贝叶斯的先前不确定性和意外性在动态环境中的声音本地化过程中引起了不同的神经模式
Burcu Bayram1, David Meijer2, Roberto Barumerli2,3
1Department of Cognition, Emotion, and Methods in Psychology, Faculty of Psychology, University of Vienna, Vienna, Austria. burcu.bayram@univie.ac.at.
Scientific reports
|March 6, 2025
概括
人类使用先前的知识来定位声音,当环境发生变化时更新它. 这项研究揭示了与听觉空间推理中的不确定性和惊喜相关的独特大脑活动模式.
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.
- 计算机建模 计算建模
背景情况:
- 听觉空间定位依赖于将先前信息与感官输入相结合,类似于贝叶斯原则.
- 虽然视觉空间处理得到了很好的研究,但听觉空间推理,特别是在动态环境中,仍然不太了解.
- 环境的波动性和不确定性会影响如何使用和更新先前信息.
研究的目的:
- 研究人类在噪音和挥发性环境中的听觉空间推理.
- 分析与先前的不确定性和环境变化相关的行为和神经模式.
- 探索贝叶斯原则在动态听觉本地化中的作用.
主要方法:
- 结合人类脑电图 (EEG) 和计算建模.
- 分析行为数据以确定声音本地化准确度和先前偏差.
- 检查了与环境统计和变化相关的时间和时间频率领域的神经活动.
主要成果:
- 参与者在稳定的环境中使用了先前的信息,但在环境转变后表现出惊和抛弃先验.
- 对于先前的不确定性和惊喜,确定了明显的EEG模式,反映了视觉任务中的发现.
- 这些EEG模式预测了逐个试验的声音定位错误,响应不确定性和先前偏差.
结论:
- 提供了新的行为和神经证据,支持贝叶斯推理在动态听觉本地化.
- 证明大脑根据环境波动和不确定性适应听觉空间估计.
- 突出了听觉系统中先前不确定性和惊喜的独特神经特征.
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