Zimmerman Benjamin J, Abraham Ivan, Schmidt Sara A, Baryshnikov Yuliy, Husain Fatima T
Beckman Institute for Advanced Science & Technology, University of Illinois at Urbana-Champaign, IL, USA.
Department of Electrical & Computer Engineering, University of Illinois at Urbana-Champaign, IL, USA.
Netw Neurosci. 2018 Oct 1;3(1):67-89. doi: 10.1162/netn_a_00053. eCollection 2019.
Chronic tinnitus is a common and sometimes debilitating condition that lacks scientific consensus on physiological models of how the condition arises as well as any known cure. In this study, we applied a novel cyclicity analysis, which studies patterns of leader-follower relationships between two signals, to resting-state functional magnetic resonance imaging (rs-fMRI) data of brain regions acquired from subjects with and without tinnitus. Using the output from the cyclicity analysis, we were able to differentiate between these two groups with 58-67% accuracy by using a partial least squares discriminant analysis. Stability testing yielded a 70% classification accuracy for identifying individual subjects' data across sessions 1 week apart. Additional analysis revealed that the pairs of brain regions that contributed most to the dissociation between tinnitus and controls were those connected to the amygdala. In the controls, there were consistent temporal patterns across frontal, parietal, and limbic regions and amygdalar activity, whereas in tinnitus subjects, this pattern was much more variable. Our findings demonstrate a proof-of-principle for the use of cyclicity analysis of rs-fMRI data to better understand functional brain connectivity and to use it as a tool for the differentiation of patients and controls who may differ on specific traits.
慢性耳鸣是一种常见且有时会使人衰弱的病症，对于其发病的生理模型以及任何已知的治疗方法，科学界尚未达成共识。在本研究中，我们应用了一种新颖的周期性分析方法，该方法研究两个信号之间的主从关系模式，并将其应用于从患有和未患耳鸣的受试者获取的脑区静息态功能磁共振成像（rs-fMRI）数据。利用周期性分析的输出结果，我们通过偏最小二乘判别分析，能够以58%至67%的准确率区分这两组。稳定性测试显示，对于识别相隔1周的不同时段的个体受试者数据，分类准确率为70%。进一步分析表明，对耳鸣患者与对照组之间的区分贡献最大的脑区对是那些与杏仁核相连的脑区。在对照组中，额叶、顶叶、边缘叶区域以及杏仁核活动存在一致的时间模式，而在耳鸣患者中，这种模式则更为多变。我们的研究结果证明了对rs-fMRI数据进行周期性分析以更好地理解脑功能连接，并将其用作区分在特定特征上可能存在差异的患者与对照组的工具的原理验证。
