MEMORY DYNAMICS IN ASYNCHRONOUS NEURAL NETWORKS
MEMORY DYNAMICS IN ASYNCHRONOUS NEURAL NETWORKS
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DOI：
10.1143/ptp.78.51
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发表时间：
1987-07-01
影响因子：
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通讯作者：
SHIMIZU, H
中科院分区：
文献类型：
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作者：
TSUDA, I;KOERNER, E;SHIMIZU, H
提出了一个无教师连续记忆回忆的学习、记忆形成模型。总结了本研究的哲学背景。所研究的网络由两组异步发射模型神经元组成。一组神经元负责场效应，另一组作为输入/输出模块引入。场效应以系统自响应的形式给出。结果表明，场效应的正反馈和负反馈在记忆模式的连续回忆中起着重要作用。这些建议的机制在大脑中实施的可能性进行了讨论。通过对一个宏变量进行Lorenz图，我们得到了关于随机连续回忆记忆表征的宏变量水平上的准确定性定律。我们证明了这种宏观秩序是由环面坍缩引起的确定性混沌，这种混沌可以作为记忆痕迹的有效工具。
A model which can perform learning, formation of memory without teacher for successive memory recalls is presented. The philosophical background of the study is summarized. The investigated network consists of two sets both composed of asynchronously firing model neurons. One set of neurons is responsible for the field effect, and the other is introduced as an input/output module. The field effect is given in the form of the system's self-response. It is shown that positive and negative global feedbacks by the field effect play an essential role in the successive recall of stored patterns. The possibility that these proposed mechanisms are implemented in the brain is discussed. We obtained a quasi-deterministic law on the level of a macrovariable concerning a random successive recall of memory representations by taking a Lorenz-plot of this macrovariable. We show that this macroscopic order is deterministic chaos steming from collapse of tori and this type of chaos can be an effective gadget for memory traces.