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首页> 外文期刊>Neural Networks: The Official Journal of the International Neural Network Society >Developmental learning of complex syntactical song in the Bengalese finch: a neural network model.
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Developmental learning of complex syntactical song in the Bengalese finch: a neural network model.

机译:孟加拉雀科复杂句法歌曲的开发学习:神经网络模型。

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摘要

We developed a neural network model for studying neural mechanisms underlying complex syntactical songs of the Bengalese finch, which result from interactions between sensori-motor nuclei, the nucleus HVC (HVC) and the nucleus interfacialis (NIf). Results of simulations are tested by comparison with the song development of real young birds learning the same songs from their fathers. The model shows that complex syntactical songs can be reproduced from the simple interaction between the deterministic dynamics of a recurrent neural network and random noise. Features of the learning process in the simulations show similar trends to those observed in empirical data on the song development of real birds. These observations suggest that the temporal note sequences of songs take the form of a dynamical process involving recurrent connections in the network of the HVC, as opposed to feedforward activities, the mechanism proposed in the previous model.
机译:我们开发了一个神经网络模型,用于研究孟加拉雀科的复杂句法歌曲所基于的神经机制,这是由感觉运动核,HVC核(HVC)和界面核(NIf)之间的相互作用导致的。通过与真实幼鸽从父亲那里学习相同歌曲的歌曲发展进行比较,测试了模拟结果。该模型表明,复杂的句法歌曲可以从递归神经网络的确定性动力学与随机噪声之间的简单交互作用中重现。模拟中学习过程的特征显示出与真实鸟类歌曲发展经验数据中观察到的趋势类似的趋势。这些观察结果表明,歌曲的时间音符序列采取动态过程的形式,该过程涉及HVC网络中的反复连接,这与前一模型中提出的机制前馈活动相反。

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