在上皮层的多变量fMRI反应预测视觉贡献,和个体差异,杂的语音的可理解性
Yue Zhang1, Johannes Rennig2, John F Magnotti3
1Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States; Department of Neurosurgery, Baylor College of Medicine, Houston, TX, United States.
NeuroImage
|July 13, 2023
概括
看到说话者的脸可以提高对噪音的语言理解. 上皮质中的大脑活动模式揭示了个体在处理杂语音方面的差异,为人们提供了对感知的见解.
科学领域:
- 神经科学是一个神经科学.
- 听觉感知是一种听觉感知.
- 语音处理 语音处理
背景情况:
- 人类即使在背景噪音下也能理解语言.
- 视觉线索 (看到发言人) 提高噪音语音的可理解性.
- 在感知噪音语言的能力方面存在显著的个体差异.
研究的目的:
- 引入一个多变体的血氧水平依赖 (BOLD) 功能磁共振成像 (fMRI) 测量.
- 解释视觉线索如何提高可理解性,并解释噪音语音感知中的个人差异.
- 在噪音中调查语音可理解性的神经相关性.
主要方法:
- 与37名参与者进行了两项独立的fMRI研究.
- 参与者在视觉,听觉和视听格式中听到清晰而杂的演讲,并对可理解性进行评分.
- 来自上皮质的多变体BOLD fMRI数据使用个体差异多维缩放来分析,以测量神经反应不相似性.
主要成果:
- 与仅仅是听觉语言相比,视听语言的神经差异较低,与更好的理解性相关.
- 在参与者中观察到较好的噪音语音感知下部神经不相似性,反映了个体差异.
- 这些发现适用于单个单词和句子,表明了通知的一般机制.
结论:
- 从fMRI数据中可以推导出感知可理解性的神经测量.
- 这一措施解释了视觉线索的好处和噪音语音感知中的个体变异性.
- 这些发现可能会为帮助语音知觉受损的个体制定策略.
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