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Connection Strategies in Associative Memory Models with Spiking and Non-spiking Neurons

机译:尖峰和非尖峰神经元的关联记忆模型中的连接策略

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The problem we address in this paper is that of finding effective and parsimonious patterns of connectivity in sparse associative memories. This problem must be addressed in real neuronal systems, so results in artificial systems could throw light on real systems. We show that there are efficient patterns of connectivity and that these patterns are effective in models with either spiking or non-spiking neurons. This suggests that there may be some underlying general principles governing good connectivity in such networks.
机译:我们在本文中解决的问题是在稀疏的关联记忆中找到有效且简约的连接模式。这个问题必须在真实的​​神经元系统中解决,因此人造系统的结果可能会对真实的系统有所启发。我们表明存在有效的连接模式,并且这些模式在带有尖峰或非尖峰神经元的模型中均有效。这表明可能存在一些基本原则来管理此类网络中的良好连接。

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