Heil Peter, Mohamed Esraa S I, Matysiak Artur
Department of Systems Physiology of Learning, Leibniz Institute for Neurobiology, Magdeburg 39118, Germany; Center for Behavioral Brain Sciences, Magdeburg, Germany.
Department of Systems Physiology of Learning, Leibniz Institute for Neurobiology, Magdeburg 39118, Germany.
Hear Res. 2021 Oct;410:108349. doi: 10.1016/j.heares.2021.108349. Epub 2021 Sep 4.
Sounds consisting of multiple simultaneous or consecutive components can be detected by listeners when the stimulus levels of the components are lower than those needed to detect the individual components alone. The mechanisms underlying such spectral, spectrotemporal, temporal, or across-ear integration are not completely understood. Here, we report threshold measurements from human subjects for multicomponent stimuli (tone complexes, tone sequences, diotic or dichotic tones) and for their individual sinusoidal components in quiet. We examine whether the data are compatible with the detection model developed by Heil, Matysiak, and Neubauer (HMN model) to account for temporal integration (Heil et al. 2017), and we compare its performance to that of the statistical summation model (Green 1958), the model commonly used to account for spectral and spectrotemporal integration. In addition, we compare the performance of both models with respect to previously published thresholds for sequences of identical tones and for diotic tones. The HMN model is similar to the statistical summation model but is based on the assumption that the decision variable is a number of sensory events generated by the components via independent Poisson point processes. The rate of events is low without stimulation and increases with stimulation. The increase is proportional to the time-varying amplitude envelope of the bandpass-filtered component(s) raised to an exponent of 3. For an ideal observer, the decision variable is the sum of the events from all channels carrying information, for as long as they carry information. We find that the HMN model provides a better account of the thresholds for multicomponent stimuli than the statistical summation model, and it offers a unifying account of spectral, spectrotemporal, temporal, and across-ear integration at threshold.
当多个同时或连续的声音成分的刺激水平低于单独检测每个成分所需的水平时，听众仍能检测到这些声音。这种频谱、频谱时间、时间或跨耳整合背后的机制尚未完全明了。在此，我们报告了人类受试者在安静环境中对多成分刺激（音调复合体、音调序列、双耳或双声道音调）及其单个正弦成分的阈值测量结果。我们研究这些数据是否与Heil、Matysiak和Neubauer开发的用于解释时间整合的检测模型（HMN模型）（Heil等人，2017年）相符，并将其性能与统计求和模型（Green，1958年）进行比较，统计求和模型是通常用于解释频谱和频谱时间整合的模型。此外，我们还比较了这两种模型在已发表的相同音调序列和双耳音调阈值方面的性能。HMN模型与统计求和模型相似，但基于这样的假设：决策变量是成分通过独立泊松点过程产生的多个感觉事件。在没有刺激时事件发生率较低，且随刺激增加。增加的幅度与带通滤波成分的时变幅度包络的三次方成正比。对于理想观察者来说，决策变量是所有携带信息通道中事件的总和，只要它们携带信息。我们发现，HMN模型比统计求和模型能更好地解释多成分刺激的阈值，并且它为阈值下的频谱、频谱时间、时间和跨耳整合提供了一个统一的解释。
