One of the current problems at the interface between neuroscience, biophysics, and computational modeling is the reverse-engineering and reproduction of Caenorhabditis elegans using computer simulation. The aim of our research was to develop the computational models and techniques for solving this problem while participating in the international open science OpenWorm Project. We have suggested models of a typical C. elegans neuron and a pharyngeal muscle cell, which were constructed and optimized using the NEURON simulation environment. The available experimental data about EGL-19 and EXP-2 ion channels allowed the model of a muscle to reproduce the action potential time profile correctly. Also, the model of a neuron reproduces quite accurately the mechanism of neural signal transmission based on passive propagation. We believe our models to be promising for better representing the specifics of various nervous and muscular cell classes when adding the corresponding ion channel models. Moreover, they can be used to construct the networks of such elements.
Abstract. This article describes system on a chip development for high speed video recording purposes. Current research was started due to difficulties in selection of FPGAs and CPUs which include wide bandwidth, high speed and high number of multipliers for real time signal analysis implementation. Current trend of high density silicon device integration will result soon in a hybrid sensor-controller-memory circuit packed in a single chip. This research was the first step in a series of experiments in manufacturing of hybrid devices. The current task is high level syntheses of high speed logic and CPU core in an FPGA. The work resulted in FPGA-based prototype implementation and examination.
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