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首页> 外文期刊>Journal of Computational Neuroscience >Estimating characteristic phase and delay from broadband interaural time difference tuning curves
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Estimating characteristic phase and delay from broadband interaural time difference tuning curves

机译：从宽带听觉时间差调谐曲线估计特征相位和延迟

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摘要

Characteristic delay and characteristic phase are shape parameters of interaural time difference tuning curves. The standard procedure for the estimation of these parameters is based on the measurement of delay curves measured for tonal stimuli with varying frequencies. Common to all procedures is the detection of a linear behavior of the phase spectrum. Hence a reliable estimate can only be expected if sufficiently many relevant frequencies are tested. Thus, the estimation precision depends on the given bandwidth. Based on a linear model, we develop and implement methods for the estimation of characteristic phase and delay from a single broadband tuning curve. We present two different estimation algorithms, one based on a Fourier-analytic interpretation of characteristic delay and phase, and the other based on mean square error minimization. Estimation precision and robustness of the algorithms are tested on artificially generated data with predetermined characteristic delay and phase values, and on sample data from electrophysiological measurements in birds and in mammals. Increasing the signal-to-noise ratio or the bandwidth increases the estimation accuracy of the algorithms. Frequency band location and strong rectification also affect the estimation accuracy. For realistic bandwidths and signal-to-noise ratios, the minimization algorithm reliably and robustly estimates characteristic delay and phase and is superior to the Fourier-analytic method. Bandwidth-dependent significance thresholds allow to assess whether the estimated characteristic delay and phase values are meaningful shape parameters of a measured tuning curve. These thresholds also indicate the sampling rates needed to obtain reliable estimates from interaural time difference tuning curves.
机译：特征延迟和特征相位是耳间时间差调谐曲线的形状参数。估计这些参数的标准程序基于对变化频率的音调刺激所测得的延迟曲线的测量。所有过程的共同点是检测相谱的线性行为。因此，只有在测试足够多的相关频率的情况下，才能期望获得可靠的估计。因此，估计精度取决于给定的带宽。基于线性模型，我们开发并实现了从单个宽带调谐曲线估计特征相位和延迟的方法。我们提出了两种不同的估计算法，一种基于特征延迟和相位的傅立叶解析解释，另一种基于均方误差最小化。该算法的估计精度和鲁棒性在具有预定特征延迟和相位值的人工生成的数据以及鸟类和哺乳动物的电生理测量的样本数据上进行了测试。增加信噪比或带宽可提高算法的估计精度。频段位置和强整流也影响估计精度。对于现实的带宽和信噪比，最小化算法可靠且鲁棒地估计特征延迟和相位，并且优于傅立叶分析法。带宽相关的重要性阈值允许评估估计的特征延迟和相位值是否是测量的调谐曲线的有意义的形状参数。这些阈值还指示了从耳间时间差调整曲线获得可靠估计所需的采样率。

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