Department of Psychology, University of Leipzig Leipzig, Germany ; Max Planck Institute for Human Cognitive and Brain Sciences Leipzig, Germany.
Front Psychol. 2013 Aug 20;4:534. doi: 10.3389/fpsyg.2013.00534. eCollection 2013.
Auditory scene analysis describes the ability to segregate relevant sounds out from the environment and to integrate them into a single sound stream using the characteristics of the sounds to determine whether or not they are related. This study aims to contrast task performances in objective threshold measurements of segregation and integration using identical stimuli, manipulating two variables known to influence streaming, inter-stimulus-interval (ISI) and frequency difference (Δf). For each measurement, one parameter (either ISI or Δf) was held constant while the other was altered in a staircase procedure. By using this paradigm, it is possible to test within-subject across multiple conditions, covering a wide Δf and ISI range in one testing session. The objective tasks were based on across-stream temporal judgments (facilitated by integration) and within-stream deviance detection (facilitated by segregation). Results show the objective integration task is well suited for combination with the staircase procedure, as it yields consistent threshold measurements for separate variations of ISI and Δf, as well as being significantly related to the subjective thresholds. The objective segregation task appears less suited to the staircase procedure. With the integration-based staircase paradigm, a comprehensive assessment of streaming thresholds can be obtained in a relatively short space of time. This permits efficient threshold measurements particularly in groups for which there is little prior knowledge on the relevant parameter space for streaming perception.
听觉场景分析描述了一种能力，即能够从环境中分离出相关的声音，并将它们整合到单个声音流中，使用声音的特征来确定它们是否相关。本研究旨在对比使用相同刺激进行的分离和整合的客观阈值测量中的任务表现，通过操纵两个已知会影响流的变量（刺激间间隔（ISI）和频率差（Δf））来实现。对于每个测量，一个参数（ISI 或 Δf）保持不变，而另一个则通过阶梯程序进行改变。通过使用这种范式，可以在一个测试会话中测试多个条件下的个体内差异，涵盖广泛的 Δf 和 ISI 范围。客观任务基于跨流的时间判断（由整合促进）和内流的偏差检测（由分离促进）。结果表明，客观的整合任务非常适合与阶梯程序相结合，因为它可以针对 ISI 和 Δf 的单独变化产生一致的阈值测量，并且与主观阈值显著相关。客观的分离任务似乎不太适合阶梯程序。使用基于整合的阶梯范式，可以在相对较短的时间内获得流的综合阈值评估。这允许在对流感知的相关参数空间几乎没有先验知识的群体中进行有效的阈值测量。
