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This research focuses on the nanoscopic investigation of the three-dimensional surface morphology of the neural growth cones from the snail Helisoma trivolvis, and InN and InGaN semiconductor material systems using Atomic Force Microscopy (AFM). In the analysis of the growth cones, the results obtained from AFM experiments have been used to construct a 3D architecture model for filopodia. The filopodia from B5 and B19 neurons have exhibited different tapering mechanisms. The volumetric analysis has been used to estimate free Ca2+ concentration in the filopodium. The Phase Contrast Microscopy (PCM) images of the growth cones have been corrected to thickness provided by AFM in order to analyze the spatial refractive index variations in the growth cone. AFM experiments have been carried out on InN and InGaN epilayers. Ternary InGaN alloys are promising for device applications tunable from ultraviolet (Eg[GaN]=3.4 eV) to near-infrared (Eg [InN]=0.7 eV). The real-time optical characteristics and ex-situ material properties of InGaN epilayers have been analyzed and compared to the surface morphological properties in order to investigate the relation between the growth conditions and overall physical properties. The effects of composition, group V/III molar ratio and temperature on the InGaN material characteristics have been studied and the growth of high quality indium-rich InGaN epilayers are demonstrated.

In a world dominated by temporal order, memory capable of processing, encoding and subsequently recalling ordered information is very important. Over the decades this memory, known as serial memory, has been extensively studied, and its effects are well known. Many models have also been developed, and while these models are able to reproduce the behavioural effects observed in human recall studies, they are not always implementable in a biologically plausible manner. This thesis presents the Ordinal Serial Encoding model, a model inspired by biology and designed with a broader view of general cognitive architectures in mind. This model has the advantage of simplicity, and we show how neuro-plausibility can be achieved by employing the principles of the Neural Engineering Framework in the model’s design. Additionally, we demonstrate that not only is the model able to closely mirror human performance in various recall tasks, but the behaviour of the model is itself a consequence of the underlying neural architecture.

Several decades of physiology, imaging and psychophysics research on attention has generated an enormous amount of data describing myriad forms of attentional effects. A similar breadth of theoretical models have been proposed that attempt to explain these effects in varying amounts of detail. However, there remains a need for neurally detailed mechanistic models of attention that connect more directly with various kinds of experimental data -- behavioural, psychophysical, neurophysiological, and neuroanatomical -- and that provide experimentally testable predictions. Research has been conducted that aims to identify neurally consistent principles that underlie selective attentional processing in cortex. The research specifically focuses on describing the functional mechanisms of attentional routing in a large-scale hierarchical model, and demonstrating the biological plausibility of the model by presenting a spiking neuron implementation that can account for a variety of attentional effects. The thesis begins by discussing several significant physiological effects of attention, and prominent brain areas involved in selective attention, which provide strong constraints for developing a model of attentional processing in cortex. Several prominent models of attention are then discussed, from which a set of common limitations in existing models is assembled that need to be addressed by the proposed model. One central limitation is that, for many existing models, it remains to be demonstrated that their computations can be plausibly performed in spiking neurons. Further, few models address attentional effects for more than a single neuron or single cortical area. And finally, few are able to account for different forms of attentional modulation in a single detailed model. These and other limitations are addressed by the Attentional Routing Circuit (ARC) proposed in this thesis. The presentation of the ARC begins with the proposal of a high-level mathematical model for selective routing in the visual hierarchy. The mathematical model is used to demonstrate that the suggested mechanisms allow for scale- and position-invariant representations of attended stimuli to be formed, and provides a functional context for interpreting detailed physiological effects. To evaluate the model's biological plausibility, the Neural Engineering Framework (NEF) is used to implement the ARC as a detailed spiking neuron model. Simulation results are then presented which demonstrate that selective routing can be performed efficiently in spiking neurons in a way that is consistent with the mathematical model. The neural circuitry for computing and applying attentional control signals in the ARC is then mapped on to neural populations in specific cortical laminae using known anatomical interlaminar and interareal connections to support the plausibility of its cortical implementation. The model is then tested for its ability to account for several forms of attentional modulation that have been reported in neurophysiological experiments. Three experiments of attention in macaque are simulated using the ARC, and for each of these experiments, the model is shown to be quantitatively consistent with measured data. Specifically, a study by Womelsdorf et al. (2008) demonstrates that spatial shifts of attention result in a shifting and shrinking of receptive fields depending on the target's position. An experiment by Treue and Martinez-Trujllo (1999) reports that attentional shifts between receptive field stimuli produce a multiplicative scaling of responses, but do not affect the neural tuning sensitivity. Finally, a study by Lee and Maunsell (2010) demonstrates that attentional shifts result in a multiplicative scaling of neural contrast-response functions that is consistent with a response-gain effect. The model accounts for each of these experimentally observed attentional effects using a single mechanism for selectively processing attended stimuli. In conclusion, it is suggested that the ARC is distinguished from previous models by providing a unifying interpretation of attentional effects at the level of single cells, neural populations, cortical areas, and over the bulk of the visual hierarchy. As well, there are several advantages of the ARC over previous models, including: (1) scalability to larger implementations without affecting the model's principles; (2) a significant increase in biological plausibility; (3) the ability to account for experimental results at multiple levels of analysis; (4) a detailed description of the model's anatomical substrate; (5) the ability to perform selective routing while preserving biological detail; and (6) generating a variety of experimentally testable predictions.

