与听觉信息相关的预测性大脑活动与在杂环境中执行语音理解任务的表现有关
Kazuhiro Okamoto1, Kengo Hoyano1, Yoshitomo Saiki1
1Department of Rehabilitation, Faculty of Health Science, Fukui Health Science University, Fukui, Japan.
Frontiers in human neuroscience
|November 14, 2024
概括
通过预测,噪音中的语音理解得到了改善,这是由刺激前的消极性 (SPN) 表示的. 在杂的环境中增加SPN表明需要更多的注意力来准确处理语音.
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.
- 认知科学 认知科学
背景情况:
- 对于有听力障碍和没有听力障碍的人来说,在杂的环境中理解语音是困难的.
- 目前用于评估噪音中的语音理解的方法存在局限性,特别是对于那些有外围听力障碍的人来说.
- 预测编码模型认为,语音理解涉及通过自下而上的和自上而下的处理整合感官信息.
研究的目的:
- 研究预测在语音理解中的作用.
- 检查电生理标记刺激前的消极性 (SPN) 作为语音处理中预期的度量.
主要方法:
- 在正常听觉的年轻成年人中测量了SPN振幅.
- 使用了带有听觉反的时间估计任务.
- 在安静和杂的听觉条件下进行测量.
主要成果:
- 与安静条件相比,SPN振幅在杂的环境中显著增加.
- SPN振幅的个体差异与语音噪音测试中的表现相关.
结论:
- 在噪音中增加的SPN振幅反映了对准确预测语音的注意力需求的增加.
- SPN显示出作为一种非侵入性神经标记物的潜力,用于评估在噪音环境中对语音理解的上下处理中的个体差异.
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