本文關(guān)鍵詞：神經(jīng)元與神經(jīng)元回路的模型分析　出處：《華南理工大學》2011年碩士論文　論文類型：學位論文

  更多相關(guān)文章： 神經(jīng)元 神經(jīng)元回路 電位發(fā)放 分岔 網(wǎng)絡模型

【摘要】：神經(jīng)回路是大腦中普遍存在的結(jié)構(gòu),也是腦信息處理的主要功能單元,而神經(jīng)元則是組成神經(jīng)回路的基本單元,是神經(jīng)信息處理的最小載體.在本文中,我們采用由小到大、層層遞進的方式,系統(tǒng)地分析了神經(jīng)元單房室模型、兩房室模型、多房室模型、電纜模型、神經(jīng)元模型中ISI倍周期分岔的數(shù)學機理及閘門控制環(huán)路中神經(jīng)纖維的活動特性和信息編碼機制,并在此基礎上,通過建立與實際結(jié)構(gòu)相吻合的嗅球神經(jīng)回路、小腦皮層神經(jīng)回路、海馬神經(jīng)回路、視網(wǎng)膜神經(jīng)回路及基底神經(jīng)節(jié)神經(jīng)回路,來模擬了這些回路對神經(jīng)信號的處理和加工,考察了神經(jīng)信息經(jīng)這些回路整合后的編碼特性,最后對大腦內(nèi)其他幾種重要的神經(jīng)回路也做了簡要的介紹,具體結(jié)果有: 1、單房室神經(jīng)元模型:主要是通過計算機模擬的手段,考察了CA1錐體神經(jīng)元所具有的豐富的發(fā)放模式,分析了隨著某些電生理參數(shù)的改變,這些發(fā)放模式之間的轉(zhuǎn)移,發(fā)現(xiàn)了幾種典型的非線性動力學分岔現(xiàn)象,如:倍周期分岔、加周期分岔等,進一步理 解了CA1錐體神經(jīng)元的信息編碼特性. 2、兩房室神經(jīng)元模型:首先,對皮層錐體神經(jīng)元兩房室模型中所固有的幾種離子通道進行了考察,分析了離子通道電導系數(shù)和離子平衡電位的擾動所引起的皮層錐體神經(jīng)元多樣性的發(fā)放模式及周期性的分岔現(xiàn)象.其次,鑒于兩房室模型中胞體和樹突在形態(tài)和功能上的區(qū)別,我們分析了兩房室中膜電容和泄漏電導單獨改變和同時改變對皮層錐體神經(jīng)元活動特性的影響,進一步理解了神經(jīng)元胞體和樹突在信息編碼上的差異.再次,考察了內(nèi)部時滯和外部溫度所帶來的皮層錐體神經(jīng)元電位發(fā)放特性上的變化.最后,研究了另一種可產(chǎn)生Ghostbursting的兩房室神經(jīng)元模型,并總結(jié)了一般性的兩房室神經(jīng)元模型中所具有的豐富的動力學分岔現(xiàn)象. 3、多房室神經(jīng)元模型:主要是通過NEURON軟件構(gòu)造了三種神經(jīng)元的多房室模型,其中有:嗅球僧帽細胞、小腦皮層浦肯野細胞和海馬錐體細胞,利用發(fā)放頻率和峰峰間距(ISI)圖,比較了三種神經(jīng)元電位發(fā)放特性的不同以及它們在各自神經(jīng)回路中信息處理作用上的差異. 4、電纜模型:以神經(jīng)元的整段樹突為基礎,根據(jù)Hodgkin-Huxley離子通道模型和Rall一維電纜模型,建立了三維空間上的神經(jīng)元樹突電纜模型,對應得到整段樹突的空間信號傳遞理論.數(shù)值結(jié)果首次揭示了樹突內(nèi)神經(jīng)信號的空間傳遞過程和規(guī)律. 5、ISI倍周期分岔的數(shù)學表達:針對神經(jīng)元HH化模型的構(gòu)造特點以及神經(jīng)元動作電位的軌跡,通過積分和微分兩種手段,對峰峰間距(ISI)的數(shù)學表達式進行了推導,并將其運用到實際的神經(jīng)元模型中,發(fā)現(xiàn)了大量的倍周期分岔現(xiàn)象,通過與傳統(tǒng)LOGISTIC映射引入的倍周期分岔對比,闡述了我們提出的ISI倍周期表達式的新穎之處. 6、閘門控制回路:在本節(jié),我們通過考察具體的神經(jīng)元回路--閘門控制回路,分析了回路中三種不同傳遞疼痛的神經(jīng)纖維在傳遞速度、承載疼痛類型上的差異,并研究了不同疼痛刺激類型所造成的回路傳出神經(jīng)元的反應. 7、嗅球神經(jīng)回路:首先,通過參考嗅球的解剖結(jié)構(gòu),建立了與實際結(jié)構(gòu)相吻合的嗅球網(wǎng)絡模型.其次,對嗅球中存在的兩種實驗現(xiàn)象進行了驗證,包括:動作電位在單個僧帽細胞上的產(chǎn)生和傳遞,嗅球網(wǎng)絡中動作電位產(chǎn)生和傳遞的四種模式,說明了所建網(wǎng)絡模型的合理性.最后,對模型的一些數(shù)值結(jié)果進行了分析,包括:嗅球中不同神經(jīng)元的動作電位發(fā)放序列、不同平面刺激類型所造成的嗅球輸出結(jié)果的不同以及顆粒細胞對僧帽細胞的側(cè)抑制所造成的僧帽細胞側(cè)樹突上動作電位傳遞的衰減和中斷. 8、小腦皮層神經(jīng)回路:首先,通過參考小腦皮層的解剖結(jié)構(gòu),建立了與實際結(jié)構(gòu)相吻合的小腦皮層網(wǎng)絡模型.其次,考察了來自兩種不同傳入系統(tǒng)的刺激所造成的浦肯野細胞發(fā)放頻率上的差異,并通過給定這兩種傳入系統(tǒng)一定的刺激,得到了小腦皮層回路中5種神經(jīng)元的電位發(fā)放圖.再次,利用所建模型考察了小腦皮層回路中存在的兩種重要的現(xiàn)象:時間聚焦現(xiàn)象和空間聚焦現(xiàn)象.最后,針對實際中存在的兔子眼閃爍的條件反射現(xiàn)象,我們也通過所建網(wǎng)絡模型再現(xiàn)了這一過程. 9、海馬神經(jīng)回路:首先,通過參考海馬的解剖結(jié)構(gòu),建立了與實際結(jié)構(gòu)相吻合的海馬結(jié)構(gòu)網(wǎng)絡模型.其次,通過給定一外界刺激,得到了海馬結(jié)構(gòu)中幾種神經(jīng)元的電位發(fā)放圖.最后,重點分析了連接左右海馬片區(qū)的胼胝體對海馬回路中信息處理和加工的影響,得出CA1片區(qū)受同側(cè)CA3輸入的影響要大過對側(cè)CA3對它的輸入. 10、視網(wǎng)膜神經(jīng)回路:首先,通過參考視網(wǎng)膜的解剖結(jié)構(gòu),構(gòu)建了與實際結(jié)構(gòu)相吻合的視網(wǎng)膜網(wǎng)絡模型.其次,考察了光刺激強度的改變所引起的光感受器反應的不同.再次,借助于平面刺激,研究了光刺激范圍的不同和光刺激類型的不同所造成的視網(wǎng)膜神經(jīng)回路輸出結(jié)果的差異.最后,討論了視網(wǎng)膜神經(jīng)回路中網(wǎng)間細胞的反饋抑制對視網(wǎng)膜神經(jīng)節(jié)細胞發(fā)放模式的影響. 11、基底神經(jīng)節(jié)神經(jīng)回路:從基底神經(jīng)節(jié)的功能展開,構(gòu)造了基地神經(jīng)節(jié)網(wǎng)絡模型,通過采用5神經(jīng)元制賦予了網(wǎng)絡五個不同的信號通道,同時模擬5種不同情況的刺激下,正常人、帕金森(PD)病人和DBS治療病人的活動特性(膜電位發(fā)放圖).結(jié)合帕金森病病例,運用WLC模型模擬了PD的發(fā)病機制以及相應的治療方法,通過建立相圖指標對正常人、PD病人和DBS治療病人三種情況進行對比,驗證了治療方法的合理性. 12、大腦內(nèi)其他幾種神經(jīng)回路的介紹:在本節(jié),我們簡要的介紹了大腦內(nèi)存在的其他幾種被廣泛研究和考察的神經(jīng)回路模型:決策選擇網(wǎng)絡、丘腦皮層網(wǎng)絡和運動皮層對隨意運動的控制網(wǎng)絡.并展望了大規(guī)模的腦神經(jīng)網(wǎng)絡的模型及其計算. 通過模型模擬大腦內(nèi)各種神經(jīng)回路中神經(jīng)元動作電位的發(fā)放序列是理論研究大腦神經(jīng)系統(tǒng)的第一步,如何利用所建網(wǎng)絡來分析這些數(shù)值結(jié)果并與實際實驗現(xiàn)象進行對比,進而提出網(wǎng)絡中所隱藏的新的特性就顯得十分重要了. 本文數(shù)值計算采用NEURON和MATLAB軟件,并利用ORIGIN對部分數(shù)據(jù)進行了處理,結(jié)果真實可靠.