<p>The specification of a single axon and multiple dendrites is the first observable event during neuronal morphogenesis and such structural specialization underlies neural connectivity and nervous system function. Numerous intracellular signaling components that are required for axon specification have been described but how such signaling paradigms are initiated by extracellular factor(s) within the embryonic milieu is poorly understood. Here, I describe how transforming growth factor-&beta; (TGF-&beta;), an embryonic morphogen that directs structural plasticity and growth in various cell types, initiates signaling pathways both in vivo and in vitro to fate naïve neurites into axons. Using conditional knockout strategies, I found that cortical neurons lacking the type II TGF-&beta; receptor (T&beta;R2) fail to initiate axons during development, and interestingly, fail to engage radial migration. In cultured neurons, exogenous TGF-&beta; is sufficient to direct the rapid growth and differentiation of an axon and genetic enhancement of receptor activity promotes the formation of multiple axons. The cellular polarization of receptor activity occurs through the interaction of the type-I TGF-&beta; receptor with Par6, a component of the axon-specifying Par3/Par6 polarity complex. Receptor distribution is restricted to axons, and downstream signaling events required for axon specification are triggered when Par6 is phosphorylated by T&beta;R2. Together, these results indicate that TGF-&beta; is the extrinsic cue for neuronal polarity in vivo and directs neuronal polarity by controlling Par6 activity and cellular migration during axon generation.</p> / Dissertation

<p>Development requires a delicate balance of proliferation and differentiation. Too little proliferation can result in dysfunctional tissues, while prolonged or heightened proliferation can result in tumor formation. This is clearly seen with the granule neuron precursors (GNPs) of the cerebellum. Too little proliferation of these cells during development results in ataxia, whereas too much proliferation results in the cerebellar tumor medulloblastoma. While these cells are known to proliferate in response to Shh, it is not clear what controls the differentiation of these cells in vivo.</p><p> Previous work from our lab has identified basic fibroblast growth factor (bFGF) as a candidate differentiation factor for these cells. In this thesis, I characterize some of the cellular and molecular mechanisms involved in FGF-mediated inhibition (FMI) of Shh-induced GNP proliferation. In addition, I employ FGFR knockouts and a bFGF gain-of-function mouse to determine whether FGF signaling is necessary and/or sufficient for differentiation of GNPs during cerebellar development. Finally, the question of whether bFGF can be effective as a therapeutic agent for in vivo tumor treatment is tested in a transplant model.</p><p> These experiments indicate that FGF signaling is neither necessary nor sufficient for GNP differentiation during cerebellar development. However, transplanted tumors are potently inhibited by bFGF treatment. Furthermore, FMI is shown to occur around the level of Gli2 processing in the Shh pathway, implying that such a treatment has promise to be widely effective in treatment of Shh-dependent medulloblastomas.</p> / Dissertation

This thesis presents a neuron emulator and headstage circuit for patch clamp setups and provides simulation, measurement and verification results. The circuit implemented on a printed circuit board (PCB) is battery powered and portable. The emulator provides both passive (resting potential) and active (action potential) electrical properties of a live neuron as seen from a single electrode by using the headstage circuit. It can be used to test electrophysiological equipment such as current-clamp, voltage-clamp or patch-clamp amplifiers. The action potentials (APs) are generated with a voltage-dependent frequency controlled by a microcontroller implementing a firing range from -60 mV to -30 mV and firing frequency from 1 Hz to10 Hz. The charge released by firing the neuron is initially stored on a 110 pC capacitor. Compared to directly using a current or voltage source, this design results in a more realistic simulation of the APs generated by ionic currents in a live neuron. The measured results from a prototype demonstrate that the neuron emulator meets the design specifications and it is capable of performing voltage clamp and rate responsive current clamp functionality. Measured results using a commercial clamp amplifier are provided to confirm the emulator operation in a practical recording environment.

