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人类听觉皮层中对歌曲具有选择性的神经群体。

A neural population selective for song in human auditory cortex.

机构信息

Zuckerman Institute, Columbia University, New York, NY, USA; HHMI Fellow of the Life Sciences Research Foundation, Chevy Chase, MD, USA; Laboratoire des Sytèmes Perceptifs, Département d'Études Cognitives, ENS, PSL University, CNRS, Paris, France; Department of Biostatistics & Computational Biology, University of Rochester Medical Center, Rochester, NY, USA; Department of Neuroscience, University of Rochester Medical Center, Rochester, NY, USA; Department of Biomedical Engineering, University of Rochester, Rochester, NY, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.

Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA; McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA; Center for Brains, Minds and Machines, Cambridge, MA, USA.

出版信息

Curr Biol. 2022 Apr 11;32(7):1470-1484.e12. doi: 10.1016/j.cub.2022.01.069. Epub 2022 Feb 22.

Abstract

How is music represented in the brain? While neuroimaging has revealed some spatial segregation between responses to music versus other sounds, little is known about the neural code for music itself. To address this question, we developed a method to infer canonical response components of human auditory cortex using intracranial responses to natural sounds, and further used the superior coverage of fMRI to map their spatial distribution. The inferred components replicated many prior findings, including distinct neural selectivity for speech and music, but also revealed a novel component that responded nearly exclusively to music with singing. Song selectivity was not explainable by standard acoustic features, was located near speech- and music-selective responses, and was also evident in individual electrodes. These results suggest that representations of music are fractionated into subpopulations selective for different types of music, one of which is specialized for the analysis of song.

摘要

音乐在大脑中是如何表现的?尽管神经影像学已经揭示了一些对音乐和其他声音的反应之间的空间分离,但对于音乐本身的神经编码知之甚少。为了解决这个问题,我们开发了一种使用对自然声音的颅内反应来推断人类听觉皮层的典型反应成分的方法,并用 fMRI 的更高覆盖率来映射它们的空间分布。推断出的成分复制了许多先前的发现,包括对语音和音乐的明显神经选择性,但也揭示了一个对仅包含歌唱的音乐有反应的新成分。歌曲选择性不能用标准的声学特征来解释,它位于语音和音乐选择性反应的附近,在单个电极中也很明显。这些结果表明,音乐的表示被分为对不同类型的音乐具有选择性的亚群,其中一个亚群专门用于分析歌曲。

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