / Chapter 5.2.2 --- Conflict reduction agorithm --- p.61 / Chapter 5.3 --- Side effects of learning algorithms --- p.68 / Chapter 5.3.1 --- Existence of Side Effects --- p.68 / Chapter 5.3.2 --- Removal of Side Effects --- p.69 / Chapter Chapter VI. --- Practical Considerations --- p.71 / Chapter 6.1 --- Input size constraint --- p.71 / Chapter 6.2 --- Limitations of functionality --- p.72 / Chapter 6.3 --- Thermometer code --- p.72 / Chapter 6.4 --- Output definitions --- p.73 / Chapter 6.5 --- More trees for one bit --- p.74 / Chapter 6.6 --- Repeated recall --- p.75 / Chapter Chapter VII. --- Implementation and Simulations --- p.78 / Chapter 7.1 --- Implementation --- p.78 / Chapter 7.2 --- Simulations --- p.81 / Chapter 7.2.1 --- Parity learning --- p.81 / Chapter 7.2.2 --- Performance of learning algorithms under different hamming distances --- p.82 / Chapter 7.2.3 --- Performance of learning algorithms with different output size --- p.83 / Chapter 7.2.4 --- Numerals recognition and noise insensitivity --- p.84 / Chapter 7.2.5 --- Automobile learning and generalization --- p.86 / Chapter Chapter VIII. --- Spoken Numerals Recognition System based on NOTPLN --- p.89 / Chapter 8.1 --- End-point detection --- p.90 / Chapter 8.2 --- Linear Predictive Analysis --- p.91 / Chapter 8.3 --- Formant Frequency Extraction --- p.93 / Chapter 8.4 --- Coding --- p.95 / Chapter 8.5 --- Results and discussion --- p.96 / Chapter Chapter IX. --- Concluding Remarks --- p.97 / Chapter 9.1 --- Revisit of the contributions of the thesis --- p.97 / Chapter 9.2 --- Further researches --- p.99 / Chapter Appendix A --- Equation for calculating the probability of random selection --- p.102 / Chapter Appendix B --- Training sets with different hamming distances --- p.103 / Chapter Appendix C --- Set of numerals with their associated binary values --- p.107 / References --- p.109

How individual neurons in a nervous system give rise to complex function, behavior and consciousness in higher animals has been studied for over a century, yet scientist have only begun to understand how brains work at the molecular level. This level of study is made possible through technological advances, especially transgenic analysis of the cells that make up nervous systems. To date, no other system has been used as extensively as the nematode Caenorhabditis elegans in this pursuit. With just 302 neurons in the adult hermaphrodite, extensive neuronal maps at the anatomical, functional, and molecular level have been built over the past 30 years. One way to understand how nervous systems develop and differentiate into diverse cell types such as sensory or motor neurons that make higher level behaviors possible, is to unravel the underlying gene regulatory programs that control development. Throughout my PhD I investigated neuron type identity regulators to understand how nervous system diversity is generated and maintained using several bioinformatic approaches. First, I developed a software program and community resource tool, TargetOrtho, useful for identifying novel regulatory targets of transcription factors such as the cell type selector proteins termed terminal selectors evidenced to control terminal cell identity of 74 of the 118 neuron types in C. elegans. Analysis of terminal selector candidate target genes led to the further discovery that predicted target genes with cis-regulatory binding sites are enriched for neuron type specific genes suggesting an overarching theme of direct regulation by terminal selectors to specify cell type. Using this knowledge, I make predictions for novel regulators of neuronal identity to further elucidate how the C. elegans nervous system diversifies into 118 neuron types.

No description available.

The Rbfox proteins are a family of splicing regulators in post-mitotic neurons, predicted to be required for control of hundreds of alternative exons in neuronal development. However, their contribution to the cellular processes in developing and adult nervous system remains unclear and few candidate target exons were experimentally confirmed due to functional redundancy of the three Rbfox proteins. In this thesis, I combined CRISPR/Cas9 genome engineering with in vitro differentiation of embryonic stem cells into spinal motor neurons to unravel the Rbfox regulatory network and to study the functional importance of Rbfox-dependent splicing regulation for neuronal maturation. Global analysis revealed that neurons lacking Rbfox proteins exhibit developmentally immature splicing profile but little change in the gene expression profile. Integrative modeling based on splicing changes in Rbfox triple knockout (Rbfox tKO) neurons and HITS-CLIP Rbfox binding mapping identified 547 cassette exons directly regulated by Rbfox proteins in maturing neurons. Strikingly, many transcripts encoding structural and functional components of axon initial segment (AIS), nodes of Ranver (NoR) and synapses undergo Rbfox-dependent regulation. I focused on the AIS whose assembly, which occurs during the early stages of neuronal maturation, is poorly understood. I found that the AIS of Rbfox tKO neurons is perturbed and contains disorganized ankyrin G, as revealed by super-resolution microscopy. This is in part due to an aberrant splicing of ankyrin G, resulting in destabilization of its interaction with βII- and βIV-spectrin. Thus, Rbfox factors play a crucial role in regulating a neurodevelopmental splicing program underlying structural and functional maturation of post-mitotic neurons. These data highlight the importance of alternative splicing in neurodevelopment and provide a novel link between alternative splicing regulation and AIS establishment.

The formation of dendritic arbors is necessary for the proper establishment of neuronal circuits. The Drosophila transcription factor Spineless has been shown to play an important role in the control of dendritic morphogenesis, although the pathways through which it functions are not completely understood. Here, we show genetic evidence that Spineless interacts with the actin/microtubule cross linking protein Shortstop to control the dendrite arbor development of the dendritic arborization (da) sensory neurons. In addition, we have discovered a novel function for spineless as we show that spineless mutant larvae exhibit an increased sensitivity to specific odorants in the absence of morphological defects of the chemosensory organs. These data show that spineless acts in multiple cell-specific contexts to control the diversification of sensory neuron morphology and function.

Thesis (Ph.D.) -- University of Texas at Dallas, 2006. / Includes vita. Includes bibliographical references (leaves 81-94)

Thesis (Ph. D.)--University of Delaware, 2006. / Principal faculty advisor: Thomas P. Beebe, Jr., Dept. of Chemistry & Biochemistry. Includes bibliographical references.

Thesis (M.Sc.)--York University, 2004. Graduate Programme in Kinesiology and Health Science. / Typescript. Includes bibliographical references. Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL:http://gateway.proquest.com/openurl?url%5Fver=Z39.88-2004&res%5Fdat=xri:pqdiss&rft%5Fval%5Ffmt=info:ofi/fmt:kev:mtx:dissertation&rft%5Fdat=xri:pqdiss:MQ99279

Thesis (M.Med.Sc.)--University of Hong Kong, 2009. / Includes bibliographical references (p. 79-86).

Thesis (Ph. D.)--Rutgers University, 2008. / "Graduate Program in Microfluidics." Includes bibliographical references (p. 115-122).