Spike-driven synaptic plasticity for learning correlated patterns of asynchronous activity

被引:0
作者
Fusi, S [1 ]
机构
[1] Univ Bern, Inst Physiol, CH-3012 Bern, Switzerland
来源
ARTIFICIAL NEURAL NETWORKS - ICANN 2002 | 2002年 / 2415卷
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D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Long term synaptic changes induced by neural spike activity are believed to underlie learning and memory. Spike-driven long term synaptic plasticity has been investigated in simplified situations in which the patterns of asynchronous activity to be encoded were statistically independent. An extra regulatory mechanism is required to extend the learning capability to more complex and natural stimuli. This mechanism is provided by the effects of the action potentials that are believed to be responsible for spike-timing dependent plasticity. These effects, when combined with the dependence of synaptic plasticity on the post-synaptic depolarization, produce the learning rule needed for storing correlated patterns of asynchronous neuronal activity.
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页码:241 / 247
页数:7
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