The study of neurons is of fundamental importance in biology and medicine. Neurons are the most basic unit of information processing in the nervous system of humans and all other vertebrates and in complex invertebrates. In addition, networks of neurons (the human brain) are the most sophisticated computational devices known, and the study of neurons individually and working in concert is seen as a step toward understanding consciousness and cognition. In the 1950's Hodgkin and Huxley developed a system of nonlinear ordinary differential equations to describe the behavior of a neuron found in the squid. Equations of this form have since been used to model the behavior of a multitude of neurons across a broad spectrum of species. Hodgkin-Huxley type neuron models helped lay the foundation for computational neuroscience, and they remain widely used in the study of neuron behavior almost sixty years after their development. Hodgkin-Huxley type models accept a set of parameters as input and generate data describing the electrical activity of the neuron as a function of time. We develop inversion algorithms to predict a set of input parameter values from the voltage trace data generated by the model. We test our algorithm on data from the Hodgkin-Huxley equations, and we extend the algorithm to solve the inverse problem associated with a more complex Hodgkin-Huxley type model for a lobster stomatogastric neuron. We find strong empirical evidence that the algorithms produce parameter values that generate a good fit to the target voltage trace, and we prove that under certain conditions the inversion algorithm for the Hodgkin-Huxley equations converges to a perfect match. To our knowledge this is the first parameter optimization procedure for which convergence has been shown theoretically. Understanding the relationship between the parameters of a neuron model and its output has implications for designing effective neuron models and for explaining the mechanisms by which neurons regulate their behavior. Inversion algorithms for Hodgkin-Huxley type neuron models are an important theoretical and practical step toward understanding the relationship between model parameters and model behavior, and toward the larger problem of inferring neuronal parameters from behavior observed experimentally.

This piece makes the claim that rhetoric is first philosophy--before philosophy, epistemology, ontology, or any other field--or that rhetoric is, at the least, on equal footing as these fields because: empathy--and thusly the impulse for communication--is physiologically hardwired into humans; special distinctions between human and animal are largely artificial constructions, as is evidenced by neurosciences; "hard" science, in the form of neurosciences, is providing entrance points & opportunities for rhetoric to raise its status within the academy; and said neurosciences, in addition to empathy studies, have shown strong evidence supporting linguistic and evolutionary links between humans and other species, thereby supporting a "preoriginary rhetoricity," in Diane Davis's terms. Davis's Inessential Solidarity... serves as a stepping stone for this piece in the sense that the ethical relation as derived from the work of Levinas, originary rhetoricity, and rhetorics of the saying or of the address require the utmost attention for rhetorical scholars right now. I show how neuroscience research might help Davis's project--in which she is far from alone--move forward by providing connections between rhetoric and current neuroscience work.

Electrical stimulation of tissues induces cell alignment, directed migration, extended processes, differentiation, and proliferation, but the mechanisms involved remain largely unknown. To reveal effects of electric fields (EF) through the media on cell behavior, voltage (7.45 – 22 V), current density (36 – 106 mA/cm2), duration (2 – 24 hrs), and alternating currents (AC, 2 – 1000 Hz) were varied independently when exposed to cell cultures. It was determined that current density and duration are the primary attribute Schwann cells respond to when an EF is applied through the media. This implies that the number of charges moving across the cell surface may play a key role in EF-induced changes in cell behavior. Identical conditions were used to stimulate cells grown on the surface of a conductive substrate to examine if a scaffold can provide structural and EF cues. The effects of an EF through the substrate were examined by placing a protein gel on the surface during stimulation and observing the morphology of subsequent cell cultures and the physical topology of the gel. EFs were shown to create Ca2+ redistribution across gels and subtle changes in collagen I fibril banding. Stimulated gels were able to induce perpendicular Schwann cell alignment on newly seeded cultures days after initial EF exposure, and the cell response decreased when seeded at longer times, indicating the effects of EF on the matrix environment has a relaxation time. These findings were then integrated into a biodegradable, electrically conductive polypyrrole-poly-ε-caprolactone polymer developed by collaborators. Dorsal root ganglia placed in matrix gels on top of conducting polymer exhibited significantly longer axons when stimulated with DC and AC signals. The overall results demonstrate that EFs have a significant effect on the extracellular environment. The broad implication of this data grants researchers with the ability to physically and metabolically control cell behavior with EFs, including improved wound healing or reduced cancer metastasis. / text