音乐激活的大脑在适应词汇音调变化方面的优势

IF 2.1 2区 心理学 Q1 AUDIOLOGY & SPEECH-LANGUAGE PATHOLOGY Brain and Language Pub Date : 2023-10-28 DOI:10.1016/j.bandl.2023.105348
Kaile Zhang , Ran Tao , Gang Peng
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引用次数: 0

摘要

对多个说话者讲话的感知是具有挑战性的。受过音乐训练的人通常表现出更强、更快的音调感知能力。本研究调查了音乐训练经验是否有助于音调型语言使用者适应词汇音调的言语可变性。本地的广东人音乐家和非音乐家被要求从多个扬声器中识别广东话级别的音调。两组在使用上下文线索来规范行为层面的词汇音调变异性方面表现同样出色。然而,音乐训练的优势是在皮层水平上观察到的。时域ERP分析表明,音乐家比非音乐家更早地将词汇音调变异性标准化(N1:70-175 ms,P2:175-280 ms)。一项探索性的来源分析进一步表明,两组人可能依赖于不同的皮层区域来规范词汇音调。左BA41在音乐家调节音调变异方面表现出更强的参与,但右听皮层(包括BA41、42和22)在非音乐家中的激活程度更高。
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The advantage of the music-enabled brain in accommodating lexical tone variabilities

The perception of multiple-speaker speech is challenging. People with music training generally show more robust and faster tone perception. The present study investigated whether music training experience can facilitate tonal-language speakers to accommodate speech variability in lexical tones. Native Cantonese musicians and nonmusicians were asked to identify Cantonese level tones from multiple speakers. Two groups were equally well in using context cues to normalize lexical tone variability at behavioral level. However, the advantage of music training was observed at cortical level. The time-domain ERP analysis suggested that musicians normalized lexical tone variability much earlier than nonmusicians (N1: 70–175 ms vs. P2: 175–280 ms). An exploratory source analysis further revealed that two groups probably relied on different cortical regions to normalize lexical tones. Left BA41 showed stronger involvement in musicians in accommodating tone variability, but right auditory cortex (including BA 41, 42 and 22) activated to a greater extend in nonmusicians.

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来源期刊
Brain and Language
Brain and Language 医学-神经科学
CiteScore
4.50
自引率
8.00%
发文量
82
审稿时长
20.5 weeks
期刊介绍: An interdisciplinary journal, Brain and Language publishes articles that elucidate the complex relationships among language, brain, and behavior. The journal covers the large variety of modern techniques in cognitive neuroscience, including functional and structural brain imaging, electrophysiology, cellular and molecular neurobiology, genetics, lesion-based approaches, and computational modeling. All articles must relate to human language and be relevant to the understanding of its neurobiological and neurocognitive bases. Published articles in the journal are expected to have significant theoretical novelty and/or practical implications, and use perspectives and methods from psychology, linguistics, and neuroscience along with brain data and brain measures.
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