Detection of Cerebral Reorganization Induced by Real-Time fMRI Feedback Training of Insula Activation: A Multivariate Investigation
Detection of Cerebral Reorganization Induced by Real-Time fMRI Feedback Training of Insula Activation: A Multivariate Investigation
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DOI：
10.1177/1545968310385128
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发表时间：
2011-03-01
影响因子：
4.2
通讯作者：
Sitaram, Ranganatha
中科院分区：
文献类型：
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作者：
Lee, Sangkyun;Ruiz, Sergio;Sitaram, Ranganatha
背景。实时功能磁共振成像（fMRI）研究表明，人类有意识地调节来自大脑限定区域的血流动力学信号，从而导致特定区域的行为后果。更好地确定不同大脑区域之间动态功能相互作用的性质以及自我调节训练导致的可塑性的方法仍在开发中。客观的。作者在训练 6 名健康参与者通过实时功能磁共振成像反馈自我调节岛叶皮层时，研究了大脑状态的变化。方法。作者使用多元模式分析来观察空间模式变化，并使用多元格兰杰因果关系模型来显示每个受试者在积极和消极情绪意象期间进行 5 次重复扫描过程中多个大脑区域的时间相互作用的变化，并提供有关岛叶激活水平的反馈。结果。反馈训练可以更加集中地招募与学习和情感相关的区域。有效的连接分析表明，初始训练与网络密度的增加相关；进一步的训练“修剪”可能是冗余的连接并“加强”相关连接。结论。作者展示了在学习局部大脑活动的意志控制过程中评估大脑重组的多变量方法的应用。这些发现提供了对训练诱导的康复学习技术机制的见解。作者预计，根据这一假设专门设计的未来研究可能能够基于各种技能任务的多个类似标准，构建技能学习期间大脑重组的通用指数。这些技术也许能够辨别补偿的恢复情况、与训练相关的剂量反应曲线，以及确定康复训练是否积极参与必要网络的方法。
Background. Studies with real-time functional magnetic resonance imaging (fMRI) demonstrate that humans volitionally regulate hemodynamic signals from circumscribed regions of the brain, leading to area-specific behavioral consequences. Methods to better determine the nature of dynamic functional interactions between different brain regions and plasticity due to self-regulation training are still in development. Objective. The authors investigated changes in brain states while training 6 healthy participants to self-regulate insular cortex by real-time fMRI feedback. Methods. The authors used multivariate pattern analysis to observe spatial pattern changes and a multivariate Granger causality model to show changes in temporal interactions in multiple brain areas over the course of 5 repeated scans per subject during positive and negative emotional imagery with feedback about the level of insular activation. Results. Feedback training leads to more spatially focused recruitment of areas relevant for learning and emotion. Effective connectivity analysis reveals that initial training is associated with an increase in network density; further training "prunes" presumably redundant connections and "strengthens" relevant connections. Conclusions. The authors demonstrate the application of multivariate methods for assessing cerebral reorganization during the learning of volitional control of local brain activity. The findings provide insight into mechanisms of training-induced learning techniques for rehabilitation. The authors anticipate that future studies, specifically designed with this hypothesis in mind, may be able to construct a universal index of cerebral reorganization during skill learning based on multiple similar criteria across various skilled tasks. These techniques may be able to discern recovery from compensation, dose-response curves related to training, and ways to determine whether rehabilitation training is actively engaging necessary networks.