Ear Institute, University College London, 332 Gray's Inn Road, London WC1X 8EE, UK; Department of Psychiatry, University of Cambridge, Cambridge, UK.
Ear Institute, University College London, 332 Gray's Inn Road, London WC1X 8EE, UK.
Hear Res. 2021 Feb;400:108111. doi: 10.1016/j.heares.2020.108111. Epub 2020 Nov 12.
The notion that sensitivity to the statistical structure of the environment is pivotal to perception has recently garnered considerable attention. Here we investigated this issue in the context of hearing. Building on previous work (Sohoglu and Chait, 2016a; elife), stimuli were artificial 'soundscapes' populated by multiple (up to 14) simultaneous streams ('auditory objects') comprised of tone-pip sequences, each with a distinct frequency and pattern of amplitude modulation. Sequences were either temporally regular or random. We show that listeners' ability to detect abrupt appearance or disappearance of a stream is facilitated when scene streams were characterized by a temporally regular fluctuation pattern. The regularity of the changing stream as well as that of the background (non-changing) streams contribute independently to this effect. Remarkably, listeners benefit from regularity even when they are not consciously aware of it. These findings establish that perception of complex acoustic scenes relies on the availability of detailed representations of the regularities automatically extracted from multiple concurrent streams.
近来，人们越来越关注到对环境统计结构的敏感性对于感知具有关键作用。在此，我们在听觉背景下研究了这个问题。在先前工作（Sohoglu 和 Chait，2016a；elife）的基础上，我们使用了由多个（最多 14 个）同时存在的流（“听觉对象”）组成的人工“音景”，这些流由具有不同频率和幅度调制模式的音调序列组成。序列要么是规则的，要么是随机的。我们发现，当场景流具有规则的时变模式时，听众检测到流的突然出现或消失的能力会得到增强。变化流和背景（不变）流的规则性都独立地对这种效应做出贡献。值得注意的是，即使听众没有意识到这种规律性，他们也能从中受益。这些发现表明，复杂声学场景的感知依赖于从多个并发流中自动提取的详细规律的详细表示。
