Biologically Plausible Computational Neurogenetic Models: Modeling the Interaction Between Genes, Neurons and Neural Networks
Abstract:The paper presents a theory and a new generic computational model of a biologically plausible artificial neuron and artificial neural network (ANN) that can mimic certain brain neuronal ensembles, the dynamics of which is influenced by the dynamics of internal gene regulatory networks (GRN). We call these models "computational neurogenetic models" (CNGM) and this new area of research—Computational Neurogenetics. We are aiming at developing a novel computational modelling paradigm and also at bringing original insights into how genes and their interactions influence the function of brain neural networks in normal and diseased states. Both brain activity and an ANN model can be analyzed using same signal processing techniques and then compared. In the proposed model, FFT and spectral characteristics of the ANN behavior are analyzed and compared with desired activity of the brain, measured as EEG signals. The model will include a large set of biologically plausible parameters and functions related to genes/proteins, spiking neuronal activities, etc., which define the GRN and the corresponding ANN. These parameters will be optimized, based for instance on targeted EEG data, through using evolutionary algorithms. The paper also offers a list of open questions in the field of CNGM. It outlines directions for further research, one of them being nanotechnology where specific models can be developed based on our approach before any medical intervention at a molecular level can be administered to patients suffering of different brain diseases.
Document Type: Research Article
Publication date: December 1, 2005
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- Journal of Computational and Theoretical Nanoscience is an international peer-reviewed journal with a wide-ranging coverage, consolidates research activities in all aspects of computational and theoretical nanoscience into a single reference source. This journal offers scientists and engineers peer-reviewed research papers in all aspects of computational and theoretical nanoscience and nanotechnology in chemistry, physics, materials science, engineering and biology to publish original full papers and timely state-of-the-art reviews and short communications encompassing the fundamental and applied research.
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