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鸣禽学习叫声中句法结构的神经编码。

Neural coding of syntactic structure in learned vocalizations in the songbird.

机构信息

Department of Biological Sciences, Faculty of Medicine, Graduate School of Biostudies, Kyoto University, Kyoto, Kyoto 606-8501, Japan.

出版信息

J Neurosci. 2011 Jul 6;31(27):10023-33. doi: 10.1523/JNEUROSCI.1606-11.2011.

Abstract

Although vocal signals including human languages are composed of a finite number of acoustic elements, complex and diverse vocal patterns can be created from combinations of these elements, linked together by syntactic rules. To enable such syntactic vocal behaviors, neural systems must extract the sequence patterns from auditory information and establish syntactic rules to generate motor commands for vocal organs. However, the neural basis of syntactic processing of learned vocal signals remains largely unknown. Here we report that the basal ganglia projecting premotor neurons (HVC(X) neurons) in Bengalese finches represent syntactic rules that generate variable song sequences. When vocalizing an alternative transition segment between song elements called syllables, sparse burst spikes of HVC(X) neurons code the identity of a specific syllable type or a specific transition direction among the alternative trajectories. When vocalizing a variable repetition sequence of the same syllable, HVC(X) neurons not only signal the initiation and termination of the repetition sequence but also indicate the progress and state-of-completeness of the repetition. These different types of syntactic information are frequently integrated within the activity of single HVC(X) neurons, suggesting that syntactic attributes of the individual neurons are not programmed as a basic cellular subtype in advance but acquired in the course of vocal learning and maturation. Furthermore, some auditory-vocal mirroring type HVC(X) neurons display transition selectivity in the auditory phase, much as they do in the vocal phase, suggesting that these songbirds may extract syntactic rules from auditory experience and apply them to form their own vocal behaviors.

摘要

尽管包括人类语言在内的声音信号由有限数量的声学元素组成,但通过这些元素的组合,并通过句法规则进行连接,可以创造出复杂多样的声音模式。为了实现这种句法声音行为,神经系统必须从听觉信息中提取序列模式,并建立句法规则,以便为发声器官生成运动指令。然而,对于学习到的声音信号的句法处理的神经基础在很大程度上仍然未知。在这里,我们报告说,孟加拉雀的基底神经节投射至前运动神经元(HVC(X)神经元)代表了生成可变歌曲序列的句法规则。当以元素之间的替代过渡段(称为音节)进行替代过渡段发声时,HVC(X)神经元稀疏爆发的尖峰脉冲编码特定音节类型或替代轨迹中特定过渡方向的身份。当以相同音节的可变重复序列发声时,HVC(X)神经元不仅发出重复序列的开始和结束信号,还指示重复序列的进度和完成状态。这些不同类型的句法信息经常在单个 HVC(X)神经元的活动中得到整合,这表明单个神经元的句法属性不是预先作为基本细胞亚型编程的,而是在发声学习和成熟过程中获得的。此外,一些听觉-发声镜像类型的 HVC(X)神经元在听觉阶段表现出过渡选择性,就像它们在发声阶段一样,这表明这些鸣禽可能从听觉经验中提取句法规则,并将其应用于形成自己的发声行为。

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本文引用的文献

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Support for a synaptic chain model of neuronal sequence generation.支持神经元序列生成的突触链模型。
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3
Linked control of syllable sequence and phonology in birdsong.鸟鸣中音节序列和音韵的连锁控制。
J Neurosci. 2010 Sep 29;30(39):12936-49. doi: 10.1523/JNEUROSCI.2690-10.2010.
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A synaptic basis for auditory-vocal integration in the songbird.鸣禽听觉-发声整合的突触基础。
J Neurosci. 2008 Feb 6;28(6):1509-22. doi: 10.1523/JNEUROSCI.3838-07.2008.

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