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音级分布调节无调性和弦序列的统计学习。

Pitch-class distribution modulates the statistical learning of atonal chord sequences.

作者信息

Daikoku Tatsuya, Yatomi Yutaka, Yumoto Masato

机构信息

Department of Clinical Laboratory, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

Department of Clinical Laboratory, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

出版信息

Brain Cogn. 2016 Oct;108:1-10. doi: 10.1016/j.bandc.2016.06.008. Epub 2016 Jul 16.

Abstract

The present study investigated whether neural responses could demonstrate the statistical learning of chord sequences and how the perception underlying a pitch class can affect the statistical learning of chord sequences. Neuromagnetic responses to two chord sequences of augmented triads that were presented every 0.5s were recorded from fourteen right-handed participants. One sequence was a series of 360 chord triplets, each of which consisted of three chords in the same pitch class (clustered pitch-classes sequences). The other sequence was a series of 360 chord triplets, each of which consisted of three chords in different pitch classes (dispersed pitch-classes sequences). The order of the triplets was constrained by a first-order Markov stochastic model such that a forthcoming triplet was statistically defined by the most recent triplet (80% for one; 20% for the other two). We performed a repeated-measures ANOVA with the peak amplitude and latency of the P1m, N1m and P2m. In the clustered pitch-classes sequences, the P1m responses to the triplets that appeared with higher transitional probability were significantly reduced compared with those with lower transitional probability, whereas no significant result was detected in the dispersed pitch-classes sequences. Neuromagnetic significance was concordant with the results of familiarity interviews conducted after each learning session. The P1m response is a useful index for the statistical learning of chord sequences. Domain-specific perception based on the pitch class may facilitate the domain-general statistical learning of chord sequences.

摘要

本研究调查了神经反应是否能够证明对和弦序列的统计学习,以及音级感知如何影响和弦序列的统计学习。从14名右利手参与者中记录了对每0.5秒呈现一次的两个增三和弦和弦序列的神经磁反应。一个序列是一系列360个和弦三元组,每个三元组由同一音级中的三个和弦组成(聚类音级序列)。另一个序列是一系列360个和弦三元组,每个三元组由不同音级中的三个和弦组成(分散音级序列)。三元组的顺序受一阶马尔可夫随机模型约束,使得即将出现的三元组在统计上由最近的三元组定义(一个为80%;另外两个为20%)。我们对P1m、N1m和P2m的峰值幅度和潜伏期进行了重复测量方差分析。在聚类音级序列中,与具有较低过渡概率的三元组相比,对具有较高过渡概率的三元组的P1m反应显著降低,而在分散音级序列中未检测到显著结果。神经磁意义与每次学习 session 后进行的熟悉度访谈结果一致。P1m反应是和弦序列统计学习的一个有用指标。基于音级的特定领域感知可能有助于和弦序列的通用领域统计学习。

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