[Abstract]:Neuronal circuits are commonly exist in the brain, the main function is the brain information processing unit, and the neurons is composed of the basic unit of the neural circuit is the smallest vector of neural information processing. In this paper, we use small, step-by-step way, systematically analyzes the single compartment neuron model, two compartment model, multi compartment model, cable model, nerve fiber mathematical mechanism and gate control loop of ISI bifurcation in the neuron model activity characteristics and information encoding mechanism, and on this basis, through the establishment of olfactory bulb neural circuits are in good agreement with the actual structure of the cerebellar cortex neural circuits, hippocampal neural circuits, retinal neural circuits and the basal ganglia neural circuits, to simulate the processing and processing of neural signals of these loops were investigated by neural information encoding characteristics of the circuit integration, finally Several other important neural circuits in the brain were briefly introduced, and the results were as follows:
1, the single compartment neuron model: mainly by means of the computer simulation, the effects of CA1 pyramidal neurons has rich firing pattern, analyzed with some electrophysiological parameters, transfer between these payment modes, found several typical nonlinear dynamic bifurcation phenomena, such as period doubling bifurcation, period adding bifurcation so, further
The solution of the information encoding characteristics of CA1 pyramidal neurons. 2, two compartment neuron model: firstly, several ion channels inherent in cortical pyramidal neurons in the two compartment model were investigated. The analysis of distribution pattern and cycle diversity cortical pyramidal neurons of the bifurcation phenomena caused by the disturbance of ion channel conductance and ion balance potential. Secondly, in view of two compartment model in the soma and dendrites in the form and function of the difference, we analyzed two chamber membrane capacitance and conductance change alone and at the same time the change of cortical pyramidal neuron activity characteristics, further understanding of the differences between the soma and dendrites of neurons in the information encoding on again. On the issue, change characteristics of cortical pyramidal neurons caused by the effects of internal potential delay and external temperature. Finally, research on another can produce Ghostbursting two The model of the atrioventricular neuron and the rich dynamic bifurcation phenomena in the general model of the two chamber neurons are summarized.
