Department of Translational Neuroscience, Faculty of Medicine and Health Science, University of Antwerp, Antwerp, Belgium; University Department of Otorhinolaryngology and Head and Neck Surgery, Antwerp University Hospital, Edegem, Belgium.
University Department of Otorhinolaryngology and Head and Neck Surgery, Antwerp University Hospital, Edegem, Belgium.
Hear Res. 2022 Jul;420:108489. doi: 10.1016/j.heares.2022.108489. Epub 2022 Mar 22.
The current limited understanding of tinnitus neurophysiology is one of the major obstacles in developing effective treatments for chronic tinnitus. As such, there is an urgent need for knowledge on underlying neural and/or neurobehavioral correlates that might function as potential biomarkers for tinnitus. We aimed to develop a model for the detection of tinnitus cases based on such potential biomarkers. In a first step, data from twenty patients suffering from chronic tinnitus, but no concurrent hearing loss or psychological complaints, were compared to data from twenty matched controls. Cortical auditory evoked potentials (CAEP) were elicited using a standard oddball paradigm. Source estimation and brain signal variability were analyzed to investigate putative differences between tinnitus patients and controls. Other examinations included standard audiometry, speech understanding in quiet and noisy conditions, and cognitive testing using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). The P300 component, a response to unexpected but relevant stimuli, was significantly reduced in the tinnitus group. Source estimation revealed that the response of tinnitus patients was characterized by a decreased activity in temporal cortex, parahippocampus and insula. Brain signal variability on fine time scales was significantly higher in the tinnitus group, suggesting that tinnitus patients rely more strongly on local information processing. Furthermore, tinnitus was associated with a decreased cognitive performance, especially on tasks measuring delayed memory. In a second step, a logistic regression model was constructed based on CAEP activity, brain signal variability and RBANS scores. This model performed significantly above chance level when detecting tinnitus cases in an unseen dataset (accuracy of 75%, area under the ROC curve of 0.86). The successful classification between tinnitus cases and controls demonstrates the potential value of the proposed combination of biomarkers. Moreover, the identified associations between tinnitus, auditory evoked activity and cognitive performance point towards a significant contribution of top-down information processing in the perception of tinnitus.
目前对耳鸣神经生理学的有限了解是开发慢性耳鸣有效治疗方法的主要障碍之一。因此,迫切需要了解潜在的神经和/或神经行为相关性,这些相关性可能作为耳鸣的潜在生物标志物。我们旨在基于这些潜在的生物标志物开发一种用于检测耳鸣病例的模型。在第一步中,将 20 名患有慢性耳鸣但无伴随听力损失或心理投诉的患者的数据与 20 名匹配的对照组的数据进行比较。使用标准的Oddball 范式诱发皮质听觉诱发电位(CAEP)。通过源估计和大脑信号变异性分析来研究耳鸣患者与对照组之间的潜在差异。其他检查包括标准听力测试、安静和嘈杂环境下的言语理解以及使用重复神经心理状态评估量表(RBANS)进行认知测试。对意外但相关刺激的反应 P300 成分在耳鸣组中显著降低。源估计表明,耳鸣患者的反应特征是颞叶、海马旁回和脑岛的活动减少。耳鸣组的精细时间尺度上的大脑信号变异性显著更高,表明耳鸣患者更依赖于局部信息处理。此外,耳鸣与认知表现下降有关,特别是在测试延迟记忆的任务上。在第二步中,基于 CAEP 活动、大脑信号变异性和 RBANS 分数构建了逻辑回归模型。该模型在未见数据集(准确率为 75%,ROC 曲线下面积为 0.86)中检测耳鸣病例时表现出明显高于随机水平的性能。成功地对耳鸣病例和对照组进行分类表明,所提出的生物标志物组合具有潜在价值。此外,耳鸣、听觉诱发电活动和认知表现之间的关联表明,自上而下的信息处理在耳鸣感知中具有重要贡献。