Papageorgiou T Dorina, Curtis William A, McHenry Monica, LaConte Stephen M
Neuroscience Department, Baylor College of Medicine, Houston, TX 77030, USA.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:5377-80. doi: 10.1109/IEMBS.2009.5333703.
This study examines the effects of neurofeedback provided by support vector machine (SVM) classification-based real-time functional magnetic resonance imaging (rt-fMRI) during two types of motor tasks. This approach also enables the examination of the neural regions associated with predicting mental states in different domains of motor control, which is critical to further our understanding of normal and impaired function. Healthy volunteers (n = 13) performed both a simple button tapping task, and a covert rate-of-speech counting task. The average prediction accuracy was approximately 95% for the button tapping task and 86% for the speech task. However, subsequent offline analysis revealed that classification of the initial runs was significantly lower - 75% (p<0.001) for button and 72% (p<0.005) for speech. To explore this effect, a group analysis was performed using the spatial maps derived from the SVM models, which showed significant differences between the two fMRI runs. One possible explanation for the difference in spatial patterns and the asymmetry in the prediction accuracies is that when subjects are actively engaged in the task (i.e. when they are trying to control a computer interface), they are generating stronger BOLD responses in terms of both intensity and spatial extent.
本研究考察了基于支持向量机（SVM）分类的实时功能磁共振成像（rt-fMRI）在两种运动任务中所提供的神经反馈的效果。这种方法还能够考察与预测运动控制不同领域中的心理状态相关的神经区域，这对于深化我们对正常和受损功能的理解至关重要。健康志愿者（n = 13）执行了简单的按键任务和隐蔽的语速计数任务。按键任务的平均预测准确率约为95%，言语任务的平均预测准确率约为86%。然而，随后的离线分析显示，初始运行的分类准确率显著更低——按键任务为75%（p<0.001），言语任务为72%（p<0.005）。为了探究这种效应，使用从SVM模型得出的空间图谱进行了组分析，结果显示两次功能磁共振成像运行之间存在显著差异。空间模式差异和预测准确率不对称的一个可能解释是，当受试者积极参与任务时（即当他们试图控制计算机界面时），他们在强度和空间范围方面都会产生更强的血氧水平依赖（BOLD）反应。