3, the multi compartment neuron model is mainly a multi compartmental model, three kinds of neurons is constructed by NEURON software including: olfactory mitral cells, cerebellar cortical Purkinje cells and pyramidal cells, the distribution frequency and interspike interval (ISI), compared with three kinds of neuronal potentials of the different characteristics and their differences in their respective neural circuits in the information processing function.
4, cable model: a whole based neuron dendrites, according to the Hodgkin-Huxley channel model and Rall one-dimensional cable model, established the dendrite cable model in three-dimensional space, the corresponding space signal throughout the dendritic transfer theory. Numerical results first revealed neural signals within dendrites space transfer process and the law.
5, the expression of ISI bifurcation of Mathematics: according to the structural characteristics of HH neurons and the trajectory model of neuronal action potentials, through integral and differential two means of interspike interval (ISI) mathematical expressions were derived and applied to the actual neuron model, found the phenomenon of double period a large number of bifurcation bifurcation, by comparing with the traditional LOGISTIC mapping is introduced, elaborated the novelty of ISI times the cycle we present expressions.
6, gate control circuit: in this section, we analyze the specific neural circuits, gate control circuit, analyzes the circuit in three different transmitting pain nerve fibers in the transmission speed, bearing differences in pain types, and the effects of different types of pain caused by the loop efferent neuron response.
7, the olfactory bulb neural circuits: first, through the reference anatomical structure of the olfactory bulb, established olfactory network model are in good agreement with the actual structure. Secondly, two kinds of experimental phenomena exist in the olfactory bulb were verified, including: the generation of action potentials in single mitral cells and the transfer of four modes action potentials of olfactory bulb network and transfer, which proves the rationality of the network model. Finally, some numerical results of the model are analyzed, including: the olfactory bulb in different neuronal action potential firing sequence, the mitral cell lateral dendrites caused by olfactory bulb output results of different types of stimulation caused by plane the different and granular cells of the mitral cell lateral inhibition on action potential propagation and attenuation of the interrupt.
8, the cerebellar cortex neural circuits: first, through the reference anatomical structure of cerebellar cortex cerebellar cortex, established the network model are in good agreement with the actual structure. Secondly, the difference caused by the frequency distribution were investigated from two different afferent system stimulation of Purkinje cells, and by stimulating certain given the two afferent system the potential of the 5 kinds of neurons, the cerebellar cortex in the loop distribution diagram. Thirdly, the model analyzes two important phenomena existing in the cerebellar cortex in the loop: time and space focusing focusing phenomenon. Finally, according to the condition of reflection phenomenon in reality of the rabbit eyes, we also through the network the model reproduces this process.
