STDP provides the substrate for igniting synfire chains by spatiotemporal input patterns
STDP provides the substrate for igniting synfire chains by spatiotemporal input patterns
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DOI：
10.1162/neco.2007.11-05-043
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发表时间：
2008-02-01
影响因子：
2.9
通讯作者：
Ikeguchi, Tohru
中科院分区：
文献类型：
--
作者：
Hosaka, Ryosuke;Araki, Osamu;Ikeguchi, Tohru
在皮质和海马中观察到尖峰定时依赖性突触可塑性（STDP），其取决于突触前和突触后动作电位之间的时间差异。虽然一些理论和实验研究揭示了它的基本方面，其功能作用仍然不清楚。为了研究输入时空尖峰模式是如何被STDP改变的，当输入时空模式被重复应用时，我们观察了具有不对称STDP规则的尖峰神经网络模型的输出尖峰模式。尖峰神经网络包括表现出局部相互作用的兴奋性和抑制性神经元。数值实验表明，脉冲神经网络产生一个单一的全球同步，其相对定时依赖于输入的时空模式和神经网络的结构。这一结果意味着脉冲神经网络学习从时空到时间信息的转换。在文献中，synfire链的起源还没有得到足够的关注。我们的研究结果表明，与STDP脉冲神经网络可以点燃synfire链在皮层。
Spike-timing-dependent synaptic plasticity (STDP), which depends on the temporal difference between pre- and postsynaptic action potentials, is observed in the cortices and hippocampus. Although several theoretical and experimental studies have revealed its fundamental aspects, its functional role remains unclear. To examine how an input spatiotemporal spike pattern is altered by STDP, we observed the output spike patterns of a spiking neural network model with an asymmetrical STDP rule when the input spatiotemporal pattern is repeatedly applied. The spiking neural network comprises excitatory and inhibitory neurons that exhibit local interactions. Numerical experiments show that the spiking neural network generates a single global synchrony whose relative timing depends on the input spatiotemporal pattern and the neural network structure. This result implies that the spiking neural network learns the transformation from spatiotemporal to temporal information. In the literature, the origin of the synfire chain has not been sufficiently focused on. Our results indicate that spiking neural networks with STDP can ignite synfire chains in the cortices.