Computational neurogenetic modeling: integration of spiking neural networks, gene networks, and signal processing techniques

摘要: The paper presents a theory and new generic computational model of biologically plausible artificial neural network (ANN) that can mimic certain brain neuronal ensembles, the dynamics which is influenced by internal gene regulatory networks (GRN). We call these models "computational neurogenetic models" (CNGM) this area research neurogenetics. are aiming at developing novel modeling paradigm also bringing original insights into how genes their interactions influence function in normal diseased states. Both activity an ANN be analyzed using same signal processing techniques then compared. In proposed model, FFT spectral characteristics behavior compared with EEG signal. will include large set parameters functions related to genes/proteins, spiking activities, etc., define GRN corresponding ANN. These optimized, based for instance on targeted data, through evolutionary algorithms. offers list open questions field CNGM. It outlines directions further research.