Department of Biophysics, Radboud University, Nijmegen, 6525 AJ, The Netherlands.
Donders Centre for Neuroscience, Radboud University, Nijmegen, 6525 AJ, The Netherlands.
Sci Rep. 2021 Jan 25;11(1):2150. doi: 10.1038/s41598-021-81232-5.
The latency of the auditory steady-state response (ASSR) may provide valuable information regarding the integrity of the auditory system, as it could potentially reveal the presence of multiple intracerebral sources. To estimate multiple latencies from high-order ASSRs, we propose a novel two-stage procedure that consists of a nonparametric estimation method, called apparent latency from phase coherence (ALPC), followed by a heuristic sequential forward selection algorithm (SFS). Compared with existing methods, ALPC-SFS requires few prior assumptions, and is straightforward to implement for higher-order nonlinear responses to multi-cosine sound complexes with their initial phases set to zero. It systematically evaluates the nonlinear components of the ASSRs by estimating multiple latencies, automatically identifies involved ASSR components, and reports a latency consistency index. To verify the proposed method, we performed simulations for several scenarios: two nonlinear subsystems with different or overlapping outputs. We compared the results from our method with predictions from existing, parametric methods. We also recorded the EEG from ten normal-hearing adults by bilaterally presenting superimposed tones with four frequencies that evoke a unique set of ASSRs. From these ASSRs, two major latencies were found to be stable across subjects on repeated measurement days. The two latencies are dominated by low-frequency (LF) (near 40 Hz, at around 41-52 ms) and high-frequency (HF) (> 80 Hz, at around 21-27 ms) ASSR components. The frontal-central brain region showed longer latencies on LF components, but shorter latencies on HF components, when compared with temporal-lobe regions. In conclusion, the proposed nonparametric ALPC-SFS method, applied to zero-phase, multi-cosine sound complexes is more suitable for evaluating embedded nonlinear systems underlying ASSRs than existing methods. It may therefore be a promising objective measure for hearing performance and auditory cortex (dys)function.
听觉稳态响应(ASSR)的潜伏期可以提供有关听觉系统完整性的有价值的信息,因为它可能揭示多个颅内源的存在。为了从高阶 ASSR 中估计多个潜伏期,我们提出了一种新的两阶段方法,该方法由一种称为相位相干的表观潜伏期(ALPC)的非参数估计方法和启发式顺序前向选择算法(SFS)组成。与现有方法相比,ALPC-SFS 需要很少的先验假设,并且对于具有零初始相位的多余弦声音复合的高阶非线性响应,它易于实现。它通过估计多个潜伏期来系统地评估 ASSR 的非线性成分,自动识别涉及的 ASSR 成分,并报告潜伏期一致性指数。为了验证所提出的方法,我们对几种情况进行了模拟:两个具有不同或重叠输出的非线性子系统。我们将我们的方法的结果与现有参数方法的预测进行了比较。我们还通过双侧呈现四个频率的叠加音,在 10 名听力正常的成年人中记录了 EEG,这些频率引发了一组独特的 ASSR。从这些 ASSR 中,我们发现两个主要潜伏期在重复测量日在受试者之间是稳定的。这两个潜伏期主要由低频(LF)(接近 40 Hz,约 41-52 ms)和高频(HF)(>80 Hz,约 21-27 ms)ASSR 分量主导。与颞叶区域相比,额叶-中央脑区在 LF 分量上显示出较长的潜伏期,但在 HF 分量上显示出较短的潜伏期。总之,与现有方法相比,应用于零相位、多余弦声音复合的非参数 ALPC-SFS 方法更适合评估 ASSR 下的嵌入式非线性系统。因此,它可能是一种有前途的客观听力和听觉皮层(功能障碍)测量方法。