Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Department of Audiology, Stanford University, Stanford, California, United States of America.
PLoS One. 2022 Feb 8;17(2):e0263516. doi: 10.1371/journal.pone.0263516. eCollection 2022.
The ability to determine a sound's location is critical in everyday life. However, sound source localization is severely compromised for patients with hearing loss who receive bilateral cochlear implants (BiCIs). Several patient factors relate to poorer performance in listeners with BiCIs, associated with auditory deprivation, experience, and age. Critically, characteristic errors are made by patients with BiCIs (e.g., medial responses at lateral target locations), and the relationship between patient factors and the type of errors made by patients has seldom been investigated across individuals. In the present study, several different types of analysis were used to understand localization errors and their relationship with patient-dependent factors (selected based on their robustness of prediction). Binaural hearing experience is required for developing accurate localization skills, auditory deprivation is associated with degradation of the auditory periphery, and aging leads to poorer temporal resolution. Therefore, it was hypothesized that earlier onsets of deafness would be associated with poorer localization acuity and longer periods without BiCI stimulation or older age would lead to greater amounts of variability in localization responses. A novel machine learning approach was introduced to characterize the types of errors made by listeners with BiCIs, making them simple to interpret and generalizable to everyday experience. Sound localization performance was measured in 48 listeners with BiCIs using pink noise trains presented in free-field. Our results suggest that older age at testing and earlier onset of deafness are associated with greater average error, particularly for sound sources near the center of the head, consistent with previous research. The machine learning analysis revealed that variability of localization responses tended to be greater for individuals with earlier compared to later onsets of deafness. These results suggest that early bilateral hearing is essential for best sound source localization outcomes in listeners with BiCIs.
确定声音位置的能力在日常生活中至关重要。然而，对于接受双侧人工耳蜗植入（BiCIs）的听力损失患者，声源定位能力严重受损。一些患者因素与接受 BiCIs 的患者的表现较差有关，这些因素与听觉剥夺、经验和年龄有关。重要的是，BiCIs 患者会出现特征性错误（例如，在外侧目标位置出现内侧反应），并且患者因素与患者所犯错误类型之间的关系很少在个体之间进行研究。在本研究中，使用了几种不同类型的分析来理解定位错误及其与患者相关因素之间的关系（根据其预测稳健性进行选择）。双耳听觉经验是发展准确定位技能所必需的，听觉剥夺与听觉外围的退化有关，而衰老会导致较差的时间分辨率。因此，假设耳聋的早期发作与较差的定位锐度有关，并且 BiCI 刺激的时间较长或年龄较大，会导致定位反应的变异性更大。引入了一种新的机器学习方法来描述 BiCIs 患者所犯错误的类型，使其易于解释且可推广到日常经验。使用自由场中的粉红噪声序列在 48 名接受 BiCIs 的患者中测量声音定位性能。我们的研究结果表明，测试时年龄较大和耳聋发作较早与平均误差较大有关，尤其是对于头部中心附近的声源，这与之前的研究一致。机器学习分析表明，与耳聋发作较晚的个体相比，耳聋发作较早的个体的定位反应变异性更大。这些结果表明，双侧早期听力对接受 BiCIs 的患者的最佳声源定位结果至关重要。
