本文選題：模型 + 神經(jīng)回路��； 參考：《華南理工大學》2016年博士論文

【摘要】：大腦的學習,記憶和認知等功能是由相互作用的神經(jīng)元構(gòu)成的神經(jīng)回路來完成.因此,神經(jīng)回路的理論研究對理解神經(jīng)系統(tǒng)的功能有著至關(guān)重要的作用.本論文對局部生物神經(jīng)回路,動物海兔的尾部收縮反射回路和額葉視區(qū)決策回路進行了動力學分析以及仿真模擬,具體工作如下第一章是緒論,主要介紹本論文的研究背景,神經(jīng)回路的動力學現(xiàn)象和模型仿真的研究框架,并提出本文的主要課題和研究內(nèi)容.第二章介紹模擬神經(jīng)回路所需的研究基礎(chǔ)和研究背景.這些內(nèi)容主要包括神經(jīng)元的解剖結(jié)構(gòu)和數(shù)學模型,離子通道及其數(shù)學模型,神經(jīng)元的興奮性,神經(jīng)元間的突觸連接以及它們的數(shù)學模型,突觸可塑性和神經(jīng)回路的拓撲結(jié)構(gòu)以及一些經(jīng)典的神經(jīng)回路模型和神經(jīng)回路研究的最新進展.神經(jīng)元模型包括Hodgkin-Huxley模型,Connor-Stevens模型,Morris-Lecar模型和呼吸神經(jīng)元模型四個基于電導的模型以及整合發(fā)放模型,還有Rall電纜模型及其離散化后得到的多房室模型.論文用到的突觸類型有電突觸和化學突觸.第三章研究生物局部神經(jīng)回路,主要討論耦合呼吸神經(jīng)元的相位同步.論文首先用電突觸將兩個呼吸神經(jīng)元連接起來,建立了一個耦合呼吸神經(jīng)元模型.通過對比單個神經(jīng)元模型和耦合神經(jīng)元模型的門控變量的極大值分岔圖,發(fā)現(xiàn)耦合神經(jīng)元模型表現(xiàn)出更復(fù)雜的發(fā)放變化模式.特別是改變耦合強度和膜電容后,耦合系統(tǒng)出現(xiàn)不同的相位同步狀態(tài)以及它們之間的轉(zhuǎn)遷.更進一步,在耦合強度和膜電容的二維平面上,我們給出了同步狀態(tài)的分布情況,并總結(jié)了同步狀態(tài)轉(zhuǎn)遷的規(guī)律.第四章研究動物神經(jīng)回路,主要通過對神經(jīng)回路的仿真研究海兔尾部收縮反射現(xiàn)象.先得到感覺神經(jīng)元的波形特征,然后通過改變刺激強度和受刺激感覺神經(jīng)元的個數(shù)得出反射回路的典型規(guī)律.此外,反射神經(jīng)回路與肌纖維模型連接后得到新的模型,并成功模擬了神經(jīng)信號與肌纖維間的興奮-收縮耦聯(lián).最后,論文還探討了突觸可塑性對停止刺激后反射回路-肌纖維連接模型的長持續(xù)反應(yīng)時間的影響.這些模型結(jié)果揭示海兔尾部收縮反射的特性.第五章研究腦決策的動力學機制,基于一個改進的額葉視區(qū)模型,對三類腦決策任務(wù)進行仿真研究.首先,在一個額葉視區(qū)模型中加入了神經(jīng)元群體的方向偏好性,規(guī)則控制模塊和基于獎勵的可塑性突觸,使其變?yōu)橐粋�基于學習的額葉視區(qū)模型.修改后的模型經(jīng)過訓練后成功模擬了三個腦認知決策任務(wù)：反向眼跳任務(wù),no-go任務(wù)和關(guān)聯(lián)任務(wù).訓練后的模型表現(xiàn)出一些與猴子實驗一致的性質(zhì),如反向眼跳的反應(yīng)時間分布的延遲,停止信號取消反射性眼跳的機制和半極大選擇性延遲的變化.此外,對訓練后的模型進行切換任務(wù)訓練,即在沒有提示的情況下,讓回路模型在兩個任務(wù)中進行切換并重新訓練,結(jié)果表明模型經(jīng)過一個重新學習的過程可以在正向眼跳任務(wù)和反向眼跳任務(wù)間以及不同的提示-眼跳關(guān)聯(lián)間切換.這些額葉視區(qū)回路的模型結(jié)果揭示腦決策任務(wù)的內(nèi)在決策過程和認知規(guī)律,為理解大腦的認知功能提供理論基礎(chǔ).
