4.7 Article

Univariate and multivariate analyses of functional networks in absolute pitch

期刊

NEUROIMAGE
卷 189, 期 -, 页码 241-247

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2019.01.021

关键词

Absolute pitch; Functional connectivity; MVPA; Resting-state fMRI; Machine learning

资金

  1. Swiss National Science Foundation [320030_163149]
  2. Swiss National Science Foundation (SNF) [320030_163149] Funding Source: Swiss National Science Foundation (SNF)

向作者/读者索取更多资源

Absolute pitch (AP) refers to the rare ability to identify the pitch of any given tone without an external reference tone. Previous studies have shown that during auditory processing, AP musicians activate the auditory cortex (AC), the prefrontal cortex (PFC), and parietal areas of the brain. Therefore, it has been hypothesized that AP is sustained by a widespread functional network. In the present functional magnetic resonance imaging (fMRI) study, we tested this hypothesis by employing a mass-univariate analysis of resting-state functional connectivity within the AC, the PFC, and parietal areas in a large sample of musicians with and without AP (N =100). AP musicians showed increased functional connectivity in the left middle frontal gyrus (MFG), left intraparietal sulcus (IPS), and right superior parietal lobule (SPL). These results provide the first evidence for an AP-specific network characterized by increased functional connections in higher-order cognitive areas. Interestingly, AP was not associated with increases in functional connectivity of the AC, but AP was successfully decoded from functional connectivity patterns in the left AC using multi-voxel pattern analysis (MVPA, also known as multivariate pattern analysis), with group classification accuracy being highest for the left Heschl's gyrus (HG). MVPA can capture fine-grained patterns in the brain connectivity profile of AP musicians, whilst a mass-univariate analysis is sensitive to macroscopic trends in the data. The successful differentiation of AP musicians by MVPA but not by a mass-univariate analysis of connectivity in the AC thus indicates that AP musicians differ in the finegrained rather than the macroscopic AC function. Based on our findings, and in light of current literature, we propose pitch-label associations, tonal working memory, pitch categorization, and multimodal integration as potential mechanisms underlying the AP ability. This set of psychological functions is controlled by a distributed functional network and a particular AC connectivity pattern only present in AP musicians.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据