Lin Feng, Cheng Shao-Qiang, Qi Dong-Qing, Jiang Yu-Er, Lyu Qian-Qian, Zhong Li-Juan, Jiang Zhong-Li
Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
Department of Rehabilitation Medicine, The Affiliated Sir Run Run Hospital of Nanjing Medical University, Nanjing, Jiangsu, China.
PeerJ. 2020 Oct 1;8:e10057. doi: 10.7717/peerj.10057. eCollection 2020.
Source localization and functional brain network modeling are methods of identifying critical regions during cognitive tasks. The first activity estimates the relative differences of the signal amplitudes in regions of interest (ROI) and the second activity measures the statistical dependence among signal fluctuations. We hypothesized that the source amplitude-functional connectivity relationship decouples or reverses in persons having brain impairments. Five Broca's aphasics with five matched cognitively healthy controls underwent overt picture-naming magnetoencephalography scans. The gamma-band (30-45 Hz) phase-locking values were calculated as connections among the ROIs. We calculated the partial correlation coefficients between the amplitudes and network measures and detected four node types, including hothubs with high amplitude and high connectivity, coldhubs with high connectivity but lower amplitude, non-hub hotspots, and non-hub coldspots. The results indicate that the high-amplitude regions are not necessarily highly connected hubs. Furthermore, the Broca aphasics utilized different hothub sets for the naming task. Both groups had dark functional networks composed of coldhubs. Thus, source amplitude-functional connectivity relationships could help reveal functional reorganizations in patients. The amplitude-connectivity combination provides a new perspective for pathological studies of the brain's dark functional networks.
源定位和功能性脑网络建模是在认知任务期间识别关键区域的方法。第一种活动估计感兴趣区域（ROI）中信号幅度的相对差异，第二种活动测量信号波动之间的统计依赖性。我们假设在患有脑损伤的个体中，源幅度-功能连接关系会解耦或反转。五名布罗卡失语症患者和五名匹配的认知健康对照者接受了公开图片命名的脑磁图扫描。伽马波段（30 - 45赫兹）的锁相值被计算为ROI之间的连接。我们计算了幅度与网络测量之间的偏相关系数，并检测到四种节点类型，包括具有高幅度和高连接性的热枢纽、具有高连接性但较低幅度的冷枢纽、非枢纽热点和非枢纽冷点。结果表明，高幅度区域不一定是高度连接的枢纽。此外，布罗卡失语症患者在命名任务中使用了不同的热枢纽集。两组都有由冷枢纽组成的暗功能网络。因此，源幅度-功能连接关系有助于揭示患者的功能重组。幅度-连接性组合为大脑暗功能网络的病理研究提供了新的视角。
