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相关实验视频

Updated: Jul 5, 2025

fMRI Mapping of Brain Activity Associated with the Vocal Production of Consonant and Dissonant Intervals
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使用7T功能性MRI解码单个和对联的音符.

Maria Araújo Vitória1, Francisco Guerreiro Fernandes1, Max van den Boom1,2

  • 1Brain Center Rudolf Magnus, Department of Neurology and Neurosurgery, University Medical Center Utrecht, Utrecht, The Netherlands.

Brain topography
|January 23, 2024
PubMed
概括
此摘要是机器生成的。

来自单个语音的脑活动可以被解码,即使结合起来. 这支持了使用机器学习在感觉运动皮层数据上的语音脑计算机接口 (BCI) 的可行性.

关键词:
功能性磁共振成像; 语音 脑电脑接口语音表达方式 (Phonemes)传感器 - 运动器语音神经假体 语音神经假体语音制作 语音制作

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相关实验视频

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科学领域:

  • 神经科学是一个神经科学.
  • 认知科学 认知科学
  • 生物医学工程 生物医学工程

背景情况:

  • 语音发音的口腔运动在感觉运动皮质中得到表现.
  • 这种神经表示理论上使脑计算机接口 (BCI) 能够进行连续的语音解码.

研究的目的:

  • 使用感觉运动皮层活动研究单个和配对语音的可解码性.
  • 确定在单个音符上训练的分类器是否可以解码组合音符.

主要方法:

  • 功能磁共振成像 (fMRI) 在7特斯拉.
  • 十五名参与者发音单个和配对的语音.
  • 支持矢量机 (SVM) 分类和搜索灯分析.

主要成果:

  • 单个和配对语音的SVM分类是成功的.
  • 使用单音符分类器对配音符进行分类,获得了53%的准确率 (33%的机会水平).
  • 语音表达在腹部感觉运动皮质中分布广泛.

结论:

  • 孤立的语音的神经活动存在,并且可以在组合的语音中区分.
  • 这些发现支持使用在单个语音上训练的机器学习算法进行语音BCI的可行性.
  • 这项研究对开发使用内电极网的先进BCI有影响.