在注意力分裂的情况下,噪音编码语音的神经处理:fMRI机器学习研究
Han Wang1,2, Rongru Chen3, Josef Schlittenlacher3
1Clinical Systems Neuroscience Section, Department of Developmental Neurosciences, Great Ormond Street Institute of Child Health, University College London, London, UK.
Human brain mapping
|August 7, 2025
概括
在注意力分裂下了解退化语音感知至关重要. 我们的研究表明,管理具有挑战性的语言的注意力资源涉及前神经网络,有助于处理困难的听觉信息.
科学领域:
- 神经科学是一个神经科学.
- 认知科学 认知科学
- 听觉感知是一种听觉感知.
背景情况:
- 现实生活中的沟通往往涉及到劣质的言语和注意力分裂.
- 在多任务处理时处理受损语音的神经基础仍然不清楚.
研究的目的:
- 研究神经网络,支持在注意力分裂下降低语音感知.
- 了解如何在复杂的审计任务中管理注意力资源.
主要方法:
- 使用了功能磁共振成像 (fMRI) 和机器学习 (XGBoost).
- 一个双任务范式涉及参与者在执行视觉运动任务 (不同难度) 时,倾听噪声编码的句子 (不同难度).
主要成果:
- 分裂的注意力诱导了前额外皮层和带带皮层以及双边岛皮层的可理解性相关反应.
- 机器学习确定了与注意力控制和绩效监测相关的前部区域的一般模式和特定响应.
结论:
- 在分散的注意力下挑战语音感知,招募双边运前网络.
- 该网络还参与处理声学降低的语音和一般认知功能.
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