兰州大学机构库 >物理科学与技术学院
神经系统中突触可塑性模型研究
Alternative TitleStudy on the Models of Synaptic Plasticity in Neuronal Systems
黄玥
Thesis Advisor汪映海
2002-05-12
Degree Grantor兰州大学
Place of Conferral兰州
Degree Name硕士
Keyword神经系统 突出可塑性 计算机模拟
Abstract大脑作为一个极其复杂而高效的信息处理系统,其工作机制一直是从神经生物学、认知科学、信息科学,到非线性动力学、生物物理等学科研究的热点。许多新的交叉学科也因此而诞生,比如计算神经科学(Computational Neuroscience)和各种用于理论研究或实际应用的神经网络模型的提出。 在大脑中,信息的表达或编码方式以及信息的存储方式都与Von Neumann 式的数字计算机截然不同。作为神经系统中基本元素的神经元,是具有累积——发放功能的非线性阈值单元;而各神经元之间的连接结构——突触,具有可塑性,通常是由突触前和突触后的神经元的发放模式所决定。这种可塑性对于大脑的学习、记忆功能具有极其重要的意义。另一种非常重要的现象就是神经系统中各神经元的同步发放,这是在神经生物学实验中经常观察到的现象,存在于大脑的不同区域。 本文重点研究了近年来在实验中发现的一种新的突触可塑性——依赖于动作电位时间的突触可塑性(STDP)。我们在更加符合实验实事的基础上对已有的关于STDP的模型进行了修改并通过统计理论得出STDP在一定条件下具有的平衡性质,并且通过计算机模拟验证了这一性质。我们还发现在一定情况下,STDP也可以作为一种基于发放频率的学习法则的基础。我们通过计算机模拟研究了单个HH神经元多个输入的系统在输入相互独立时的性质,并且发现如果相应的突触满足STDP法则,在这种情况下对于信息传递和处理没有积极的意义。但如果输入神经元有一部分做同步发放,则会产生与独立发放完全不同的结果,这种情况下对于信息的传递和处理都会有很有意义的现象出现。 在对STDP法则做了较为详细的研究后我们又对另一种突触可塑性——BCM理论作了初步的研究。该理论由于实验支持不多所以没有引起很多人的重视。我们写出了BCM的具体的数学形式并模拟了类似的单个HH神经元多个输入,相应的突触满足BCM理论所描述的可塑性的系统,发现在一定情况下系统会出现振荡现象。最后我们对可以进行的后续工作和神经系统中可塑性的模拟研究进行了讨论和展望。
Other AbstractBeing an extremely complex and highly efficient information processing system, the brain and its functioning mechanisms have attracted extensive attentions from Neurobiology, Cognitive Science, Information Science to Nonlinear Dynamics and Biophysics, giving birth to many multidisciplinary research such as Computational Neuroscience and the emergences of various neural networks models, either for theoretical study or for practical purposes. In the brain, the way that information is encoded and stored is completely different from that of a Von Neumann type digital computer. As the building blocks of neuronal systems, neurons are nonlinear threshold units that can integrate and fire. Synapse, the connection structure between neurons, is subjected to plasticity, which is generally determined by the firing patterns of pre and postsynaptic neurons. This kind of plasticity has great implications to learning and memory in the brain. Another very important phenomenon is the synchronization of firing among neurons, which is frequently discovered in neurobiological experiments and various regions of the brain. In this thesis, we mainly focused on the study of a new synaptic plasticity discovered in experiments in recent years—the Spike-Timing Dependent Plasticity (STDP). Incorporated more experimental details, we updated the prior mathematic model of STDP and studied its equilibrium property using relevant statistical theory. We discovered that STDP could serve as the basis of a rate-learning rule under certain conditions. Using computer simulations, we studied the system of a single HH neuron which is driven by multiple synaptic inputs, and the corresponding synapses are subjected to STDP rule. We found that independent inputs would yield meaningless results for information transmission and processing, however, if a subpopulation of the input neurons fire synchronously, much more meaningful phenomena for information transmission and processing would emerge. After the relatively detailed study of STDP, we proceeded to deal with another synaptic plasticity rule——the BCM theory, which has attracted little attention due to its scarce experimental support. We worked out its detailed mathematical form and again studied the system of single HH neuron which is driven by multiple synaptic inputs using computer simulation, this time the synapses are subjected to BCM accordingly. We found that the system would have some kind of oscillation behavior under certain condit...
URL查看原文
Language中文
Document Type学位论文
Identifierhttps://ir.lzu.edu.cn/handle/262010/229398
Collection物理科学与技术学院
Recommended Citation
GB/T 7714
黄玥. 神经系统中突触可塑性模型研究[D]. 兰州. 兰州大学,2002.
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