Qiao Jianping, Wang Zhishun, Zhao Guihu, Huo Yuankai, Herder Carl L, Sikora Chamonix O, Peterson Bradley S
School of Physics and Electronics, Shandong Province Key Laboratory of Medical Physics and Image Processing Technology, Institute of Data Science and Technology, Shandong Normal University, Jinan, China.
Department of Psychiatry, Columbia University, New York, NY, United States of America.
PLoS One. 2017 Jul 31;12(7):e0179255. doi: 10.1371/journal.pone.0179255. eCollection 2017.
The aim of this study was to identify differences in functional and effective brain connectivity between persons who stutter (PWS) and typically developing (TD) fluent speakers, and to assess whether those differences can serve as biomarkers to distinguish PWS from TD controls. We acquired resting-state functional magnetic resonance imaging data in 44 PWS and 50 TD controls. We then used Independent Component Analysis (ICA) together with Hierarchical Partner Matching (HPM) to identify networks of robust, functionally connected brain regions that were highly reproducible across participants, and we assessed whether connectivity differed significantly across diagnostic groups. We then used Granger Causality (GC) to study the causal interactions (effective connectivity) between the regions that ICA and HPM identified. Finally, we used a kernel support vector machine to assess how well these measures of functional connectivity and granger causality discriminate PWS from TD controls. Functional connectivity was stronger in PWS compared with TD controls in the supplementary motor area (SMA) and primary motor cortices, but weaker in inferior frontal cortex (IFG, Broca's area), caudate, putamen, and thalamus. Additionally, causal influences were significantly weaker in PWS from the IFG to SMA, and from the basal ganglia to IFG through the thalamus, compared to TD controls. ICA and GC indices together yielded an accuracy of 92.7% in classifying PWS from TD controls. Our findings suggest the presence of dysfunctional circuits that support speech planning and timing cues for the initiation and execution of motor sequences in PWS. Our high accuracy of classification further suggests that these aberrant brain features may serve as robust biomarkers for PWS.
本研究的目的是确定口吃者(PWS)与发育正常(TD)的流利说话者在功能和有效脑连接方面的差异,并评估这些差异是否可作为区分PWS与TD对照组的生物标志物。我们获取了44名PWS和50名TD对照组的静息态功能磁共振成像数据。然后,我们使用独立成分分析(ICA)和分层伙伴匹配(HPM)来识别在参与者之间具有高度可重复性的、功能连接的稳健脑区网络,并评估诊断组之间的连接性是否存在显著差异。接着,我们使用格兰杰因果关系(GC)来研究ICA和HPM识别出的区域之间的因果相互作用(有效连接)。最后,我们使用核支持向量机来评估这些功能连接和格兰杰因果关系的测量方法在区分PWS与TD对照组方面的效果如何。与TD对照组相比,PWS在辅助运动区(SMA)和初级运动皮层的功能连接更强,但在额下回(IFG,布洛卡区)、尾状核、壳核和丘脑的功能连接较弱。此外,与TD对照组相比,PWS从IFG到SMA以及从基底神经节通过丘脑到IFG的因果影响明显较弱。ICA和GC指数共同在区分PWS与TD对照组时的准确率为92.7%。我们的研究结果表明,PWS中存在功能失调的回路,这些回路支持语音计划以及运动序列启动和执行的时间线索。我们较高的分类准确率进一步表明,这些异常的脑特征可能是PWS的有力生物标志物。