Research On Models Of Key Parts Of Olfactory Neural Pathway

The research on the olfactory neural pathway is the basis of olfactory research,which is of great significance in many aspects of brain science.The dissertation starts with the exploration of the olfactory neural pathway and conducts model research on key parts.Firstly,the dissertation outlines the neural conduction mechanism of the olfactory neural pathway.This neural pathway is divided into the front part(olfactory epithelium,olfactory bulb,anterior olfactory nucleus and piriform cortex),the middle part(amygdala and entorhinal cortex),and the rear part(hippocampus and subiculum).The projection process from the olfactory bulb and the piriform cortex to the entorhinal cortex is unknow,so it is assumed that their neurons are connected one-to-one or randomly.Secondly,based on the improvement of KIII model,a front-part model of the olfactory neural pathway was proposed.The small-world network theory is used to analyze the changes in the average path length and clustering coefficient of the KIII model and the front-part model when the number of channels gradually increases from 5 to 100.The analysis results show that when the number is greater than 16,compared with the KIII model,the front-part model has a smaller average path length and a larger clustering coefficient.In addition,the KIII model is analyzed based on the idea of deep learning.The similarity between the KIII model and the deep learning model is analyzed from three aspects of the model structure,noise tolerance and connections between neurons.After suitably segmented,The EEG signals are directly input to the KIII model and deep learning model for recognition,without the feature extraction.The experimental results show that the KIII model has the ability to automatically extract features in EEG signals,and the different segmenting methods for EEG signals affect the recognition results.Therefore,considering the similarity between the KIII model and the deep learning model,it is a natural and promising research idea to optimize the performance of the KIII model based on the idea of deep learning in order to achieve a good balance between high bionics and good performance.Thirdly,based on the existing dentate gyrus model under pathological conditions,a rear-part model of the olfactory neural pathway was proposed.The membrane potential of typical neurons in the rear-part model were obtained using the NEURON simulation platform.The simulation results show that the neurons in the rear-part model have the same stimulusresponse characteristics as real neurons.In addition,a middle-part model with the entorhinal cortex as the core is constructed based on the neural masses theory,and a bionic model of the olfactory neural pathway is constructed based on the hypothetical connection form the olfactory bulb and the piriform cortex to the entorhinal cortex.