A Study of Neuronal Properties, Synaptic Plasticity and Network Interactions Using a Computer Reconstituted Neuronal Network Derived from Fundamental Biophysical Principles
Final rept. Dec 1990-Jun 1992
BAYLOR COLL OF MEDICINE HOUSTON TX DIV OF NEUROSCIENCE
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The primary research goal is to understand the parallel signal processing capabilities of biological neurons, neural networks and their functions in the central nervous system. The research is focused on computational neuroscience and the analysis of the signals encoded by multiple neurons in a network. Two approaches are employed to study the function of the neural processing system theoretical modeling and experimental analysis. Theoretical studies include developing computational models of the central nervous system, neural networks and single neurons to reproduce the operating principles of neural processing. Special time-series statistical techniques spike train analytical methods are developed to analyze the signals encoded in the firing patterns of neurons with dynamical interactions. Experimental studies include in vivo neurophysiological experiments studying the motor control, sensori-motor integration and learning functions by recording the firing patterns of multiple neurons simultaneously from the motor and cerebellar cortices, and in vitro experiments studying neuronal network dynamics in signal processing and synaptic plasticity in learning and memory by recording the firing patterns of cultured neurons grown on a multimicroelectrode plate. It is an attempt to bridge the gap between theories and experiments in neuroscience by testing the hypotheses predicted in the models with specifically designed experiments.
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