学术论文

      非流畅性失语症脑功能网络分析

      Functional brain network analyses of language functions in non-fluent aphasics

      摘要:
      目的:为非流畅性失语症建立图片命名任务的脑功能活动网络模型并与健康对照比较,分析失语症患者的脑功能网络特征.方法:非流畅性失语症患者和健康对照者各5例,接受图片命名任务下的脑磁图检测.以脑磁图的信号检测位点为节点,位点间的加权相延迟指数的去偏二乘估计值为连线权重,分别为命名任务的五个时间段构建脑网络.通过与基线水平进行比较,采用自举法重采样技术,在99%置信水平上进行检验,最终确定需要保留的连线.网络模型建成后,对患者和对照组进行参数计算和可视化分析.结果:健康受试在显示与图片命名任务预期相符的双枕叶和左侧额颞叶网络结构以外,还在400-600ms的音声组构阶段呈现的右脑为主的同步活动.失语症在命名任务的各个时间段,都呈现节点地位的扁平化和模块度下降,并且存在中线附近的联系强化和反应模式的迟滞.结论:①右脑同步功能活动参与了常人的图片命名过程.②失语症患者的脑功能网络倾向于围绕中线部位发生重组.③以语言任务为基础的脑磁图网络建模方法可用于失语症脑功能重组研究.
      Abstract:
      Objective:Modeling the functional brain networks of picture naming for non-fluent aphasics.To explore features of aphasics' brain networks by comparing with health control group.Method:Five aphasics and five health subjects participated in this study.They received magnetoencephalography (MEG) scan with picture naming tasks.The study established brain models for five naming stages respectively.In the brain network models,MEG sensors were nodes,and synchronization activations were lines.Values of debiased estimator of the squared weighted phase lag index were weights of the lines.To decide whether a line should be accepted or not,this study used bootstrap method and tested the phase lag index on 99% confidence interval level by comparing the phase lag values with baseline ones.Based on the models,the study visualized the networks and analyzed their parameters.Result:The health group showed expected network structures on their bilateral occipital lobes and left frontaltemporal lobes,while they also exhibited right brain synchronizations in phonetic processing stage of 400600ms.Aphasics showed enhanced synchronization around middle line,delayed network patterns,and decreased network parameters in comparing with health controls,including hierarchical gradients and modularities.Conclusion:For health subjects,picture naming evoked synchronizations in the right brain.For aphasics,functional brain networks reorganized around middle line.Functional brain network modeling based on MEG scanning with language tasks are available for detecting mechanisms of functional brain reorganization in aphasics.
      作者: 林枫 [1] 江钟立 [1] 程少强 [1] 祁冬晴 [1] 吴婷 [2] 向伟华 [1] 高婧 [1]
      作者单位: 南京医科大学第一附属医院康复医学科,南京,210029 南京医科大学附属南京脑科医院脑磁图室
      刊 名: 中国康复医学杂志 ISTICPKU
      年,卷(期): 2017, 32(3)
      分类号: R492 R743
      在线出版日期: 2017年4月18日
      基金项目: 江苏省科技支撑计划,国家自然科学基金项目,南京市科委项目,江苏省“六大人才高峰”资助项目