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Neural processing of musical meter in musicians and non-musicians

机译:音乐家和非音乐家音乐仪的神经处理

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Musical sounds, along with speech, are the most prominent sounds in our daily lives. They are highly dynamic, yet well structured in the temporal domain in a hierarchical manner. The temporal structures enhance the predictability of musical sounds. Western music provides an excellent example: while time intervals between musical notes are highly variable, underlying beats can be realized. The beat-level temporal structure provides a sense,of regular pulses. Beats can be further organized into units, giving the percept of alternating strong and weak beats (i.e. metrical structure or meter). Examining neural processing at the meter level offers a unique opportunity to understand how the human brain extracts temporal patterns, predicts future stimuli and optimizes neural resources for processing. The present study addresses two important questions regarding meter processing, using the mismatch negativity (MMN) obtained with electroencephalography (EEG): 1) how tempo (fast vs. slow) and type of metrical structure (duple: two beats per unit vs. triple: three beats per unit) affect the neural processing of metrical structure in non-musically trained individuals, and 2) how early music training modulates the neural processing of metrical structure. Metrical structures were established by patterns of consecutive strong and weak tones (Standard) with occasional violations that disrupted and reset the structure (Deviant). Twenty non-musicians listened passively to these tones while their neural activities were recorded. MMN indexed the neural sensitivity to the meter violations. Results suggested that MMNs were larger for fast tempo and for triple meter conditions. Further, 20 musically trained individuals were tested using the same methods and the results were compared to the non-musicians. While tempo and meter type similarly influenced MMNs in both groups, musicians overall exhibited significantly reduced MMNs, compared to their non-musician counterparts. Further analyses indicated that the reduction was driven by responses to sounds that defined the structure (Standard), not by responses to Deviants. We argue that musicians maintain a more accurate and efficient mental model for metrical structures, which incorporates occasional disruptions using significantly fewer neural resources.
机译:音乐声音以及言论,是我们日常生活中最突出的声音。它们具有高度动态的,并且以分层方式在时间域中结构良好。时间结构增强了音乐声音的可预测性。西方音乐提供了一个很好的例子:而音符之间的时间间隔是高度变化的,可以实现潜在的节拍。节拍级时间结构提供了常规脉冲的感觉。跳动可以进一步组织成单位,给出交替强度和弱节拍的感知(即韵律结构或仪表)。在仪表层面检查神经处理提供了一个独特的机会,了解人脑如何提取时间模式,预测未来的刺激并优化神经资源进行处理。本研究解决了有关仪表处理的两个重要问题,使用用脑电图(EEG)获得的失配消极性(MMN):1)如何节奏(快速与慢速)和级别结构类型(双重:每单位的两个节拍与三倍:每单位三个节拍)影响非音乐训练有素的韵律结构的神经处理,以及2)早期音乐训练如何调节韵律结构的神经处理。通过连续强度和弱音调(标准)的模式建立了测量结构,偶尔违规破坏和重置结构(偏差)。在记录他们的神经活动时,二十名非音乐家被动地听到这些音调。 MMN索引了对仪表违规的神经敏感性。结果表明,快速节奏和三级条件的MMN较大。此外,使用相同的方法测试20个音乐训练的个体,并将结果与​​非音乐家进行比较。虽然速度和仪表类型在这两个群体中相似地影响了MMN,但与非音乐同行相比,音乐家整体展会显着减少了MMN。进一步的分析表明,通过对定义结构(标准)的声音的响应来驱动减少,而不是通过对偏差的反应来驱动。我们认为音乐家为估计结构维持更准确,高效的心理模型,它含有偶尔使用显着较少的神经资源的中断。

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