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γ节律神经振荡：反映自闭症多感觉整合失调的一项重要生物指标

本站小编 Free考研考试/2022-01-01
贾磊, 徐玉帆, 王成, 任俊(), 汪俊()
浙江师范大学教师教育学院心理系, 金华 321004
收稿日期:2019-11-20出版日期:2021-01-15发布日期:2020-11-23
通讯作者:任俊,汪俊E-mail:drinren@163.com;jun.wang@zjnu.edu.cn

基金资助:* 全国教育科学规划国家一般项目“多模态教育视角下自闭症儿童跨通道感觉统合障碍的神经机制及干预研究”(BBA180083)

Gamma oscillation: An important biomarker reflecting multisensory integration deficits in autism spectrum disorders

JIA Lei, XU Yu-fan, WANG Cheng, REN Jun(), WANG Jun()
Department of Psychology, College of Teacher Education, Zhejiang Normal University, Jinhua 321004, China
Received:2019-11-20Online:2021-01-15Published:2020-11-23
Contact:REN Jun,WANG Jun E-mail:drinren@163.com;jun.wang@zjnu.edu.cn






摘要/Abstract


摘要： 多感觉整合是对不同感官信息进行选择、联系、统一乃至解释的加工过程, 它需要神经系统不同功能区域的共同投入与相互协调, 以实现多种感觉信息的时间捆绑以及全局性的预测编码。而γ神经振荡因具有反映神经皮层兴奋/抑制的平衡状况, 实现多感官信息的时间同步, 以及通过跨频耦合实现全局性预测编码的特点, 在多感觉整合的加工过程中发挥着重要作用。相比正常个体, 自闭症患者神经系统中的GABA中间神经元存在结构与功能异常, 导致γ神经振荡紊乱, 由此破坏了正常的时间同步以及预测编码加工, 并最终引发多感觉整合失调。基于上述因果关联, 未来研究可结合无创可逆性干预技术, 以γ节律神经振荡为生物反馈指标, 形成科学系统化的临床干预治疗方案。


表1神经振荡频谱能量分析提取的不同方法及其衍生出的不同类型
频谱能量类型 刺激/反应的锁相情况 与锁相系数的相关性 提取分析方法
总频谱能量(total) 非确定性的 根据锁相系数的大小来确定神经振荡是诱发型的还是引发型的 基于单个试次做频谱/时频分析后, 再对所有试次进行平均;
诱发型(evoked) 高锁相 正相关 先在时域对试次平均后进行频谱/时频分析;
引发型(induced) 低锁相或非锁相 负相关 用总的神经振荡能量减去诱发性的神经振荡能量;
自发型(spontaneous) 非确定性的 非确定性的 对连续记录的EEG/MEG数据进行分段后, 基于每个分段进行频谱/时频分析, 之后再做平均。

表1神经振荡频谱能量分析提取的不同方法及其衍生出的不同类型
频谱能量类型 刺激/反应的锁相情况 与锁相系数的相关性 提取分析方法
总频谱能量(total) 非确定性的 根据锁相系数的大小来确定神经振荡是诱发型的还是引发型的 基于单个试次做频谱/时频分析后, 再对所有试次进行平均;
诱发型(evoked) 高锁相 正相关 先在时域对试次平均后进行频谱/时频分析;
引发型(induced) 低锁相或非锁相 负相关 用总的神经振荡能量减去诱发性的神经振荡能量;
自发型(spontaneous) 非确定性的 非确定性的 对连续记录的EEG/MEG数据进行分段后, 基于每个分段进行频谱/时频分析, 之后再做平均。







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