ERGODIC CELLULAR AUTOMATON NEURON MODEL FOR A VIRTUAL CLINICAL TRIAL OF NEURAL PROSTHESIS

A novel cellular automaton neuron model and its cellular differentiation method are presented. It is shown that the differentiation method enables the neuron model to reproduce typical nonlinear responses of a given neuron model. Then a virtual clinical trial of neural prosthesis is executed, i.e., a target neuron model in a network composed of biologically plausible differential equation neuron models is replaced with the presented neuron model that is differentiated to reproduce the target neuron model. The presented neuron model is implemented in a field programmable gate array and the virtual clinical trial is validated by experiments. The results show the presented neuron model is much more hardware-efficient compared to a simplified differential equation neuron model

The quantitative single-neuron modeling competition

As large-scale, detailed network modeling projects are flourishing in the field of computational neuroscience, it is more and more important to design single neuron models that not only capture qualitative features of real neurons but are quantitatively accurate in silico representations of those. Recent years have seen substantial effort being put in the development of algorithms for the systematic evaluation and optimization of neuron models with respect to electrophysiological data. It is however difficult to compare these methods because of the lack of appropriate benchmark tests. Here, we describe one such effort of providing the community with a standardized set of tests to quantify the performances of single neuron models. Our effort takes the form of a yearly challenge similar to the ones which have been present in the machine learning community for some time. This paper gives an account of the first two challenges which took place in 2007 and 2008 and discusses future directions. The results of the competition suggest that best performance on data obtained from single or double electrode current or conductance injection is achieved by models that combine features of standard leaky integrate-and-fire models with a second variable reflecting adaptation, refractoriness, or a dynamic threshold

Identifying and Predicting Rat Behavior Using Neural Networks

The hippocampus is known to play a critical role in episodic memory function. Understanding the relation between electrophysiological activity in a rat hippocampus and rat behavior may be helpful in studying pathological diseases that corrupt electrical signaling in the hippocampus, such as Parkinson’s and Alzheimer’s. Additionally, having a method to interpret rat behaviors from neural activity may help in understanding the dynamics of rat neural activity that are associated with certain identified behaviors. In this thesis, neural networks are used as a black-box model to map electrophysiological data, representative of an ensemble of neurons in the hippocampus, to a T-maze, wheel running or open exploration behavior. The velocity and spatial coordinates of the identified behavior are then predicted using the same neurological input data that was used for behavior identification. Results show that a nonlinear autoregressive process with exogenous inputs (NARX) neural network can partially identify between different behaviors and can generally determine the velocity and spatial position attributes of the identified behavior inside and outside of the trained interva

The Role of Glutaminase 1 in HIV-1 Associated Neurocognitive Disorders and in Brain Development

Glutaminase is the enzyme that converts glutamine into glutamate, which serves as a key excitatory neurotransmitter and one of the energy providers for cellular metabolism. Glutamate is essential for proper brain functioning but at excess levels, it is neurotoxic and has a key role in the pathogenesis of various neurodegenerative diseases, including HIV-1 associated neurocognitive disorders (HAND). However, the detailed mechanism of glutamate-mediated neurotoxicity remains unclear. In part I, we identified the regulation of glutaminase 1 (GLS1) in the central nervous system (CNS) of HAND animal models including HIV-Tat transgenic (Tg) mouse and HIVE-SCID mouse, since GLS1 is the dominant isoform of glutaminase in mammalian brains. Interestingly, examinations of both animals revealed an upregulation of GLS1 in correlation with the increase of brain inflammation and cognitive impairment. As our previous data revealed an upregulation of glutaminase C (GAC) in the postmortem brain tissues of patients with HIV dementia by protein analysis, suggesting a critical role of GAC in the instigation of primary dysfunction and subsequent neuronal damage in HAND, thus in part II we hypothesize that GAC dysregulation in brain is sufficient to induce brain inflammation and dementia in relevance to HAND. Using a brain GAC overexpression mouse model (which has the overexpression of GAC confined in the brain), we found that the expressions of the marker for brain inflammation, the glial fibrillary acidic protein (GFAP), were increased in the brains of GAC-overexpression mice, suggesting increased reactive astrogliosis. To study the functional impact of GAC overexpression, we performed Morris Water Maze (MWM) test and Contextual Fear Conditioning (CFC) test to determine the learning and memory of mice. GAC-overexpression mice perfomed poorer in both tests, indicating that overexpressing GAC in mouse brain impaired the learning and memory of the animals. Moreover, pathological and physiologial examinations revealed synaptic damage and increased apoptosis in Nestin-GAC mouse brain. Together, these data suggest that dysregulated GAC has a causal relationship with prolonged inflammation and dementia relevant to HAND. In part III, we evaluated the feasibility of genetically knocking down GLS1 in CNS to treat HAND using human primary neural progenitor cell (NPC) culture. However, we have found that GLS1 is essential for the survival, proliferation and differentiation of human NPC. This suggests that more-advanced genetic methods capable of targeting GLS1 in specific cell types of CNS ought to be developed for the therapeutic purpose. In summary, we report that GLS1 is dysregulated in the brains of HAND murine models in correlation with increased brain inflammation and cognitive impairment. Moreover, overexpressed GAC in mouse brains has a causal relationship to prolonged brain inflammation and dementia of these animals, suggesting a pathologenic role of dysregulated brain GLS1 in relevance to HAND