[Abstract]:The learning, memory, and cognition of the brain are accomplished by a neural circuit composed of interacting neurons. Therefore, the theoretical study of the neural circuits plays a vital role in understanding the function of the nervous system. This paper is a part of the local neural circuit, the tail contraction reflex loop of the animal sea hare and the decision loop of the frontal lobes. The first chapter is the introduction, which mainly introduces the research background of this paper, the dynamic phenomena of neural circuits and the framework of model simulation, and puts forward the main topics and research contents of this paper. The second chapter introduces the research foundation and research background of the simulated divine loop. The main contents include the anatomical structure and mathematical models of neurons, ion channels and their mathematical models, excitatory properties of neurons, synaptic connections among neurons and their mathematical models, synaptic plasticity and topological structures of neural circuits, and the latest advances in some classical neural circuits and neural circuits. The Hodgkin-Huxley model, the Connor-Stevens model, the Morris-Lecar model and the respiratory neuron model are four based on the electrical conductivity model and the integrated distribution model, and the Rall cable model and the multiple atrioventricular model after the discretization. The synaptic types are used as the electrical synapse and the chemical synapse. The third chapter studies the biological local nerve. In this paper, the phase synchronization of coupled respiratory neurons is mainly discussed. Firstly, two respiratory neurons are connected by electric synapses, and a coupled respiratory neuron model is established. By comparing the maximum bifurcation diagram of the single neuron model and the gated variable of the coupled neuron model, it is found that the Coupled Neuron Model is more complex. In particular, after changing the coupling strength and membrane capacitance, the coupling systems have different phase synchronization states and their transition between them. Further, on the two dimensional plane of the coupling strength and membrane capacitance, we give the distribution of the synchronous state and the law of the transition of the synchronous state. The fourth chapter studies the movement. The neural circuit is used to study the contractile reflex in the tail of the rabbit by simulation of the neural circuit. The characteristics of the waveform of the sensory neurons are obtained first, and then the typical law of the reflex loop is obtained by changing the intensity of stimulation and the number of stimulated sensory neurons. In addition, a new model is obtained after the reflex neural circuit is connected with the muscle fiber model. Finally, the effect of synaptic plasticity on the long sustained response time of the muscle fiber connection model after the stop stimulation is also discussed. The results reveal the specificity of the contractile reflex in the tail of the rabbit. The fifth chapter studies the dynamic mechanism of brain decision-making. In a modified frontal visual area model, three types of brain decision-making tasks are simulated. First, the orientation preference of the neuron group is added to a frontal visual area model, the rule control module and the reward based plasticity synapse become a learning based frontal visual area model. After training, the modified model is trained. Three brain cognitive decision-making tasks were successfully simulated: reverse saccade task, no-go task, and associated task. The model after training showed some properties consistent with monkey experiment, such as the delay of reaction time distribution of reverse saccade, the mechanism of stopping the reflex saccade and the change of semi maximum selective delay. The model is trained for switching tasks, that is, to switch and retrain the loop model in two tasks without prompting. The results show that the model can switch between the forward saccade task and the reverse saccade task and the different hint - saccade association through a relearning process. The results of the model reveal the internal decision-making process and cognitive rules of the brain decision-making task, and provide a theoretical basis for understanding the cognitive function of the brain.
【學位授予單位】：華南理工大學
【學位級別】：博士
【學位授予年份】：2016
【分類號】：B842

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