9, the hippocampal neural circuits: first, through the reference anatomical structure of the hippocampus, established the hippocampal structure network model is consistent with the actual structure. Secondly, through a given stimulus, the potential of several neurons in hippocampal structure in the distribution graph. Finally, analyzed the influence of the corpus callosum is connected to the information about the hippocampus area treatment and processing of hippocampal circuits, the CA1 area is affected by the same side CA3 input is greater than the contralateral CA3 on its input.
10 retinal neural circuits: first, through the anatomical reference of the retina, constructs the retina network model are in good agreement with the actual structure. Secondly, effects of photoreceptor responses to stimulus light changes caused by the different. Again, with the help of plane stimulation, the research results of differences in retinal nerve loop output light stimulation range different types and light stimulation caused by the different. Finally, discussed the feedback inhibitory effects on retinal ganglion cell firing pattern of retinal nerve cells in the loop between.
11, the basal ganglia circuits: start from the function of basal ganglia, construct basal ganglia network model, by using the 5 neuron system gives five different signal channel, and simulated 5 different conditions under the stimulation of normal people, Parkinson (PD) and DBS disease activity characteristics of patients (film potential distribution map). Combined with Parkinson's disease, the WLC model was used to simulate the pathogenesis of PD and the corresponding treatments, through the establishment of a phase diagram index of normal people, compared with PD patients and DBS patients three cases, verified the rationality of the treatment method.
12, several other neural circuits in the brain: in this section, we briefly introduce several other existing neural circuits in the brain has been widely studied and investigated the model: decision network, control network and motor cortex of thalamocortical network free movement. And look a large-scale neural network model and its calculation the.
Through the issuance of series model action potentials of neurons in the brain of various neural circuits is the first step in theoretical research of brain neural system, how to use the network to analyze the numerical results were compared with the actual experimental phenomena and then puts forward the hidden network of new features is very important.
In this paper, NEURON and MATLAB software are used in the numerical calculation, and some data are processed with ORIGIN. The results are true and reliable.

【學位授予單位】：華南理工大學
【學位級別】：碩士
【學位授予年份】：2011
【分類號】：R311

【參考文獻】

相關(guān)期刊論文 前10條

1 王海俠;陸啟韶;鄭艷紅;;神經(jīng)元模型的復雜動力學:分岔與編碼[J];動力學與控制學報;2009年04期

2 汪雷;劉深泉;;大腦中神經(jīng)回路的電位發(fā)放比較[J];動力學與控制學報;2010年03期

3 王功伍;蔡景霞;;海馬-前額葉神經(jīng)回路與工作記憶[J];動物學研究;2010年01期

4 ;Stability Analysis for Recurrent Neural Networks with Time-varying Delay[J];International Journal of Automation & Computing;2009年03期

5 羅，

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