Spatial representation of temporal information through spike-timing-dependent plasticity.
Spatial representation of temporal information through spike-timing-dependent plasticity.
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DOI：
10.1103/physreve.68.011908
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发表时间：
2002-09
期刊：
影响因子：
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通讯作者：
Thomas Nowotny;M. Rabinovich;H. Abarbanel
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文献类型：
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作者：
Thomas Nowotny;M. Rabinovich;H. Abarbanel
我们提出了一种基于突触的spike- time -dependent plasticity （STDP）来存储、检索和预测时间序列的机制。该机制在一个由STDP突触紧密连接的简化的整合-火型神经元模型系统中得到了证明。所有的突触都是根据各种真实生物突触中观察到的所谓正常STDP规则进行修饰的。通过对有限数量的时间序列的重复输入进行调节后，系统能够在接收到其中一部分时间序列的输入时完成该时间序列。这是一个在生物现实系统中有效的无监督学习的例子。我们研究了学习成功与娱乐时间、系统大小和噪音存在的关系。可能的应用包括运动序列的学习，视觉和听觉系统中时间感觉信息的识别和预测，以及昆虫嗅觉系统的后期处理。
We suggest a mechanism based on spike-timing-dependent plasticity (STDP) of synapses to store, retrieve and predict temporal sequences. The mechanism is demonstrated in a model system of simplified integrate-and-fire type neurons densely connected by STDP synapses. All synapses are modified according to the so-called normal STDP rule observed in various real biological synapses. After conditioning through repeated input of a limited number of temporal sequences, the system is able to complete the temporal sequence upon receiving the input of a fraction of them. This is an example of effective unsupervised learning in a biologically realistic system. We investigate the dependence of learning success on entrainment time, system size, and presence of noise. Possible applications include learning of motor sequences, recognition and prediction of temporal sensory information in the visual as well as the auditory system, and late processing in the olfactory system of insects.