Translational Hearing Research, The Bionics Institute, East Melbourne, Victoria, Australia.
Department of ENT, Head and Neck Surgery, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Ear Hear. 2020 Sep/Oct;41(5):1187-1195. doi: 10.1097/AUD.0000000000000836.
Functional near-infrared spectroscopy (fNIRS) is a brain imaging technique particularly suitable for hearing studies. However, the nature of fNIRS responses to auditory stimuli presented at different stimulus intensities is not well understood. In this study, we investigated whether fNIRS response amplitude was better predicted by stimulus properties (intensity) or individually perceived attributes (loudness).
Twenty-two young adults were included in this experimental study. Four different stimulus intensities of a broadband noise were used as stimuli. First, loudness estimates for each stimulus intensity were measured for each participant. Then, the 4 stimulation intensities were presented in counterbalanced order while recording hemoglobin saturation changes from cortical auditory brain areas. The fNIRS response was analyzed in a general linear model design, using 3 different regressors: a non-modulated, an intensity-modulated, and a loudness-modulated regressor.
Higher intensity stimuli resulted in higher amplitude fNIRS responses. The relationship between stimulus intensity and fNIRS response amplitude was better explained using a regressor based on individually estimated loudness estimates compared with a regressor modulated by stimulus intensity alone.
Brain activation in response to different stimulus intensities is more reliant upon individual loudness sensation than physical stimulus properties. Therefore, in measurements using different auditory stimulus intensities or subjective hearing parameters, loudness estimates should be examined when interpreting results.
功能近红外光谱（fNIRS）是一种特别适合听力研究的脑成像技术。然而，对于在不同刺激强度下呈现的听觉刺激，fNIRS 响应的性质尚不清楚。在这项研究中，我们研究了 fNIRS 响应幅度是由刺激特性（强度）还是个体感知属性（响度）更好地预测。
本实验研究纳入了 22 名年轻成年人。宽带噪声的四个不同刺激强度用作刺激。首先，为每个参与者测量每个刺激强度的响度估计。然后，以平衡的顺序呈现 4 种刺激强度，同时记录皮质听觉脑区的血红蛋白饱和度变化。使用 3 种不同的回归器（非调制回归器、强度调制回归器和响度调制回归器）在广义线性模型设计中分析 fNIRS 响应。
更高强度的刺激导致更高幅度的 fNIRS 响应。与仅由刺激强度调制的回归器相比，基于个体估计的响度估计的回归器更好地解释了刺激强度与 fNIRS 响应幅度之间的关系。
对不同刺激强度的大脑激活更依赖于个体的响度感觉，而不是物理刺激特性。因此，在使用不同听觉刺激强度或主观听力参数进行测量时，在解释结果时应检查响度估计。
